diff --git a/environment.yml b/environment.yml index e386acb..6ecd7c2 100644 --- a/environment.yml +++ b/environment.yml @@ -2,7 +2,7 @@ name: example-environment channels: - conda-forge dependencies: - - cython + - cython>=0.29.20, <3.0.0 - scipy - numpy - qutip @@ -12,6 +12,6 @@ dependencies: - cycler - pathos - dill - - scqubits==2.0 - - ipywidgets + - scqubits==3.2 - sympy + - ipyvuetify diff --git a/examples/demo_fluxonium.ipynb b/examples/demo_fluxonium.ipynb index a9f510f..f40ac13 100644 --- a/examples/demo_fluxonium.ipynb +++ b/examples/demo_fluxonium.ipynb @@ -251,7 +251,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.9.15" + "version": "3.9.16" }, "pycharm": { "stem_cell": { diff --git a/examples/demo_gui.ipynb b/examples/demo_gui.ipynb index 3f44ee7..ae094dd 100644 --- a/examples/demo_gui.ipynb +++ b/examples/demo_gui.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 1, + "execution_count": 2, "id": "7a5d2415", "metadata": {}, "outputs": [], @@ -12,14 +12,14 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 3, "id": "84376185", "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "98e57c8424b8474a8039e6fdb0525397", + "model_id": "864b110590264f9bb1decc3cdb8996d3", "version_major": 2, "version_minor": 0 }, @@ -34,7 +34,7 @@ "data": { "text/plain": [] }, - "execution_count": 2, + "execution_count": 3, "metadata": {}, "output_type": "execute_result" } @@ -53,13 +53,13 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 4, "id": "fcdc5bb1", "metadata": {}, "outputs": [ { "data": { - "application/pdf": 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", 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" ] }, - "execution_count": 3, + "execution_count": 4, "metadata": {}, "output_type": "execute_result" } diff --git a/examples/demo_hilbertspace.ipynb b/examples/demo_hilbertspace.ipynb index 9175efd..14ed6e5 100644 --- a/examples/demo_hilbertspace.ipynb +++ b/examples/demo_hilbertspace.ipynb @@ -1,7 +1,6 @@ { "cells": [ { - "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ @@ -16,7 +15,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 2, "metadata": { "ExecuteTime": { "end_time": "2020-03-31T11:43:53.057632Z", @@ -34,7 +33,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ @@ -44,7 +42,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ @@ -65,7 +62,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 3, "metadata": { "ExecuteTime": { "end_time": "2020-03-31T11:43:54.037807Z", @@ -102,7 +99,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 4, "metadata": { "ExecuteTime": { "end_time": "2020-03-31T11:43:54.772581Z", @@ -143,7 +140,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "metadata": { "pycharm": { @@ -156,7 +152,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 5, "metadata": { "ExecuteTime": { "end_time": "2020-03-31T11:43:56.149663Z", @@ -209,7 +205,7 @@ " 0. 0. 0. 0. 0. 33.963]]" ] }, - "execution_count": 4, + "execution_count": 5, "metadata": {}, "output_type": "execute_result" } @@ -220,7 +216,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ @@ -229,7 +224,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 6, "metadata": {}, "outputs": [ { @@ -238,7 +233,7 @@ "True" ] }, - "execution_count": 5, + "execution_count": 6, "metadata": {}, "output_type": "execute_result" } @@ -248,7 +243,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "metadata": { "pycharm": { @@ -261,7 +255,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "metadata": { "pycharm": { @@ -275,7 +268,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ @@ -286,7 +278,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 7, "metadata": { "ExecuteTime": { "end_time": "2020-03-31T11:44:00.099411Z", @@ -332,7 +324,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "metadata": { "pycharm": { @@ -345,7 +336,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 8, "metadata": { "ExecuteTime": { "end_time": "2020-03-31T11:44:03.627440Z", @@ -414,7 +405,7 @@ " 0. 0. 0. 34.053 ]]" ] }, - "execution_count": 7, + "execution_count": 8, "metadata": {}, "output_type": "execute_result" } @@ -425,7 +416,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ @@ -434,7 +424,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 9, "metadata": { "ExecuteTime": { "end_time": "2020-03-31T11:44:06.327709Z", @@ -456,7 +446,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ @@ -467,32 +456,18 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 10, "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "f3f947cb87bf4b198948a37ee4bee782", + "model_id": "d8d491963e674504860ea15c4dc55c7f", "version_major": 2, "version_minor": 0 }, "text/plain": [ - "VBox(children=(HBox(children=(VBox(children=(HBox(children=(Label(value='Select subsystems (Ctrl-Click)'), But…" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "2ffb1a622bac411199662b5548b04746", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "Output()" + "Container(children=[Card(children=[CardTitle(children=['Create Hilbert Space'], layout=None), Container(childr…" ] }, "metadata": {}, @@ -635,7 +610,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ @@ -663,7 +637,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ @@ -674,7 +647,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 11, "metadata": { "ExecuteTime": { "end_time": "2020-03-31T11:44:10.103117Z", @@ -687,7 +660,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ @@ -696,7 +668,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 12, "metadata": { "ExecuteTime": { "end_time": "2020-03-31T11:44:13.722890Z", @@ -719,7 +691,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ @@ -728,7 +699,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 13, "metadata": { "ExecuteTime": { "end_time": "2020-03-31T11:44:16.331869Z", @@ -742,7 +713,7 @@ "(1, 2)" ] }, - "execution_count": 15, + "execution_count": 13, "metadata": {}, "output_type": "execute_result" } @@ -752,7 +723,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ @@ -761,7 +731,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 14, "metadata": { "ExecuteTime": { "end_time": "2020-03-31T11:44:19.844481Z", @@ -775,7 +745,7 @@ "8" ] }, - "execution_count": 16, + "execution_count": 14, "metadata": {}, "output_type": "execute_result" } @@ -785,7 +755,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ @@ -794,7 +763,7 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 15, "metadata": { "ExecuteTime": { "end_time": "2020-03-31T11:44:52.454767Z", @@ -805,10 +774,10 @@ { "data": { "text/plain": [ - "18.413688985491895" + "18.41368898549191" ] }, - "execution_count": 17, + "execution_count": 15, "metadata": {}, "output_type": "execute_result" } @@ -818,7 +787,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ @@ -845,7 +813,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.3" + "version": "3.9.16" }, "toc": { "base_numbering": 1, diff --git a/examples/demo_legacy_explorer.ipynb b/examples/demo_legacy_explorer.ipynb deleted file mode 100644 index edbbc6d..0000000 --- a/examples/demo_legacy_explorer.ipynb +++ /dev/null @@ -1,748 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# [DEPRECATED] scqubits example: the Explorer class\n", - "J. Koch and P. Groszkowski\n", - "\n", - "For further documentation of scqubits see https://scqubits.readthedocs.io/en/latest/.\n", - "\n", - "---" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": { - "ExecuteTime": { - "end_time": "2020-02-13T14:26:06.207526Z", - "start_time": "2020-02-13T14:26:03.363950Z" - } - }, - "outputs": [], - "source": [ - "%matplotlib inline\n", - "%config InlineBackend.figure_format = 'svg'\n", - "\n", - "import numpy as np\n", - "\n", - "import scqubits as scq\n", - "from scqubits import HilbertSpace, InteractionTerm, ParameterSweep, Explorer" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# The Explorer Class\n", - "\n", - "Sometimes, exploring the properties of coupled quantum systems benefits from visual aides, and the possibility to see how properties change when system parameters are changed. The `Explorer` class in scqubits provides an interactive plot with multiple panels collecting an important set of information. \n", - "\n", - "The idea behind the `Explorer` class is simple: the user selects an external parameter that they wish to sweep, e.g., an external magnetic flux. The composite system is user-defined through the `HilbertSpace` and `InteractionTerm` classes, allowing flexibility to include different types and numbers of superconducting qubits and harmonic modes.\n", - "\n", - "Once defined, the parameter sweep is computed by means of the `ParameterSweep` class, and spectral data is stored in memory to allow efficient, interactive display of data. The `Explorer` plots are currently fixed to:\n", - "\n", - "1. Bare spectra of the individual qubits\n", - "2. Wave functions of the bare qubits\n", - "3. Dressed spectrum of the composite Hilbert space\n", - "4. Spectrum for n-photon qubit transitions, starting from a given initial state\n", - "5. AC Stark shift $\\chi_{01}$ for any of the qubits\n", - "6. Charge matrix elements for any of the qubits, using the same initial state as in point 4.\n", - "\n", - "## Example 1: fluxonium coupled to resonator\n", - "As a first example, we consider a system composed of a fluxonium qubit, coupled through its charge operator to the voltage inside a resonator.\n", - "\n", - "### HilbertSpace setup\n", - "The initialization of the composite Hilbert space proceeds as usual; we first define the individual two subsystems that will make up the Hilbert space:" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": { - "ExecuteTime": { - "end_time": "2020-02-13T14:26:06.228141Z", - "start_time": "2020-02-13T14:26:06.213556Z" - } - }, - "outputs": [], - "source": [ - "qbt = scq.Fluxonium(\n", - " EJ=2.55,\n", - " EC=0.72,\n", - " EL=0.12,\n", - " flux=0.0,\n", - " cutoff=110,\n", - " truncated_dim=9\n", - ")\n", - "\n", - "osc = scq.Oscillator(\n", - " E_osc=4.0,\n", - " truncated_dim=5\n", - ")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Here, the `truncated_dim` parameters are important. For the fluxonium, with `cutoff` set to 110, the internal Hilbert space dimension is 110. Once diagonalized, we will only keep a few eigenstates going forward - in the above example 9. Similarly, we keep 5 levels for the resonators, i.e., photon states n=0,1,...,4 are included in the following.\n", - "\n", - "Next, the two subsystems are declared as the two components of a joint Hilbert space:" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": { - "ExecuteTime": { - "end_time": "2020-02-13T14:26:06.252987Z", - "start_time": "2020-02-13T14:26:06.235033Z" - } - }, - "outputs": [], - "source": [ - "hilbertspace = scq.HilbertSpace([qbt, osc])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The interaction between fluxonium and resonator is of the form $H_\\text{int} = g n (a+a^\\dagger)$, where $n$ is the fluxonium's charge operator: `qbt.n_operator()`. This structure is captured by creating an `InteractionTerm` object. Since this is the only interaction term, the `interaction_list` contains only this one term. It is inserted into the `HilbertSpace` object." - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": { - "ExecuteTime": { - "end_time": "2020-02-13T14:26:08.346043Z", - "start_time": "2020-02-13T14:26:08.338054Z" - } - }, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "FutureWarning: This use of `InteractionTerm` is deprecated and will cease to be supported in the future.\n", - " c:\\users\\drjen\\onedrive\\coding\\pycharmprojects\\scqubits\\scqubits\\core\\hilbert_space.py: 186FutureWarning: This use of `InteractionTerm` is deprecated and will cease to be supported in the future.\n", - " c:\\users\\drjen\\onedrive\\coding\\pycharmprojects\\scqubits\\scqubits\\core\\hilbert_space.py: 116" - ] - } - ], - "source": [ - "interaction = InteractionTerm(\n", - " g_strength=0.2,\n", - " op1=qbt.n_operator(),\n", - " subsys1=qbt,\n", - " op2=osc.creation_operator() + osc.annihilation_operator(),\n", - " subsys2=osc\n", - ")\n", - "\n", - "interaction_list = [interaction]\n", - "hilbertspace.interaction_list = interaction_list" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Parameter sweep setup\n", - "We consider sweeping the external flux through the fluxonium loop. To create the necessary `ParameterSweep` object, we specify:\n", - "1. `param_name`: the name of the sweep parameter (below expressed in LaTeX format as the flux in units of the flux quantum)\n", - "2. `param_vals`: an array with the flux values used in the sweep\n", - "3. `subsys_update_list`: a list containing all Hilbert space subsystems that change as the flux is varied\n", - "4. `update_hilbertspace(param_val)`: a function that shows how a change in the sweep parameter affects the Hilbert space; here only the `.flux` attributed of the fluxonium qubit needs to be changed\n", - "\n", - "These ingredients all make it into the initialization of the `ParameterSweep` object. Once initialized, spectral data is generated and stored. Here, we additionally generate data for dispersive shifts and charge matrix elements." - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": { - "ExecuteTime": { - "end_time": "2020-02-13T14:26:13.431122Z", - "start_time": "2020-02-13T14:26:09.721855Z" - } - }, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "FutureWarning: The implementation of the `ParameterSweep` class has changed and this old-style interface will cease to be supported in the future.\n", - " c:\\users\\drjen\\onedrive\\coding\\pycharmprojects\\scqubits\\scqubits\\core\\param_sweep.py: 710" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "Parallel compute bare eigensys [num_cpus=4]" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "Parallel compute dressed eigensys [num_cpus=4]" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "ename": "TypeError", - "evalue": "cannot pickle 'WeakMethod' object", - "output_type": "error", - "traceback": [ - "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[1;31mTypeError\u001b[0m Traceback (most recent call last)", - "\u001b[1;32m\u001b[0m in \u001b[0;36m\u001b[1;34m\u001b[0m\n\u001b[0;32m 9\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 10\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 11\u001b[1;33m sweep = ParameterSweep(\n\u001b[0m\u001b[0;32m 12\u001b[0m \u001b[0mparam_name\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mparam_name\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 13\u001b[0m \u001b[0mparam_vals\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mparam_vals\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", - "\u001b[1;32mc:\\users\\drjen\\onedrive\\coding\\pycharmprojects\\scqubits\\scqubits\\core\\param_sweep.py\u001b[0m in \u001b[0;36m__new__\u001b[1;34m(cls, *args, **kwargs)\u001b[0m\n\u001b[0;32m 715\u001b[0m \u001b[1;32mfrom\u001b[0m \u001b[0mscqubits\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mlegacy\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_param_sweep\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0m_ParameterSweep\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 716\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 717\u001b[1;33m \u001b[1;32mreturn\u001b[0m \u001b[0m_ParameterSweep\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m*\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 718\u001b[0m \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 719\u001b[0m \u001b[1;32mreturn\u001b[0m \u001b[0msuper\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m__new__\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mcls\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m*\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", - "\u001b[1;32mc:\\users\\drjen\\onedrive\\coding\\pycharmprojects\\scqubits\\scqubits\\legacy\\_param_sweep.py\u001b[0m in \u001b[0;36m__init__\u001b[1;34m(self, param_name, param_vals, evals_count, hilbertspace, subsys_update_list, update_hilbertspace, num_cpus)\u001b[0m\n\u001b[0;32m 194\u001b[0m \u001b[1;31m# generate the spectral data sweep\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 195\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0msettings\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mAUTORUN_SWEEP\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 196\u001b[1;33m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mrun\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 197\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 198\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0mrun\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m->\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", - "\u001b[1;32mc:\\users\\drjen\\onedrive\\coding\\pycharmprojects\\scqubits\\scqubits\\legacy\\_param_sweep.py\u001b[0m in \u001b[0;36mrun\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m 201\u001b[0m \u001b[0msettings\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mDISPATCH_ENABLED\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mFalse\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 202\u001b[0m \u001b[0mbare_specdata_list\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_compute_bare_specdata_sweep\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 203\u001b[1;33m \u001b[0mdressed_specdata\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_compute_dressed_specdata_sweep\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mbare_specdata_list\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 204\u001b[0m self._lookup = spec_lookup.SpectrumLookup(\n\u001b[0;32m 205\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdressed_specdata\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mbare_specdata_list\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", - 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"\u001b[1;32m~\\miniconda3\\lib\\pickle.py\u001b[0m in \u001b[0;36msave\u001b[1;34m(self, obj, save_persistent_id)\u001b[0m\n\u001b[0;32m 558\u001b[0m \u001b[0mf\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdispatch\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mt\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 559\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0mf\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 560\u001b[1;33m \u001b[0mf\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mobj\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;31m# Call unbound method with explicit self\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 561\u001b[0m \u001b[1;32mreturn\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 562\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n", - 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"\u001b[1;32m~\\miniconda3\\lib\\pickle.py\u001b[0m in \u001b[0;36msave_reduce\u001b[1;34m(self, func, args, state, listitems, dictitems, state_setter, obj)\u001b[0m\n\u001b[0;32m 715\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0mstate\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 716\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0mstate_setter\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 717\u001b[1;33m \u001b[0msave\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mstate\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 718\u001b[0m \u001b[0mwrite\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mBUILD\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 719\u001b[0m \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", - 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"\u001b[1;32m~\\miniconda3\\lib\\site-packages\\dill\\_dill.py\u001b[0m in \u001b[0;36msave_module_dict\u001b[1;34m(pickler, obj)\u001b[0m\n\u001b[0;32m 988\u001b[0m \u001b[1;31m# we only care about session the first pass thru\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 989\u001b[0m \u001b[0mpickler\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_session\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mFalse\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 990\u001b[1;33m \u001b[0mStockPickler\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msave_dict\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mpickler\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mobj\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 991\u001b[0m \u001b[0mlog\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0minfo\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"# D2\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 992\u001b[0m \u001b[1;32mreturn\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", - "\u001b[1;32m~\\miniconda3\\lib\\pickle.py\u001b[0m in \u001b[0;36msave_dict\u001b[1;34m(self, obj)\u001b[0m\n\u001b[0;32m 969\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 970\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mmemoize\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 971\u001b[1;33m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_batch_setitems\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mitems\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 972\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 973\u001b[0m \u001b[0mdispatch\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mdict\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0msave_dict\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", - "\u001b[1;32m~\\miniconda3\\lib\\pickle.py\u001b[0m in \u001b[0;36m_batch_setitems\u001b[1;34m(self, items)\u001b[0m\n\u001b[0;32m 995\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mk\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mv\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mtmp\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 996\u001b[0m \u001b[0msave\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mk\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 997\u001b[1;33m \u001b[0msave\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mv\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 998\u001b[0m \u001b[0mwrite\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mSETITEMS\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 999\u001b[0m \u001b[1;32melif\u001b[0m \u001b[0mn\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", - "\u001b[1;32m~\\miniconda3\\lib\\pickle.py\u001b[0m in \u001b[0;36msave\u001b[1;34m(self, obj, save_persistent_id)\u001b[0m\n\u001b[0;32m 558\u001b[0m \u001b[0mf\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdispatch\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mt\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 559\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0mf\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 560\u001b[1;33m \u001b[0mf\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mobj\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;31m# Call unbound method with explicit self\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 561\u001b[0m \u001b[1;32mreturn\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 562\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n", - "\u001b[1;32m~\\miniconda3\\lib\\site-packages\\dill\\_dill.py\u001b[0m in \u001b[0;36msave_module_dict\u001b[1;34m(pickler, obj)\u001b[0m\n\u001b[0;32m 988\u001b[0m \u001b[1;31m# we only care about session the first pass thru\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 989\u001b[0m \u001b[0mpickler\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_session\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mFalse\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 990\u001b[1;33m \u001b[0mStockPickler\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msave_dict\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mpickler\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mobj\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 991\u001b[0m \u001b[0mlog\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0minfo\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"# D2\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 992\u001b[0m \u001b[1;32mreturn\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", - "\u001b[1;32m~\\miniconda3\\lib\\pickle.py\u001b[0m in \u001b[0;36msave_dict\u001b[1;34m(self, obj)\u001b[0m\n\u001b[0;32m 969\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 970\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mmemoize\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 971\u001b[1;33m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_batch_setitems\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mitems\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 972\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 973\u001b[0m \u001b[0mdispatch\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mdict\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0msave_dict\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", - "\u001b[1;32m~\\miniconda3\\lib\\pickle.py\u001b[0m in \u001b[0;36m_batch_setitems\u001b[1;34m(self, items)\u001b[0m\n\u001b[0;32m 1000\u001b[0m \u001b[0mk\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mv\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mtmp\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 1001\u001b[0m \u001b[0msave\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mk\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1002\u001b[1;33m \u001b[0msave\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mv\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 1003\u001b[0m \u001b[0mwrite\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mSETITEM\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 1004\u001b[0m \u001b[1;31m# else tmp is empty, and we're done\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", - "\u001b[1;32m~\\miniconda3\\lib\\pickle.py\u001b[0m in \u001b[0;36msave\u001b[1;34m(self, obj, save_persistent_id)\u001b[0m\n\u001b[0;32m 576\u001b[0m \u001b[0mreduce\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mgetattr\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m\"__reduce_ex__\"\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 577\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0mreduce\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 578\u001b[1;33m \u001b[0mrv\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mreduce\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mproto\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 579\u001b[0m \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 580\u001b[0m \u001b[0mreduce\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mgetattr\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m\"__reduce__\"\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", - "\u001b[1;31mTypeError\u001b[0m: cannot pickle 'WeakMethod' object" - ] - } - ], - "source": [ - "param_name = r'$\\Phi_{ext}/\\Phi_0$'\n", - "param_vals = np.linspace(-0.5, 0.5, 100)\n", - "\n", - "subsys_update_list = [qbt]\n", - "\n", - "\n", - "def update_hilbertspace(param_val):\n", - " qbt.flux = param_val\n", - "\n", - "\n", - "sweep = ParameterSweep(\n", - " param_name=param_name,\n", - " param_vals=param_vals,\n", - " evals_count=10,\n", - " hilbertspace=hilbertspace,\n", - " subsys_update_list=subsys_update_list,\n", - " update_hilbertspace=update_hilbertspace,\n", - " num_cpus=4\n", - ")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Starting the Explorer class\n", - "At this point, everything is prepared to start the interactive `Explorer` and play with the interactive display!" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": { - "ExecuteTime": { - "end_time": "2020-02-13T14:26:20.251368Z", - "start_time": "2020-02-13T14:26:17.313557Z" - } - }, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "FutureWarning: You are using a deprecated version of `ParameterSweep` that will be removed in the future.\n", - " c:\\users\\drjen\\onedrive\\coding\\pycharmprojects\\scqubits\\scqubits\\explorer\\explorer.py: 70" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "HBox(children=(HTML(value='data sweep'), FloatProgress(value=0.0), HTML(value='')))" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "HBox(children=(HTML(value='data sweep'), FloatProgress(value=0.0), HTML(value='')))" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "1eac592eb84044e8ac9ca56edab72474", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "HBox(children=(VBox(children=(FloatSlider(value=0.0, continuous_update=False, description='$\\\\Phi_{ext}/\\\\Phi_…" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "ecafbc8f14bc4035a7276a807e21c249", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "Output()" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "explorer = Explorer(\n", - " sweep=sweep,\n", - " evals_count=10\n", - ")\n", - "explorer.interact()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Example 2: two transmons coupled to a resonator\n", - "In the following second example, we consider a system composed of two flux-tunable transmons, capacitively coupled to one joint harmonic mode. (The flux is assumed to arise from a global field, and the SQUID-loop areas of the two transmons are different with an area ratio of 1.4) \n", - "\n", - "### Hilbert space setup" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "FutureWarning: This use of `InteractionTerm` is deprecated and will cease to be supported in the future.\n", - " c:\\users\\drjen\\onedrive\\coding\\pycharmprojects\\scqubits\\scqubits\\core\\hilbert_space.py: 180FutureWarning: This use of `InteractionTerm` is deprecated and will cease to be supported in the future.\n", - " c:\\users\\drjen\\onedrive\\coding\\pycharmprojects\\scqubits\\scqubits\\core\\hilbert_space.py: 110" - ] - } - ], - "source": [ - "qbt1 = scq.Transmon(\n", - " EJ=25.0,\n", - " EC=0.2,\n", - " ng=0,\n", - " ncut=30,\n", - " truncated_dim=3)\n", - "\n", - "qbt2 = scq.Transmon(\n", - " EJ=15.0,\n", - " EC=0.15,\n", - " ng=0,\n", - " ncut=30,\n", - " truncated_dim=3)\n", - "\n", - "\n", - "resonator = scq.Oscillator(\n", - " E_osc=5.5,\n", - " truncated_dim=4)\n", - "\n", - "hilbertspace = HilbertSpace([qbt1, qbt2, resonator])\n", - "\n", - "\n", - "g1 = 0.1 # coupling resonator-CPB1 (without charge matrix elements)\n", - "g2 = 0.2 # coupling resonator-CPB2 (without charge matrix elements)\n", - "\n", - "interaction1 = InteractionTerm(\n", - " g_strength = g1,\n", - " op1 = qbt1.n_operator(),\n", - " subsys1 = qbt1,\n", - " op2 = resonator.creation_operator() + resonator.annihilation_operator(),\n", - " subsys2 =resonator\n", - ")\n", - "\n", - "interaction2 = InteractionTerm(\n", - " g_strength = g2,\n", - " op1 = qbt2.n_operator(),\n", - " subsys1 = qbt2,\n", - " op2 = resonator.creation_operator() + resonator.annihilation_operator(),\n", - " subsys2 =resonator\n", - ")\n", - "\n", - "\n", - "\n", - "interaction_list = [interaction1, interaction2]\n", - "hilbertspace.interaction_list = interaction_list" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Parameter sweep setup" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "FutureWarning: The implementation of the `ParameterSweep` class has changed and this old-style interface will cease to be supported in the future.\n", - " c:\\users\\drjen\\onedrive\\coding\\pycharmprojects\\scqubits\\scqubits\\core\\param_sweep.py: 678" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "HBox(children=(HTML(value='Bare spectra'), FloatProgress(value=0.0, max=150.0), HTML(value='')))" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "HBox(children=(HTML(value='Dressed spectrum'), FloatProgress(value=0.0, max=150.0), HTML(value='')))" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "param_name = r'$\\Phi_{ext}/\\Phi_0$'\n", - "param_vals = np.linspace(0.0, 1.0, 150)\n", - "\n", - "subsys_update_list = [qbt1, qbt2]\n", - "\n", - "\n", - "def update_hilbertspace(param_val): # function that shows how Hilbert space components are updated\n", - " qbt1.EJ = 30*np.abs(np.cos(np.pi * param_val))\n", - " qbt2.EJ = 40*np.abs(np.cos(np.pi * param_val * 2))\n", - " \n", - "\n", - "sweep = ParameterSweep(\n", - " param_name=param_name,\n", - " param_vals=param_vals,\n", - " evals_count=15,\n", - " hilbertspace=hilbertspace,\n", - " subsys_update_list=subsys_update_list,\n", - " update_hilbertspace=update_hilbertspace,\n", - ")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Start Explorer" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "FutureWarning: You are using a deprecated version of `ParameterSweep` that will be removed in the future.\n", - " c:\\users\\drjen\\onedrive\\coding\\pycharmprojects\\scqubits\\scqubits\\explorer\\explorer.py: 70" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "HBox(children=(HTML(value='data sweep'), FloatProgress(value=0.0, max=150.0), HTML(value='')))" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "HBox(children=(HTML(value='data sweep'), FloatProgress(value=0.0, max=150.0), HTML(value='')))" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "HBox(children=(HTML(value='data sweep'), FloatProgress(value=0.0, max=150.0), HTML(value='')))" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "HBox(children=(HTML(value='data sweep'), FloatProgress(value=0.0, max=150.0), HTML(value='')))" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "52bb502a3bc245dfb63e24edfd408463", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "HBox(children=(VBox(children=(FloatSlider(value=0.0, continuous_update=False, description='$\\\\Phi_{ext}/\\\\Phi_…" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "171a4654c4bb42f9a6955f1993a60795", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "Output()" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "explorer = Explorer(\n", - " sweep=sweep,\n", - " evals_count=10\n", - ")\n", - "explorer.interact()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.8.10" - }, - "pycharm": { - "stem_cell": { - "cell_type": "raw", - "metadata": { - "collapsed": false - }, - "source": [] - } - }, - "toc": { - "base_numbering": 1, - "nav_menu": {}, - "number_sections": false, - "sideBar": true, - "skip_h1_title": true, - "title_cell": "Table of Contents", - "title_sidebar": "Contents", - "toc_cell": false, - "toc_position": {}, - "toc_section_display": true, - "toc_window_display": true - } - }, - "nbformat": 4, - "nbformat_minor": 4 -} diff --git a/examples/demo_parametersweep.ipynb b/examples/demo_parametersweep.ipynb index 4d09b59..dcf51d1 100644 --- a/examples/demo_parametersweep.ipynb +++ b/examples/demo_parametersweep.ipynb @@ -50,7 +50,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 4, "metadata": { "ExecuteTime": { "end_time": "2016-08-23T15:16:24.535943", @@ -107,7 +107,7 @@ "\n", "hilbertspace.add_interaction(\n", " g_strength = g2,\n", - " op1 = (tmon2.n_operator(), tmon2),\n", + " op1 = tmon2.n_operator,\n", " op2 = resonator.creation_operator,\n", " add_hc = True,\n", " id_str=\"tmon2-resonator\" # optional keyword argument\n", @@ -140,7 +140,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 10, "metadata": { "scrolled": true }, @@ -167,7 +167,7 @@ "version_minor": 0 }, "text/plain": [ - "Parallel compute bare eigensys for subsystem TunableTransmon_12 [num_cpus=4]" + "Parallel compute bare eigensys for subsystem tmon2 [num_cpus=4]" ] }, "metadata": {}, @@ -181,7 +181,7 @@ "version_minor": 0 }, "text/plain": [ - "Parallel compute bare eigensys for subsystem Oscillator_6 [num_cpus=4]" + "Parallel compute bare eigensys for subsystem Oscillator_3 [num_cpus=4]" ] }, "metadata": {}, @@ -190,7 +190,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "7981871f2000413694c0f59b5b81c9b6", + "model_id": "", "version_major": 2, "version_minor": 0 }, @@ -205,7 +205,7 @@ "source": [ "# Set up parameter name and values\n", "pname1 = 'flux' \n", - "flux_vals = np.linspace(0.0, 2.0, 17)\n", + "flux_vals = np.linspace(0.0, 2.0, 39)\n", "pname2 = 'ng'\n", "ng_vals = np.linspace(-0.5, 0.5, 49)\n", "\n", @@ -232,11 +232,52 @@ " update_hilbertspace=update_hilbertspace,\n", " evals_count=20,\n", " subsys_update_info=subsys_update_info,\n", - " num_cpus=4,\n", - " deepcopy=True\n", + " num_cpus=4\n", ")" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### `update_hilbertspace`: use of global variables vs. accessing objects via `ParameterSweep` \n", + "\n", + "In the above code, `update_hilbertspace` directly manipulates the two transmon instances via global variables. It is generally considered better progamming style to avoid such use of global variables. \n", + "\n", + "To facilitate this, `update_hilbertspace` may be defined with an additional first argument that takes in the `ParameterSweep` object itself. This way, all `HilbertSpace` constituents can be accessed via \n", + "\n", + "```.hilbertspace[]```:" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [], + "source": [ + "def update_hilbertspace(param_sweep, flux, ng): # function that defines how Hilbert space components are updated\n", + " param_sweep.hilbertspace[\"tmon1\"].flux = flux\n", + " param_sweep.hilbertspace[\"tmon2\"].flux = area_ratio * flux\n", + " param_sweep.hilbertspace[\"tmon2\"].ng = ng" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### ParameterSweep data: using NamedSlotsNdarray\n", + "\n", + "Much of the computed data that is stored and immediately retrievable after this sweep by accessing the `ParameterSweep` object like a dictionary with the following string keys:\n", + "\n", + "* `\"evals\"`, `\"evecs\"` \n", + "* `\"bare_evals\"`, `\"bare_evecs\"`\n", + "* `\"lamb\"`, `\"chi\"`, `\"kerr\"`\n", + "\n", + "\n", + "\n", + "Data are returned as a `NamedSlotsNdarray` which behaves like a regular numpy array:" + ] + }, { "cell_type": "code", "execution_count": 12, @@ -244,70 +285,109 @@ "outputs": [ { "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "Parallel compute bare eigensys for subsystem tmon1 [num_cpus=4]" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "Parallel compute bare eigensys for subsystem TunableTransmon_12 [num_cpus=4]" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "Parallel compute bare eigensys for subsystem Oscillator_6 [num_cpus=4]" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "ac3df467c3494930b81d6bf5dd8799d1", - "version_major": 2, - "version_minor": 0 - }, "text/plain": [ - "Parallel compute dressed eigensys [num_cpus=4]" + "NamedSlotsNdarray([[[-48.9786042 , -45.0278778 , -44.36746497, ...,\n", + " -30.97638042, -29.62856751, -29.01322673],\n", + " [-48.97847617, -45.02774984, -44.36733698, ...,\n", + " -30.97652916, -29.62844062, -29.0131366 ],\n", + " [-48.978356 , -45.02762973, -44.36721684, ...,\n", + " -30.97666868, -29.62832151, -29.01305202],\n", + " ...,\n", + " [-48.9808442 , -45.03011672, -44.36970433, ...,\n", + " -30.97376163, -29.63078775, -29.01480591],\n", + " [-48.98107747, -45.03034988, -44.36993753, ...,\n", + " -30.97348714, -29.63101896, -29.0149706 ],\n", + " [-48.98131859, -45.03059088, -44.37017858, ...,\n", + " -30.97320307, -29.63125795, -29.01514089]],\n", + "\n", + " [[-48.20325811, -44.28425515, -43.60056726, ...,\n", + " -30.25603071, -28.99383643, -28.35465722],\n", + " [-48.20313009, -44.28412719, -43.60043927, ...,\n", + " -30.25618669, -28.99370954, -28.35456307],\n", + " [-48.20300992, -44.28400708, -43.60031913, ...,\n", + " -30.25633302, -28.99359043, -28.3544747 ],\n", + " ...,\n", + " [-48.20549812, -44.28649407, -43.60280663, ...,\n", + " -30.25328561, -28.99605667, -28.3563063 ],\n", + " [-48.20573139, -44.28672722, -43.60303983, ...,\n", + " -30.25299803, -28.99628788, -28.35647821],\n", + " [-48.20597251, -44.28696822, -43.60328087, ...,\n", + " -30.25270042, -28.99652687, -28.35665594]],\n", + "\n", + " [[-45.90554365, -42.08639336, -41.32406178, ...,\n", + " -28.12093102, -27.12375734, -26.4156855 ],\n", + " [-45.90541563, -42.0862654 , -41.32393379, ...,\n", + " -28.12110785, -27.12363045, -26.41558219],\n", + " [-45.90529546, -42.08614529, -41.32381365, ...,\n", + " -28.12127374, -27.12351134, -26.41548523],\n", + " ...,\n", + " [-45.90778366, -42.08863227, -41.32630116, ...,\n", + " -28.11782282, -27.12597757, -26.41749346],\n", + " [-45.90801693, -42.08886543, -41.32653435, ...,\n", + " -28.11749759, -27.12620878, -26.41768178],\n", + " [-45.90825805, -42.08910643, -41.3267754 , ...,\n", + " -28.11716111, -27.12644777, -26.41787646]],\n", + "\n", + " ...,\n", + "\n", + " [[-42.3758711 , -39.11264733, -37.84719404, ...,\n", + " -25.34826562, -24.15265074, -23.96998296],\n", + " [-42.37574308, -39.11251937, -37.84706605, ...,\n", + " -25.34852241, -24.15252385, -23.96986411],\n", + " [-42.37562291, -39.11239926, -37.84694591, ...,\n", + " -25.34876343, -24.15240474, -23.96975266],\n", + " ...,\n", + " [-42.3781111 , -39.11488618, -37.84943346, ...,\n", + " -25.3437662 , -24.15487095, -23.97206248],\n", + " [-42.37834437, -39.11511933, -37.84966666, ...,\n", + " -25.34329699, -24.15510216, -23.97227883],\n", + " [-42.37858549, -39.11536033, -37.84990772, ...,\n", + " -25.34281187, -24.15534116, -23.97250258]],\n", + "\n", + " [[-41.86257504, -38.99628578, -37.34858161, ...,\n", + " -25.0892816 , -24.07580354, -23.71022581],\n", + " [-41.86244702, -38.99615781, -37.34845361, ...,\n", + " -25.08916161, -24.07568285, -23.71009891],\n", + " [-41.86232685, -38.99603767, -37.34833347, ...,\n", + " -25.08904894, -24.07557068, -23.70997976],\n", + " ...,\n", + " [-41.86481504, -38.99852453, -37.35082107, ...,\n", + " -25.09137431, -24.0779208 , -23.71244592],\n", + " [-41.8650483 , -38.99875771, -37.35105427, ...,\n", + " -25.0915915 , -24.07813997, -23.71267715],\n", + " [-41.86528942, -38.99899871, -37.35129533, ...,\n", + " -25.09181586, -24.07836764, -23.71291615]],\n", + "\n", + " [[-40.26341946, -37.89241505, -35.75966452, ...,\n", + " -23.4563923 , -23.40746803, -22.49823508],\n", + " [-40.26329144, -37.89228692, -35.75953653, ...,\n", + " -23.45627132, -23.40735025, -22.49810801],\n", + " [-40.26317129, -37.89216604, -35.75941639, ...,\n", + " -23.45615773, -23.40725573, -22.49798813],\n", + " ...,\n", + " [-40.26565945, -37.89465293, -35.76190412, ...,\n", + " -23.45850306, -23.4096158 , -22.50045431],\n", + " [-40.2658927 , -37.89488675, -35.76213733, ...,\n", + " -23.45872211, -23.40982114, -22.50068619],\n", + " [-40.26613382, -37.89512782, -35.76237839, ...,\n", + " -23.45894839, -23.41004977, -22.50092525]]])" ] }, + "execution_count": 12, "metadata": {}, - "output_type": "display_data" + "output_type": "execute_result" } ], "source": [ - "sweep2 = ParameterSweep(\n", - " hilbertspace=hilbertspace,\n", - " paramvals_by_name=paramvals_by_name,\n", - " update_hilbertspace=update_hilbertspace,\n", - " evals_count=20,\n", - " subsys_update_info=subsys_update_info,\n", - " num_cpus=4\n", - ")" + "sweep[\"evals\"]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Parameter information\n", + "For convenience, `NamedSlotsNdarray` stores information about the parameters along with the array. Our array has the shape" ] }, { @@ -318,25 +398,7 @@ { "data": { "text/plain": [ - "HilbertSpace(**{'subsystem_list': [TunableTransmon(**{'EJmax': 40.0, 'EC': 0.2, 'd': 0.1, 'flux': 0.0, 'ng': 0.3, 'ncut': 40, 'truncated_dim': 3, 'id_str': 'tmon1'}), TunableTransmon(**{'EJmax': 15.0, 'EC': 0.15, 'd': 0.2, 'flux': 0.0, 'ng': -0.5, 'ncut': 30, 'truncated_dim': 3, 'id_str': 'TunableTransmon_12'}), Oscillator(**{'E_osc': 4.5, 'l_osc': None, 'truncated_dim': 4, 'id_str': 'Oscillator_6'})], 'interaction_list': [InteractionTerm(**{'g_strength': 0.1, 'operator_list': [(0, array([[-40, 0, 0, ..., 0, 0, 0],\n", - " [ 0, -39, 0, ..., 0, 0, 0],\n", - " [ 0, 0, -38, ..., 0, 0, 0],\n", - " ...,\n", - " [ 0, 0, 0, ..., 38, 0, 0],\n", - " [ 0, 0, 0, ..., 0, 39, 0],\n", - " [ 0, 0, 0, ..., 0, 0, 40]])), (2, array([[0. , 0. , 0. , 0. ],\n", - " [1. , 0. , 0. , 0. ],\n", - " [0. , 1.41421356, 0. , 0. ],\n", - " [0. , 0. , 1.73205081, 0. ]]))], 'add_hc': True}), InteractionTerm(**{'g_strength': 0.2, 'operator_list': [(1, array([[-30, 0, 0, ..., 0, 0, 0],\n", - " [ 0, -29, 0, ..., 0, 0, 0],\n", - " [ 0, 0, -28, ..., 0, 0, 0],\n", - " ...,\n", - " [ 0, 0, 0, ..., 28, 0, 0],\n", - " [ 0, 0, 0, ..., 0, 29, 0],\n", - " [ 0, 0, 0, ..., 0, 0, 30]])), (2, array([[0. , 0. , 0. , 0. ],\n", - " [1. , 0. , 0. , 0. ],\n", - " [0. , 1.41421356, 0. , 0. ],\n", - " [0. , 0. , 1.73205081, 0. ]]))], 'add_hc': True})]})" + "(39, 49, 20)" ] }, "execution_count": 13, @@ -345,7 +407,14 @@ } ], "source": [ - "sweep2.hilbertspace" + "sweep[\"evals\"].shape" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The associated parameters are obtained through the `NamedSlotsNdarray` attribute `param_info`:" ] }, { @@ -356,25 +425,26 @@ { "data": { "text/plain": [ - "HilbertSpace(**{'subsystem_list': [TunableTransmon(**{'EJmax': 40.0, 'EC': 0.2, 'd': 0.1, 'flux': 0.23, 'ng': 0.3, 'ncut': 40, 'truncated_dim': 3, 'id_str': 'tmon1'}), TunableTransmon(**{'EJmax': 15.0, 'EC': 0.15, 'd': 0.2, 'flux': 0.0, 'ng': 0.0, 'ncut': 30, 'truncated_dim': 3, 'id_str': 'TunableTransmon_12'}), Oscillator(**{'E_osc': 4.5, 'l_osc': None, 'truncated_dim': 4, 'id_str': 'Oscillator_6'})], 'interaction_list': [InteractionTerm(**{'g_strength': 0.1, 'operator_list': [(0, array([[-40, 0, 0, ..., 0, 0, 0],\n", - " [ 0, -39, 0, ..., 0, 0, 0],\n", - " [ 0, 0, -38, ..., 0, 0, 0],\n", - " ...,\n", - " [ 0, 0, 0, ..., 38, 0, 0],\n", - " [ 0, 0, 0, ..., 0, 39, 0],\n", - " [ 0, 0, 0, ..., 0, 0, 40]])), (2, array([[0. , 0. , 0. , 0. ],\n", - " [1. , 0. , 0. , 0. ],\n", - " [0. , 1.41421356, 0. , 0. ],\n", - " [0. , 0. , 1.73205081, 0. ]]))], 'add_hc': True}), InteractionTerm(**{'g_strength': 0.2, 'operator_list': [(1, array([[-30, 0, 0, ..., 0, 0, 0],\n", - " [ 0, -29, 0, ..., 0, 0, 0],\n", - " [ 0, 0, -28, ..., 0, 0, 0],\n", - " ...,\n", - " [ 0, 0, 0, ..., 28, 0, 0],\n", - " [ 0, 0, 0, ..., 0, 29, 0],\n", - " [ 0, 0, 0, ..., 0, 0, 30]])), (2, array([[0. , 0. , 0. , 0. ],\n", - " [1. , 0. , 0. , 0. ],\n", - " [0. , 1.41421356, 0. , 0. ],\n", - " [0. , 0. , 1.73205081, 0. ]]))], 'add_hc': True})]})" + "OrderedDict([('flux',\n", + " array([0. , 0.05263158, 0.10526316, 0.15789474, 0.21052632,\n", + " 0.26315789, 0.31578947, 0.36842105, 0.42105263, 0.47368421,\n", + " 0.52631579, 0.57894737, 0.63157895, 0.68421053, 0.73684211,\n", + " 0.78947368, 0.84210526, 0.89473684, 0.94736842, 1. ,\n", + " 1.05263158, 1.10526316, 1.15789474, 1.21052632, 1.26315789,\n", + " 1.31578947, 1.36842105, 1.42105263, 1.47368421, 1.52631579,\n", + " 1.57894737, 1.63157895, 1.68421053, 1.73684211, 1.78947368,\n", + " 1.84210526, 1.89473684, 1.94736842, 2. ])),\n", + " ('ng',\n", + " array([-0.5 , -0.47916667, -0.45833333, -0.4375 , -0.41666667,\n", + " -0.39583333, -0.375 , -0.35416667, -0.33333333, -0.3125 ,\n", + " -0.29166667, -0.27083333, -0.25 , -0.22916667, -0.20833333,\n", + " -0.1875 , -0.16666667, -0.14583333, -0.125 , -0.10416667,\n", + " -0.08333333, -0.0625 , -0.04166667, -0.02083333, 0. ,\n", + " 0.02083333, 0.04166667, 0.0625 , 0.08333333, 0.10416667,\n", + " 0.125 , 0.14583333, 0.16666667, 0.1875 , 0.20833333,\n", + " 0.22916667, 0.25 , 0.27083333, 0.29166667, 0.3125 ,\n", + " 0.33333333, 0.35416667, 0.375 , 0.39583333, 0.41666667,\n", + " 0.4375 , 0.45833333, 0.47916667, 0.5 ]))])" ] }, "execution_count": 14, @@ -383,3867 +453,1083 @@ } ], "source": [ - "sweep.hilbertspace" + "sweep[\"evals\"].param_info" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "#### `update_hilbertspace`: use of global variables vs. accessing objects via `ParameterSweep` \n", - "\n", - "In the above code, `update_hilbertspace` directly manipulates the two transmon instances via global variables. It is generally considered better progamming style to avoid such use of global variables. \n", - "\n", - "To facilitate this, `update_hilbertspace` may be defined with an additional first argument that takes in the `ParameterSweep` object itself. This way, all `HilbertSpace` constituents can be accessed via \n", + "There are two names axes, one for the flux parameter, one for the offset charge parameter. The last (unnamed) axis is for the number of eigenvalues at each point (the default is 20).\n", "\n", - "```.hilbertspace[]```:" + "The `param_info` entries are kept up-to-date upon slicing an `NamedSlotsNdarray`:" ] }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 15, "metadata": {}, "outputs": [ { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "Parallel compute bare eigensys [num_cpus=4]" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "Parallel compute bare eigensys [num_cpus=4]" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "Parallel compute bare eigensys [num_cpus=4]" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, + "name": "stdout", + "output_type": "stream", + "text": [ + "(49, 20)\n", + "OrderedDict([('ng', array([-0.5 , -0.47916667, -0.45833333, -0.4375 , -0.41666667,\n", + " -0.39583333, -0.375 , -0.35416667, -0.33333333, -0.3125 ,\n", + " -0.29166667, -0.27083333, -0.25 , -0.22916667, -0.20833333,\n", + " -0.1875 , -0.16666667, -0.14583333, -0.125 , -0.10416667,\n", + " -0.08333333, -0.0625 , -0.04166667, -0.02083333, 0. ,\n", + " 0.02083333, 0.04166667, 0.0625 , 0.08333333, 0.10416667,\n", + " 0.125 , 0.14583333, 0.16666667, 0.1875 , 0.20833333,\n", + " 0.22916667, 0.25 , 0.27083333, 0.29166667, 0.3125 ,\n", + " 0.33333333, 0.35416667, 0.375 , 0.39583333, 0.41666667,\n", + " 0.4375 , 0.45833333, 0.47916667, 0.5 ]))])\n" + ] + } + ], + "source": [ + "sliced_data = sweep[\"evals\"][0, :] # fix flux to the first parameter value and keep all ng values\n", + "print(sliced_data.shape)\n", + "print(sliced_data.param_info)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Once all named axes have been collapsed, we return to an ordinary numpy array:" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [ { "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, "text/plain": [ - "Parallel compute dressed eigensys [num_cpus=4]" + "array([-42.16995175, -38.52931607, -37.61369475, -35.00709028,\n", + " -34.86152745, -33.99696531, -33.05853937, -31.22092496,\n", + " -30.60986733, -30.30595679, -29.46683007, -28.4761959 ,\n", + " -27.76026966, -27.69875162, -26.68922661, -26.16386938,\n", + " -25.75118972, -24.65086717, -24.1172506 , -23.30225406])" ] }, + "execution_count": 16, "metadata": {}, - "output_type": "display_data" + "output_type": "execute_result" } ], "source": [ - "def update_hilbertspace(param_sweep, flux, ng): # function that defines how Hilbert space components are updated\n", - " param_sweep.hilbertspace[\"tmon1\"].flux = flux\n", - " param_sweep.hilbertspace[\"tmon2\"].flux = area_ratio * flux\n", - " param_sweep.hilbertspace[\"tmon2\"].ng = ng" + "sweep[\"evals\"][3, 5]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "#### State after the sweep\n", - "\n", - "By default, the `HilbertSpace` object and its constituents will be left by `ParameterSweep` in a state reached with the last evaluation involved in the sweep. (When multiprocessing, this final state may not be easy to predict.)\n", - "\n", - "Alternatively, the `deepcopy` option can be used to\n", - "1. disconnect all global ``HilbertSpace` constituents from the sweep,and\n", - "2. restore the `HilbertSpace` object stored internally with the `ParameterSweep` to the parameters prior to the sweep.\n", + "#### Generalized slicing with NamedSlotsNdarray\n", "\n", - "Without use of `deepcopy`, there is a good chance that, for example, the offset charge of `tmon2` is now different than prior to the sweep:" + "**Name-based slicing**.\n", + "While the order of axes in a `NamedSlotsNdarray` is maintained consistently, referring to an axis by its name can be convenient. In this name-based slicing, order of index entries does not matter:" ] }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 17, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "-0.5" + "(array([-31.02296701, -28.01314337, -26.50746401, -25.14426972,\n", + " -24.61771606, -23.50709722, -21.99190319, -21.6079114 ,\n", + " -20.70072329, -20.10392284, -18.9990933 , -18.73912611,\n", + " -18.42113417, -17.44503573, -17.10353526, -16.24507994,\n", + " -15.58922726, -15.41056565, -14.31428268, -14.2964135 ]),\n", + " array([-31.02296701, -28.01314337, -26.50746401, -25.14426972,\n", + " -24.61771606, -23.50709722, -21.99190319, -21.6079114 ,\n", + " -20.70072329, -20.10392284, -18.9990933 , -18.73912611,\n", + " -18.42113417, -17.44503573, -17.10353526, -16.24507994,\n", + " -15.58922726, -15.41056565, -14.31428268, -14.2964135 ]))" ] }, - "execution_count": 8, + "execution_count": 17, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "tmon2.ng" + "(sweep[\"evals\"][\"flux\":5, \"ng\":7], \n", + " sweep[\"evals\"][\"ng\":7, \"flux\":5])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "When using `deepcopy=True`, the original state is restored. Note that `update_hilbertspace` must be based on manipulating the objects interior to `ParameterSweep` with the `deepcopy` option. (Changing the global variables will have no effect in this case.)" + "Name-based slicing allows for `start` and `stop`. For example, `[\"flux\":3:-2]` chooses the flux parameter values from element 4 to the second-but-last element. (A `step` entry is not supported for name-based slicing.)\n", + "\n", + ".. note::\n", + " Name-based slicing and ordinary slicing by axes position cannot be mixed. If a multi-index contains a \n", + " name-based entry, then all entries must be name-based. " ] }, { - "cell_type": "code", - "execution_count": 3, + "cell_type": "markdown", "metadata": {}, - "outputs": [ - { - "ename": "NameError", - "evalue": "name 'paramvals_by_name' is not defined", - "output_type": "error", - "traceback": [ - "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[1;31mNameError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[1;32mIn[3], line 64\u001b[0m\n\u001b[0;32m 58\u001b[0m param_sweep\u001b[38;5;241m.\u001b[39mhilbertspace[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mtmon2\u001b[39m\u001b[38;5;124m\"\u001b[39m]\u001b[38;5;241m.\u001b[39mflux \u001b[38;5;241m=\u001b[39m area_ratio \u001b[38;5;241m*\u001b[39m flux\n\u001b[0;32m 59\u001b[0m param_sweep\u001b[38;5;241m.\u001b[39mhilbertspace[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mtmon2\u001b[39m\u001b[38;5;124m\"\u001b[39m]\u001b[38;5;241m.\u001b[39mng \u001b[38;5;241m=\u001b[39m ng\n\u001b[0;32m 62\u001b[0m sweep \u001b[38;5;241m=\u001b[39m ParameterSweep(\n\u001b[0;32m 63\u001b[0m hilbertspace\u001b[38;5;241m=\u001b[39mhilbertspace,\n\u001b[1;32m---> 64\u001b[0m paramvals_by_name\u001b[38;5;241m=\u001b[39m\u001b[43mparamvals_by_name\u001b[49m,\n\u001b[0;32m 65\u001b[0m update_hilbertspace\u001b[38;5;241m=\u001b[39mupdate_hilbertspace,\n\u001b[0;32m 66\u001b[0m evals_count\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m20\u001b[39m,\n\u001b[0;32m 67\u001b[0m subsys_update_info\u001b[38;5;241m=\u001b[39msubsys_update_info,\n\u001b[0;32m 68\u001b[0m \u001b[38;5;66;03m# -------- This time: enable deepcopy ----------------\u001b[39;00m\n\u001b[0;32m 69\u001b[0m deepcopy\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m,\n\u001b[0;32m 70\u001b[0m \u001b[38;5;66;03m# ----------------------------------------------------\u001b[39;00m\n\u001b[0;32m 71\u001b[0m )\n", - "\u001b[1;31mNameError\u001b[0m: name 'paramvals_by_name' is not defined" - ] - } - ], "source": [ - "tmon1 = scq.TunableTransmon(\n", - " EJmax=40.0,\n", - " EC=0.2,\n", - " d=0.1,\n", - "# ---------------- USE THIS AS A TEST FOR RESTORING THE PRE-SWEEP STATE\n", - " flux=-1.333, \n", - "# ---------------------------------------------------------------------\n", - " ng=0.3,\n", - " ncut=40,\n", - " truncated_dim=3, # after diagonalization, we will keep 3 levels\n", - " id_str=\"tmon1\" # this is used for referencing the object from within ParamaterSweep or HilberSpace\n", - ")\n", - "\n", - "tmon2 = scq.TunableTransmon(\n", - " EJmax=15.0,\n", - " EC=0.15,\n", - " d=0.2,\n", - " flux=0.0,\n", - " ng=0.0,\n", - " ncut=30,\n", - " truncated_dim=3,\n", - " id_str=\"tmon2\"\n", - ")\n", - "\n", - "resonator = scq.Oscillator(\n", - " E_osc=4.5,\n", - " truncated_dim=4 # up to 3 photons (0,1,2,3)\n", - ")\n", - "\n", - "hilbertspace = scq.HilbertSpace([tmon1, tmon2, resonator])\n", - "\n", - "\n", - "g1 = 0.1 # coupling resonator-CPB1 (without charge matrix elements)\n", - "g2 = 0.2 # coupling resonator-CPB2 (without charge matrix elements)\n", - "\n", - "hilbertspace.add_interaction(\n", - " g_strength = g1,\n", - " op1 = tmon1.n_operator,\n", - " op2 = resonator.creation_operator,\n", - " add_hc = True\n", - ")\n", - "\n", - "hilbertspace.add_interaction(\n", - " g_strength = g2,\n", - " op1 = tmon2.n_operator,\n", - " op2 = resonator.creation_operator,\n", - " add_hc = True\n", - ")\n", - "\n", - "pname1 = 'flux' \n", - "flux_vals = np.linspace(0.0, 2.0, 171)\n", - "pname2 = 'ng'\n", - "ng_vals = np.linspace(-0.5, 0.5, 49)\n", + "**Value-based slicing**.\n", + "Generalized slicing includes the possibility to refer to an array axis by a parameter value rather than through its index. One downside of this: the parameter value needs to be entered in full with all relevant decimals. This option therefore makes most sense when parameter value arrays are built commensurate with simple decimals.\n", "\n", - "# ------- only access interior objects, no globals---------\n", - "def update_hilbertspace(param_sweep, flux, ng): \n", - " param_sweep.hilbertspace[\"tmon1\"].flux = flux\n", - " param_sweep.hilbertspace[\"tmon2\"].flux = area_ratio * flux\n", - " param_sweep.hilbertspace[\"tmon2\"].ng = ng\n", - " \n", - " \n", - "sweep = ParameterSweep(\n", - " hilbertspace=hilbertspace,\n", - " paramvals_by_name=paramvals_by_name,\n", - " update_hilbertspace=update_hilbertspace,\n", - " evals_count=20,\n", - " subsys_update_info=subsys_update_info,\n", - "# -------- This time: enable deepcopy ----------------\n", - " deepcopy=True,\n", - "# ----------------------------------------------------\n", - ")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "For `deepcopy=True` the global instances are disconnected and remain untouched, and the `HilbertSpace` object interior to `sweep` is restored to its original state. Check:" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "False" - ] - }, - "execution_count": 9, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "sweep.hilbertspace is hilbertspace" + "Example: the ng value 0.0 is one value in the ng parameter array. We can access it via" ] }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 18, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "-1.333" + "NamedSlotsNdarray([[-4.89776994e+01, -4.50269734e+01, -4.43665604e+01,\n", + " -4.11776030e+01, -4.11662270e+01, -4.04603313e+01,\n", + " -3.97615157e+01, -3.72269436e+01, -3.68116207e+01,\n", + " -3.65668931e+01, -3.59186443e+01, -3.51455468e+01,\n", + " -3.35837935e+01, -3.33662442e+01, -3.26606899e+01,\n", + " -3.23497791e+01, -3.19621276e+01, -3.09774295e+01,\n", + " -2.96276707e+01, -2.90125902e+01],\n", + " [-4.82023533e+01, -4.42833508e+01, -4.35996627e+01,\n", + " -4.04586083e+01, -4.04564086e+01, -3.97222197e+01,\n", + " -3.90020180e+01, -3.65374672e+01, -3.60989459e+01,\n", + " -3.58541719e+01, -3.51814104e+01, -3.43906140e+01,\n", + " -3.29168457e+01, -3.27127717e+01, -3.19767508e+01,\n", + " -3.16408686e+01, -3.12568160e+01, -3.02571311e+01,\n", + " -2.89929396e+01, -2.83539922e+01],\n", + " 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-2.75017790e+01,\n", + " -2.63494370e+01, -2.43027643e+01, -2.35997335e+01,\n", + " -2.29039139e+01, -2.24033864e+01, -2.17497864e+01,\n", + " -2.08011511e+01, -1.99542788e+01, -1.90656123e+01,\n", + " -1.85474138e+01, -1.82961620e+01, -1.78476723e+01,\n", + " -1.71542187e+01, -1.68474551e+01, -1.61528905e+01,\n", + " -1.54997959e+01, -1.42112727e+01],\n", + " [-3.64617871e+01, -3.25683190e+01, -3.18677736e+01,\n", + " -3.00564916e+01, -2.87720348e+01, -2.80138109e+01,\n", + " -2.72781620e+01, -2.61631876e+01, -2.54640920e+01,\n", + " -2.44113574e+01, -2.38598228e+01, -2.34769575e+01,\n", + " -2.26734735e+01, -2.23670879e+01, -2.16101537e+01,\n", + " -2.08754258e+01, -1.99610163e+01, -1.99587192e+01,\n", + " -1.92327755e+01, -1.85693894e+01],\n", + " [-3.96773119e+01, -3.59084440e+01, -3.51052291e+01,\n", + " -3.27588486e+01, -3.22491226e+01, -3.13668695e+01,\n", + " -3.05353408e+01, -2.89900474e+01, -2.81877190e+01,\n", + " -2.78686761e+01, -2.68328550e+01, -2.60482517e+01,\n", + " -2.59433043e+01, -2.53308147e+01, -2.44493657e+01,\n", + " -2.36183798e+01, -2.34217017e+01, -2.22759437e+01,\n", + " -2.19757656e+01, -2.14463186e+01],\n", + " [-4.16589980e+01, -3.80971677e+01, -3.71105541e+01,\n", + " -3.46579914e+01, -3.43505750e+01, -3.35695434e+01,\n", + " -3.25628545e+01, -3.07887713e+01, -3.02522857e+01,\n", + " -2.98028231e+01, -2.90427902e+01, -2.79873191e+01,\n", + " -2.73496439e+01, -2.72493223e+01, -2.62618093e+01,\n", + " -2.58064583e+01, -2.52555104e+01, -2.42494840e+01,\n", + " -2.36855058e+01, -2.29446405e+01],\n", + " [-4.23749663e+01, -3.91117427e+01, -3.78462894e+01,\n", + " -3.59826196e+01, -3.47921717e+01, -3.45961970e+01,\n", + " -3.33177243e+01, -3.15513566e+01, -3.15289587e+01,\n", + " -3.02640608e+01, -3.00789957e+01, -2.87583136e+01,\n", + " -2.83998645e+01, -2.74160550e+01, -2.70996079e+01,\n", + " -2.70139633e+01, -2.57358086e+01, -2.53500810e+01,\n", + " -2.41517536e+01, -2.39691553e+01],\n", + " [-4.18616703e+01, -3.89953777e+01, -3.73476770e+01,\n", + " -3.62735900e+01, -3.44893855e+01, -3.41157344e+01,\n", + " -3.28335848e+01, -3.18204965e+01, -3.12494462e+01,\n", + " -2.99815210e+01, -2.96022461e+01, -2.85276759e+01,\n", + " -2.82880983e+01, -2.73583273e+01, -2.67439506e+01,\n", + " -2.65761899e+01, -2.53107588e+01, -2.50884326e+01,\n", + " -2.40750739e+01, -2.37093253e+01],\n", + " [-4.02625159e+01, -3.78914427e+01, -3.57587604e+01,\n", + " -3.56776033e+01, -3.33925477e+01, -3.24624305e+01,\n", + " -3.12548603e+01, -3.12079972e+01, -3.00913594e+01,\n", + " -2.88923087e+01, -2.79591618e+01, -2.78775301e+01,\n", + " -2.67351402e+01, -2.67207213e+01, -2.55929465e+01,\n", + " -2.48686460e+01, -2.42709742e+01, -2.34555363e+01,\n", + " -2.34084017e+01, -2.24972702e+01]])" ] }, - "execution_count": 10, + "execution_count": 18, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "sweep.hilbertspace[\"tmon1\"].flux" + "sweep[\"evals\"][:, 0.0]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "### ParameterSweep data: using NamedSlotsNdarray\n", - "\n", - "Much of the computed data that is stored and immediately retrievable after this sweep by accessing the `ParameterSweep` object like a dictionary with the following string keys:\n", - "\n", - "* `\"evals\"`, `\"evecs\"` \n", - "* `\"bare_evals\"`, `\"bare_evecs\"`\n", - "* `\"lamb\"`, `\"chi\"`, `\"kerr\"`\n", - "\n", - "\n", - "\n", - "Data are returned as a `NamedSlotsNdarray` which behaves like a regular numpy array:" + "Value-based indexing will ordinarily fail if values entered do not match concrete values in the original array of values. This behavior can be changed in favor of more forgiving \"fuzzy\" value-based indexing which selects the closest value to the one entered. This is enabled by changing the default for `FUZZY_SLICING`:" ] }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 19, "metadata": {}, "outputs": [ { - "data": { - "text/plain": [ - "NamedSlotsNdarray([[[-48.9786042 , -45.0278778 , -44.36746497, ...,\n", - " -30.97638042, -29.62856751, -29.01322673],\n", - " [-48.9786042 , -45.0278778 , -44.36746497, ...,\n", - " -30.97638042, -29.62856751, -29.01322673],\n", - " [-48.9786042 , -45.0278778 , -44.36746497, ...,\n", - " -30.97638042, -29.62856751, -29.01322673],\n", - " ...,\n", - " [-48.9786042 , -45.0278778 , -44.36746497, ...,\n", - " -30.97638042, -29.62856751, -29.01322673],\n", - " [-48.9786042 , -45.0278778 , -44.36746497, ...,\n", - " -30.97638042, -29.62856751, -29.01322673],\n", - " [-48.9786042 , -45.0278778 , -44.36746497, ...,\n", - " -30.97638042, -29.62856751, -29.01322673]],\n", - "\n", - " [[-48.9786042 , -45.0278778 , -44.36746497, ...,\n", - " -30.97638042, -29.62856751, -29.01322673],\n", - " [-48.9786042 , -45.0278778 , -44.36746497, ...,\n", - " -30.97638042, -29.62856751, -29.01322673],\n", - " [-48.9786042 , -45.0278778 , -44.36746497, ...,\n", - " -30.97638042, -29.62856751, -29.01322673],\n", - " ...,\n", - " [-48.9786042 , -45.0278778 , -44.36746497, ...,\n", - " -30.97638042, -29.62856751, -29.01322673],\n", - " [-48.9786042 , -45.0278778 , -44.36746497, ...,\n", - " -30.97638042, -29.62856751, -29.01322673],\n", - " [-48.9786042 , -45.0278778 , -44.36746497, ...,\n", - " -30.97638042, -29.62856751, -29.01322673]],\n", - "\n", - " [[-48.9786042 , -45.0278778 , -44.36746497, ...,\n", - " -30.97638042, -29.62856751, -29.01322673],\n", - " [-48.9786042 , -45.0278778 , -44.36746497, ...,\n", - " -30.97638042, -29.62856751, -29.01322673],\n", - " [-48.9786042 , -45.0278778 , -44.36746497, ...,\n", - " -30.97638042, -29.62856751, -29.01322673],\n", - " ...,\n", - " [-48.9786042 , -45.0278778 , -44.36746497, ...,\n", - " -30.97638042, -29.62856751, -29.01322673],\n", - " [-48.9786042 , -45.0278778 , -44.36746497, ...,\n", - " -30.97638042, -29.62856751, -29.01322673],\n", - " [-48.9786042 , -45.0278778 , -44.36746497, ...,\n", - " -30.97638042, -29.62856751, -29.01322673]],\n", - "\n", - " ...,\n", - "\n", - " [[-48.9786042 , -45.0278778 , -44.36746497, ...,\n", - " -30.97638042, -29.62856751, -29.01322673],\n", - " [-48.9786042 , -45.0278778 , -44.36746497, ...,\n", - " -30.97638042, -29.62856751, -29.01322673],\n", - " [-48.9786042 , -45.0278778 , -44.36746497, ...,\n", - " -30.97638042, -29.62856751, -29.01322673],\n", - " ...,\n", - " [-48.9786042 , -45.0278778 , -44.36746497, ...,\n", - " -30.97638042, -29.62856751, -29.01322673],\n", - " [-48.9786042 , -45.0278778 , -44.36746497, ...,\n", - " -30.97638042, -29.62856751, -29.01322673],\n", - " [-48.9786042 , -45.0278778 , -44.36746497, ...,\n", - " -30.97638042, -29.62856751, -29.01322673]],\n", - "\n", - " [[-48.9786042 , -45.0278778 , -44.36746497, ...,\n", - " -30.97638042, -29.62856751, -29.01322673],\n", - " [-48.9786042 , -45.0278778 , -44.36746497, ...,\n", - " -30.97638042, -29.62856751, -29.01322673],\n", - " [-48.9786042 , -45.0278778 , -44.36746497, ...,\n", - " -30.97638042, -29.62856751, -29.01322673],\n", - " ...,\n", - " [-48.9786042 , -45.0278778 , -44.36746497, ...,\n", - " -30.97638042, -29.62856751, -29.01322673],\n", - " [-48.9786042 , -45.0278778 , -44.36746497, ...,\n", - " -30.97638042, -29.62856751, -29.01322673],\n", - " [-48.9786042 , -45.0278778 , -44.36746497, ...,\n", - " -30.97638042, -29.62856751, -29.01322673]],\n", - "\n", - " [[-48.9786042 , -45.0278778 , -44.36746497, ...,\n", - " -30.97638042, -29.62856751, -29.01322673],\n", - " [-48.9786042 , -45.0278778 , -44.36746497, ...,\n", - " -30.97638042, -29.62856751, -29.01322673],\n", - " [-48.9786042 , -45.0278778 , -44.36746497, ...,\n", - " -30.97638042, -29.62856751, -29.01322673],\n", - " ...,\n", - " [-48.9786042 , -45.0278778 , -44.36746497, ...,\n", - " -30.97638042, -29.62856751, -29.01322673],\n", - " [-48.9786042 , -45.0278778 , -44.36746497, ...,\n", - " -30.97638042, -29.62856751, -29.01322673],\n", - " [-48.9786042 , -45.0278778 , -44.36746497, ...,\n", - " -30.97638042, -29.62856751, -29.01322673]]])" - ] - }, - "execution_count": 9, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "sweep[\"evals\"]" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### Parameter information\n", - "For convenience, `NamedSlotsNdarray` stores information about the parameters along with the array. Our array has the shape" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ + "name": "stderr", + "output_type": "stream", + "text": [ + "UserWarning: Using fuzzy value based indexing: selected value is 0.0\n", + " : 24" + ] + }, { "data": { "text/plain": [ - "(171, 49, 20)" + "NamedSlotsNdarray([[-4.89776994e+01, -4.50269734e+01, -4.43665604e+01,\n", + " -4.11776030e+01, -4.11662270e+01, -4.04603313e+01,\n", + " -3.97615157e+01, -3.72269436e+01, -3.68116207e+01,\n", + " -3.65668931e+01, -3.59186443e+01, -3.51455468e+01,\n", + " -3.35837935e+01, -3.33662442e+01, -3.26606899e+01,\n", + " -3.23497791e+01, -3.19621276e+01, -3.09774295e+01,\n", + " -2.96276707e+01, -2.90125902e+01],\n", + " [-4.82023533e+01, -4.42833508e+01, -4.35996627e+01,\n", + " -4.04586083e+01, -4.04564086e+01, -3.97222197e+01,\n", + " -3.90020180e+01, -3.65374672e+01, -3.60989459e+01,\n", + " -3.58541719e+01, -3.51814104e+01, -3.43906140e+01,\n", + " -3.29168457e+01, 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-2.70996079e+01,\n", + " -2.70139633e+01, -2.57358086e+01, -2.53500810e+01,\n", + " -2.41517536e+01, -2.39691553e+01],\n", + " [-4.18616703e+01, -3.89953777e+01, -3.73476770e+01,\n", + " -3.62735900e+01, -3.44893855e+01, -3.41157344e+01,\n", + " -3.28335848e+01, -3.18204965e+01, -3.12494462e+01,\n", + " -2.99815210e+01, -2.96022461e+01, -2.85276759e+01,\n", + " -2.82880983e+01, -2.73583273e+01, -2.67439506e+01,\n", + " -2.65761899e+01, -2.53107588e+01, -2.50884326e+01,\n", + " -2.40750739e+01, -2.37093253e+01],\n", + " [-4.02625159e+01, -3.78914427e+01, -3.57587604e+01,\n", + " -3.56776033e+01, -3.33925477e+01, -3.24624305e+01,\n", + " -3.12548603e+01, -3.12079972e+01, -3.00913594e+01,\n", + " -2.88923087e+01, -2.79591618e+01, -2.78775301e+01,\n", + " -2.67351402e+01, -2.67207213e+01, -2.55929465e+01,\n", + " -2.48686460e+01, -2.42709742e+01, -2.34555363e+01,\n", + " -2.34084017e+01, -2.24972702e+01]])" ] }, - "execution_count": 5, + "execution_count": 19, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "sweep[\"evals\"].shape" + "scq.settings.FUZZY_SLICING = True\n", + "sweep[\"evals\"][\"ng\":0.001]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "The associated parameters are obtained through the `NamedSlotsNdarray` attribute `param_info`:" + "Value-based and string-based slicing can be combined. The following thus produces the same result:" ] }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 20, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "OrderedDict([('flux',\n", - " array([0. , 0.01176471, 0.02352941, 0.03529412, 0.04705882,\n", - " 0.05882353, 0.07058824, 0.08235294, 0.09411765, 0.10588235,\n", - " 0.11764706, 0.12941176, 0.14117647, 0.15294118, 0.16470588,\n", - " 0.17647059, 0.18823529, 0.2 , 0.21176471, 0.22352941,\n", - " 0.23529412, 0.24705882, 0.25882353, 0.27058824, 0.28235294,\n", - " 0.29411765, 0.30588235, 0.31764706, 0.32941176, 0.34117647,\n", - " 0.35294118, 0.36470588, 0.37647059, 0.38823529, 0.4 ,\n", - " 0.41176471, 0.42352941, 0.43529412, 0.44705882, 0.45882353,\n", - " 0.47058824, 0.48235294, 0.49411765, 0.50588235, 0.51764706,\n", - " 0.52941176, 0.54117647, 0.55294118, 0.56470588, 0.57647059,\n", - " 0.58823529, 0.6 , 0.61176471, 0.62352941, 0.63529412,\n", - " 0.64705882, 0.65882353, 0.67058824, 0.68235294, 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-2.59433043e+01, -2.53308147e+01, -2.44493657e+01,\n", + " -2.36183798e+01, -2.34217017e+01, -2.22759437e+01,\n", + " -2.19757656e+01, -2.14463186e+01],\n", + " [-4.16589980e+01, -3.80971677e+01, -3.71105541e+01,\n", + " -3.46579914e+01, -3.43505750e+01, -3.35695434e+01,\n", + " -3.25628545e+01, -3.07887713e+01, -3.02522857e+01,\n", + " -2.98028231e+01, -2.90427902e+01, -2.79873191e+01,\n", + " -2.73496439e+01, -2.72493223e+01, -2.62618093e+01,\n", + " -2.58064583e+01, -2.52555104e+01, -2.42494840e+01,\n", + " -2.36855058e+01, -2.29446405e+01],\n", + " [-4.23749663e+01, -3.91117427e+01, -3.78462894e+01,\n", + " -3.59826196e+01, -3.47921717e+01, -3.45961970e+01,\n", + " -3.33177243e+01, -3.15513566e+01, -3.15289587e+01,\n", + " -3.02640608e+01, -3.00789957e+01, -2.87583136e+01,\n", + " -2.83998645e+01, -2.74160550e+01, -2.70996079e+01,\n", + " -2.70139633e+01, -2.57358086e+01, -2.53500810e+01,\n", + " -2.41517536e+01, -2.39691553e+01],\n", + " [-4.18616703e+01, -3.89953777e+01, -3.73476770e+01,\n", + " -3.62735900e+01, -3.44893855e+01, -3.41157344e+01,\n", + " -3.28335848e+01, -3.18204965e+01, -3.12494462e+01,\n", + " -2.99815210e+01, -2.96022461e+01, -2.85276759e+01,\n", + " -2.82880983e+01, -2.73583273e+01, -2.67439506e+01,\n", + " -2.65761899e+01, -2.53107588e+01, -2.50884326e+01,\n", + " -2.40750739e+01, -2.37093253e+01],\n", + " [-4.02625159e+01, -3.78914427e+01, -3.57587604e+01,\n", + " -3.56776033e+01, -3.33925477e+01, -3.24624305e+01,\n", + " -3.12548603e+01, -3.12079972e+01, -3.00913594e+01,\n", + " -2.88923087e+01, -2.79591618e+01, -2.78775301e+01,\n", + " -2.67351402e+01, -2.67207213e+01, -2.55929465e+01,\n", + " -2.48686460e+01, -2.42709742e+01, -2.34555363e+01,\n", + " -2.34084017e+01, -2.24972702e+01]])" ] }, - "execution_count": 6, + "execution_count": 20, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "sweep[\"evals\"].param_info" + "sweep[\"evals\"][\"ng\":0.0]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "There are two names axes, one for the flux parameter, one for the offset charge parameter. The last (unnamed) axis is for the number of eigenvalues at each point (the default is 20).\n", + "**Distinction between value-based and index-based slicing**. All integer entries in slicing are interpreted as index-based slicing, whereas floats are taken as value-based. Thus, `[\"flux\":1.0]` is the flux value 1.0 (if existent), whereas `[\"flux\":1]` is the second (!) entry in the flux values array.\n", "\n", - "The `param_info` entries are kept up-to-date upon slicing an `NamedSlotsNdarray`:" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "(49, 20)\n", - "OrderedDict([('ng', array([-0.5 , -0.47916667, -0.45833333, -0.4375 , -0.41666667,\n", - " -0.39583333, -0.375 , -0.35416667, -0.33333333, -0.3125 ,\n", - " -0.29166667, -0.27083333, -0.25 , -0.22916667, -0.20833333,\n", - " -0.1875 , -0.16666667, -0.14583333, -0.125 , -0.10416667,\n", - " -0.08333333, -0.0625 , -0.04166667, -0.02083333, 0. ,\n", - " 0.02083333, 0.04166667, 0.0625 , 0.08333333, 0.10416667,\n", - " 0.125 , 0.14583333, 0.16666667, 0.1875 , 0.20833333,\n", - " 0.22916667, 0.25 , 0.27083333, 0.29166667, 0.3125 ,\n", - " 0.33333333, 0.35416667, 0.375 , 0.39583333, 0.41666667,\n", - " 0.4375 , 0.45833333, 0.47916667, 0.5 ]))])\n" - ] - } - ], - "source": [ - "sliced_data = sweep[\"evals\"][0, :] # fix flux to the first parameter value and keep all ng values\n", - "print(sliced_data.shape)\n", - "print(sliced_data.param_info)" + "Note: when using integer-valued parameters such as `ncut`, value-based slicing should not be used." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "Once all named axes have been collapsed, we return to an ordinary numpy array:" + "#### Quick plotting of sweep data\n", + "Once a `NamedSlotsNdarray` is reduced to a single parameter axis, data can readily be plotted using the `plot()` method:" ] }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 21, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "array([-48.62879419, -44.69222677, -44.02155029, -40.85303536,\n", - " -40.84759218, -40.12813102, -39.41989067, -36.91653198,\n", - " -36.49063412, -36.24623164, -35.58624946, -34.80531985,\n", - " -33.28360314, -33.07194437, -32.35283653, -32.03010386,\n", - " -31.64485568, -30.65258036, -29.34186695, -28.71590343])" + "(
, )" ] }, - "execution_count": 8, + "execution_count": 21, "metadata": {}, "output_type": "execute_result" - } - ], - "source": [ - "sweep[\"evals\"][3, 5]" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### Generalized slicing with NamedSlotsNdarray\n", - "\n", - "**Name-based slicing**.\n", - "While the order of axes in a `NamedSlotsNdarray` is maintained consistently, referring to an axis by its name can be convenient. In this name-based slicing, order of index entries does not matter:" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [ + }, { "data": { - "text/plain": [ - "(array([-48.01009565, -44.09912786, -43.40939218, -40.28342854,\n", - " -40.27765944, -39.53927029, -38.81349535, -36.36675152,\n", - " -35.92246726, -35.67741621, -34.9984359 , -34.20284515,\n", - " -32.75162751, -32.5510992 , -31.80731523, -31.46499517,\n", - " -31.08181066, -30.07813715, -28.83587136, -28.19100498]),\n", - " array([-48.01009565, -44.09912786, -43.40939218, -40.28342854,\n", - " -40.27765944, -39.53927029, -38.81349535, -36.36675152,\n", - " -35.92246726, -35.67741621, -34.9984359 , -34.20284515,\n", - " -32.75162751, -32.5510992 , -31.80731523, -31.46499517,\n", - " -31.08181066, -30.07813715, -28.83587136, -28.19100498]))" - ] - }, - "execution_count": 9, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "(sweep[\"evals\"][\"flux\":5, \"ng\":7], \n", - " sweep[\"evals\"][\"ng\":7, \"flux\":5])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Name-based slicing allows for `start` and `stop`. For example, `[\"flux\":3:-2]` chooses the flux parameter values from element 4 to the second-but-last element. (A `step` entry is not supported for name-based slicing.)\n", - "\n", - ".. note::\n", - " Name-based slicing and ordinary slicing by axes position cannot be mixed. If a multi-index contains a \n", - " name-based entry, then all entries must be name-based. " - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "**Value-based slicing**.\n", - "Generalized slicing includes the possibility to refer to an array axis by a parameter value rather than through its index. One downside of this: the parameter value needs to be entered in full with all relevant decimals. This option therefore makes most sense when parameter value arrays are built commensurate with simple decimals.\n", - "\n", - "Example: the ng value 0.0 is one value in the ng parameter array. We can access it via" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "NamedSlotsNdarray([[-48.9776994 , -45.02697343, -44.3665604 , ...,\n", - " -30.97742949, -29.62767069, -29.01259019],\n", - " [-48.93884687, -44.98968522, -44.32814867, ...,\n", - " -30.9413373 , -29.59581918, -28.97953529],\n", - " [-48.82236 , -44.8779047 , -44.2129721 , ...,\n", - " -30.83312517, -29.50035136, -28.88046418],\n", - " ...,\n", - " [-41.09507455, -38.49150016, -36.58723883, ...,\n", - " -24.29075907, -23.7870638 , -23.11887094],\n", - " [-40.69998479, -38.210735 , -36.19428593, ...,\n", - " -23.89182356, -23.6119997 , -22.82192523],\n", - " [-40.26251587, -37.8914427 , -35.7587604 , ...,\n", - " -23.45553629, -23.40840165, -22.49727021]])" - ] - }, - "execution_count": 10, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "sweep[\"evals\"][:, 0.0]" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Value-based indexing will ordinarily fail if values entered do not match concrete values in the original array of values. This behavior can be changed in favor of more forgiving \"fuzzy\" value-based indexing which selects the closest value to the one entered. This is enabled by changing the default for `FUZZY_SLICING`:" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "UserWarning: Using fuzzy value based indexing: selected value is 0.0\n", - " : 24" - ] - }, - { - "data": { - "text/plain": [ - "NamedSlotsNdarray([[-48.9776994 , -45.02697343, -44.3665604 , ...,\n", - " -30.97742949, -29.62767069, -29.01259019],\n", - " [-48.93884687, -44.98968522, -44.32814867, ...,\n", - " -30.9413373 , -29.59581918, -28.97953529],\n", - " [-48.82236 , -44.8779047 , -44.2129721 , ...,\n", - " -30.83312517, -29.50035136, -28.88046418],\n", - " ...,\n", - " [-41.09507455, -38.49150016, -36.58723883, ...,\n", - " -24.29075907, -23.7870638 , -23.11887094],\n", - " [-40.69998479, -38.210735 , -36.19428593, ...,\n", - " -23.89182356, -23.6119997 , -22.82192523],\n", - " [-40.26251587, -37.8914427 , -35.7587604 , ...,\n", - " -23.45553629, -23.40840165, -22.49727021]])" - ] - }, - "execution_count": 11, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "scq.settings.FUZZY_SLICING = True\n", - "sweep[\"evals\"][\"ng\":0.001]" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Value-based and string-based slicing can be combined. The following thus produces the same result:" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "NamedSlotsNdarray([[-48.9776994 , -45.02697343, -44.3665604 , ...,\n", - " -30.97742949, -29.62767069, -29.01259019],\n", - " [-48.93884687, -44.98968522, -44.32814867, ...,\n", - " -30.9413373 , -29.59581918, -28.97953529],\n", - " [-48.82236 , -44.8779047 , -44.2129721 , ...,\n", - " -30.83312517, -29.50035136, -28.88046418],\n", - " ...,\n", - " [-41.09507455, -38.49150016, -36.58723883, ...,\n", - " -24.29075907, -23.7870638 , -23.11887094],\n", - " [-40.69998479, -38.210735 , -36.19428593, ...,\n", - " -23.89182356, -23.6119997 , -22.82192523],\n", - " [-40.26251587, -37.8914427 , -35.7587604 , ...,\n", - " -23.45553629, -23.40840165, -22.49727021]])" - ] - }, - "execution_count": 12, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "sweep[\"evals\"][\"ng\":0.0]" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "**Distinction between value-based and index-based slicing**. All integer entries in slicing are interpreted as index-based slicing, whereas floats are taken as value-based. Thus, `[\"flux\":1.0]` is the flux value 1.0 (if existent), whereas `[\"flux\":1]` is the second (!) entry in the flux values array.\n", - "\n", - "Note: when using integer-valued parameters such as `ncut`, value-based slicing should not be used." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### Quick plotting of sweep data\n", - "Once a `NamedSlotsNdarray` is reduced to a single parameter axis, data can readily be plotted using the `plot()` method:" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "(
, )" - ] - }, - "execution_count": 13, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/svg+xml": [ - "\r\n", - "\r\n", - "\r\n", - "\r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " 2021-07-05T08:37:54.330430\r\n", - " image/svg+xml\r\n", - " \r\n", - " \r\n", - " Matplotlib v3.3.4, https://matplotlib.org/\r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - "\r\n" - ], - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "sweep[\"evals\"][:,0].plot()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "This result looks odd at first glance: where, for instance, is the flux-independent resonator line? The reason for the unfamiliar appearance is that we are plotting eigenvalues without subtracting the ground state energy. For that, see the `.transitions()` and `.plot_transitions()` methods below." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Transition plots\n", - "Energy spectra obtained in single-tone or two-tone spectroscopy always represent transitions energies, rather than absolute energies of individual eigenstates. To generate data mimicking this, appropriate differences between eigenenergies must be taken.\n", - "\n", - "The methods for generating transition energy data and plotting them are `.transitions(...)` and `.plot_transitions(...)`. To create a plot, we use **\"pre-slicing\"** of the `ParameterSweep` instance to specify a sweep along a single axis, and then call `.plot_transitions()`.\n", - "\n", - ".. note::\n", - " **Pre-slicing** applies to `ParameterSweep` objects. It uses numpy or generalized slicing notation to \n", - " specify a subset of the sweep. For plotting, the resulting subset should be a one-dimensional sweep. Note that \n", - " pre-slicing does not actually discard any data. Rather, it internally marks the selected sub-sweep which is \n", - " then looked up when applying `.transitions()` or `plot_transitions()`." - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "data": { - "application/pdf": 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\n", - " \n", + " \n", " \n", " \n", " \n", @@ -4547,12 +1833,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -4563,12 +1849,12 @@ " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -4577,148 +1863,84 @@ " \n", " \n", " \n", - " \n", - " \n", + " \n", + " \n", " \n", - " \n", + " \n", + " \n", - " \n", - " \n", - " \n", - " \n", - " \n", " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", @@ -4726,1195 +1948,1034 @@ " \n", " \n", " \n", - " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", - " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", - " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", - " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", - " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", + " \n", + 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- " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", + " \n", " \n", " \n", - " \n", " \n", " \n", - " \n", " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", " \n", " \n", " \n", - " \n", - " \n", + " \n", + " \n", " \n", " \n", "\n" @@ -5928,17 +2989,40 @@ } ], "source": [ - "sweep[\"ng\":0.0].plot_transitions();" + "sweep[\"evals\"][:,0].plot()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "This result looks odd at first glance: where, for instance, is the flux-independent resonator line? The reason for the unfamiliar appearance is that we are plotting eigenvalues without subtracting the ground state energy. For that, see the `.transitions()` and `.plot_transitions()` methods below." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Transition plots\n", + "Energy spectra obtained in single-tone or two-tone spectroscopy always represent transitions energies, rather than absolute energies of individual eigenstates. To generate data mimicking this, appropriate differences between eigenenergies must be taken.\n", + "\n", + "The methods for generating transition energy data and plotting them are `.transitions(...)` and `.plot_transitions(...)`. To create a plot, we use **\"pre-slicing\"** of the `ParameterSweep` instance to specify a sweep along a single axis, and then call `.plot_transitions()`.\n", + "\n", + ".. note::\n", + " **Pre-slicing** applies to `ParameterSweep` objects. It uses numpy or generalized slicing notation to \n", + " specify a subset of the sweep. For plotting, the resulting subset should be a one-dimensional sweep. Note that \n", + " pre-slicing does not actually discard any data. Rather, it internally marks the selected sub-sweep which is \n", + " then looked up when applying `.transitions()` or `plot_transitions()`." ] }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 22, "metadata": {}, "outputs": [ { "data": { - "application/pdf": 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", 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"HilbertSpace(**{'subsystem_list': [TunableTransmon(**{'EJmax': 40.0, 'EC': 0.2, 'd': 0.1, 'flux': 0.23, 'ng': 0.3, 'ncut': 40, 'truncated_dim': 3, 'id_str': 'tmon1'}), TunableTransmon(**{'EJmax': 15.0, 'EC': 0.15, 'd': 0.2, 'flux': 0.0, 'ng': 0.0, 'ncut': 30, 'truncated_dim': 3, 'id_str': 'tmon2'}), Oscillator(**{'E_osc': 4.5, 'l_osc': None, 'truncated_dim': 4, 'id_str': 'Oscillator_1'})], 'interaction_list': [InteractionTerm(**{'g_strength': 0.1, 'operator_list': [(0, array([[-40, 0, 0, ..., 0, 0, 0],\n", - " [ 0, -39, 0, ..., 0, 0, 0],\n", - " [ 0, 0, -38, ..., 0, 0, 0],\n", - " ...,\n", - " [ 0, 0, 0, ..., 38, 0, 0],\n", - " [ 0, 0, 0, ..., 0, 39, 0],\n", - " [ 0, 0, 0, ..., 0, 0, 40]])), (2, array([[0. , 0. , 0. , 0. ],\n", - " [1. , 0. , 0. , 0. ],\n", - " [0. , 1.41421356, 0. , 0. ],\n", - " [0. , 0. , 1.73205081, 0. ]]))], 'add_hc': True}), InteractionTerm(**{'g_strength': 0.2, 'operator_list': [(1, array([[-30, 0, 0, ..., 0, 0, 0],\n", - " [ 0, -29, 0, ..., 0, 0, 0],\n", - " [ 0, 0, -28, ..., 0, 0, 0],\n", - " ...,\n", - " [ 0, 0, 0, ..., 28, 0, 0],\n", - " [ 0, 0, 0, ..., 0, 29, 0],\n", - " [ 0, 0, 0, ..., 0, 0, 30]])), (2, array([[0. , 0. , 0. , 0. ],\n", - " [1. , 0. , 0. , 0. ],\n", - " [0. , 1.41421356, 0. , 0. ],\n", - " [0. , 0. , 1.73205081, 0. ]]))], 'add_hc': True})]})" - ] - }, - "execution_count": 8, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "sweep.hilbertspace" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "HilbertSpace(**{'subsystem_list': [TunableTransmon(**{'EJmax': 40.0, 'EC': 0.2, 'd': 0.1, 'flux': 0.0, 'ng': 0.3, 'ncut': 40, 'truncated_dim': 3, 'id_str': 'tmon1'}), TunableTransmon(**{'EJmax': 15.0, 'EC': 0.15, 'd': 0.2, 'flux': 0.0, 'ng': -0.5, 'ncut': 30, 'truncated_dim': 3, 'id_str': 'tmon2'}), Oscillator(**{'E_osc': 4.5, 'l_osc': None, 'truncated_dim': 4, 'id_str': 'Oscillator_1'})], 'interaction_list': [InteractionTerm(**{'g_strength': 0.1, 'operator_list': [(0, array([[-40, 0, 0, ..., 0, 0, 0],\n", - " [ 0, -39, 0, ..., 0, 0, 0],\n", - " [ 0, 0, -38, ..., 0, 0, 0],\n", - " ...,\n", - " [ 0, 0, 0, ..., 38, 0, 0],\n", - " [ 0, 0, 0, ..., 0, 39, 0],\n", - " [ 0, 0, 0, ..., 0, 0, 40]])), (2, array([[0. , 0. , 0. , 0. ],\n", - " [1. , 0. , 0. , 0. ],\n", - " [0. , 1.41421356, 0. , 0. ],\n", - " [0. , 0. , 1.73205081, 0. ]]))], 'add_hc': True}), InteractionTerm(**{'g_strength': 0.2, 'operator_list': [(1, array([[-30, 0, 0, ..., 0, 0, 0],\n", - " [ 0, -29, 0, ..., 0, 0, 0],\n", - " [ 0, 0, -28, ..., 0, 0, 0],\n", - " ...,\n", - " [ 0, 0, 0, ..., 28, 0, 0],\n", - " [ 0, 0, 0, ..., 0, 29, 0],\n", - " [ 0, 0, 0, ..., 0, 0, 30]])), (2, array([[0. , 0. , 0. , 0. ],\n", - " [1. , 0. , 0. , 0. ],\n", - " [0. , 1.41421356, 0. , 0. ],\n", - " [0. , 0. , 1.73205081, 0. ]]))], 'add_hc': True})]})" - ] - }, - "execution_count": 9, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "sweep2.hilbertspace" - ] - }, - { - "cell_type": "markdown", + "cell_type": "markdown", "metadata": {}, "source": [ " The generated transition plot is based on default choices:\n", @@ -7746,20 +5348,12 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 25, "metadata": {}, "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "FutureWarning: `subsys_list` is deprecated. Use `subsystem_list` instead.\n", - " c:\\users\\drjen\\onedrive\\coding\\pycharmprojects\\scqubits\\scqubits\\utils\\misc.py: 195" - ] - }, { "data": { - "application/pdf": 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\n", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "sweep[\"ng\":0.0].plot_transitions(subsystems=[tmon1]);" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### `initial` and `final`\n", + "By default, the ground state is taken as origin for all transitions. In case of thermal excitations, other states can be of interest as initial states. Specification of an alternative initial state uses dispersive labeling of states:\n", + "\n", + "e.g., (1,0,0) uses the 1st excited `tmon1` state as the initial state:" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": {}, + "outputs": [ + { + "data": { + "application/pdf": 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "sweep[\"ng\":0.0].plot_transitions(initial=(1,0,0));" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Similarly `final` option may be used if only the transitions to a specific state should be highlighted:" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": {}, + "outputs": [ + { + "data": { + "application/pdf": 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jgec41L7ENJ7jFJME4Lul8ZLCLhyFz/2RGit3YHDgh7Wj5YBvLKeWuvbtPPAUf1n7KRvwXCGYz+jguTdLudUAPJZR+9v5OOJphZF+x1o93hCyh9OOxFsVYsbSHQTFLY+VeDjgB7P4sQpbH5x4mC7m5TSmnnggS786RyR+UvOT+WxPPNGGnobSHQSFFZwjenjcENn6ucXmmMfzVWqOnTHUozR1bV1uzEOP2B4a9uQINxM3jdDDoai1pQXo8SPS4LW1vEEP/9nYlBWgh3dGhJdbxB4Y1w6vXSL2g20MSx837Cff6+TGY88UGbYp9MtwUZKwvrZhb2s1k6z9PYe9KqdjcaunXrl1JGNGL4/VaizcjEA99DQLkqcY1tNNypQaN+fYAFF1mdyNek64prg5Z5ExVqiGFprcqlkni7E26mkUIR8N1GPKlXHBnZuH9lBNo5vnKs4z/fDUc2oQxtyh1zWBGNaz46GzghyYV7op6EzYhOf1vbXeY+kOckLa0OVZSnfszdaaeqkBek7i3Pq+QY9Vgjsoq0Jygx6WC9a9lLaH9cugjOVYHfPsYVCsqwTmJ11iqjPW6+n/Md2VIDvmWSzrLMY+wbwd3YjMV5Z3eoqB/UDIXNK5h+6Yn9xAldZj8Y4tQ9CcEiJ7BEss8Cwf4ZinLJGu3CXyJvqkZ059Y97a5RMinpDIS+KplJFGZB5PKqeWOuZpCxAZzAWZh56d1yPHXjmq9QREI7p6NjAgki6hX47LBdjaXWxvCc44Q4YdegR3qUXoh+2jyAxb8qtegii+B+gZqyvVN0BPbhJ0OXTPGX/IW+9yeYwjASkSoF/LCOnJRj2lX+rbTf8b9ry8gTON23QwuQwrS/T1aqlJ0ZjNY3zMsjpcPjz2mTo2ebppwx7DCPdSDtgD0iqpzb1+J7lj0XW2vX4nLJilIi36em6dVxjZ2H1jPlRWsXrjnr9aUo2+vjMgUV29M4576jJUxxTec4/r8da5xAAfSFPDe/T1bK0DaC1wT9C0wkeHoj2NopC5UMCTjFfh6Zbg6ylk4XAI8e3MVddVCPbcY7wkvNDYuYf0G7e6Ivd8bDqn6biXLHiTdIYMnvtuqVukHq4yp363TwdNhnqVtQPvqJ/QLRB6V8GDcnX2Yt5Rj0wfocrqWvHUN3bDlXpHPZtAIMAY4CuLZvMuwLfFwoO77NTTuA5ujIRuO44j+zlxvVG/1rD20DtL4fNcxQzU8/pO4yo79RQ+2xNyKNrTSAOCabr/4alnaQtLF5popbCLjvtIO/XIl+mmxx7hCwgtUIwSqTdJ5RXJ36hf5jSdtT1HPReOVfgeqJ92fW+h6Y4xnY7VKeKhJ89If0PTHUJ7CBFGKEfmoQmiJQdfz1Alp3bGJJ55VkGgFzkwT4sIsEboxzEDyo3QHJhfQmsl+vol4xEb77gkWClJ++48L08woDn04wAYCA35xh3zBKueFN+Yp4lG9t5zCPC5WIiDz31GRz1Md+ZOYGitXaabGW2gnlXhhjvFtN6OFEIZ7nw9a67prr+WCQQjrbvdeYaQs1YNu/NGMe5/Bv436jOLsWA37NRxGcdY0vfQs+Sq516+g14qLWhfZT8HPQ/BIJvRULin9GGgs+0he+itd6GV8jyuvnCLhhZmZx46xQx477OF/eNda9rr9iK4Xctn6LwzzwggNM+b2mEtSqjkCZvh0toV2pBnci1ro8QjP1icPrvMAvNw/ytyC9CzUeeuB4/FMNEzSffQdygg1Cv00C/PqjG8F26B5Vi3J5w9lxUXeuKLbc2vjr2NeK4n85974mmE8741f5psuSN+XX7XgcffBHYraNqI77bLGJtt6ZgAxKqUO+JpCYq+Td1vxNNQFmRjMxbyGGVDJ1rswKPal9w0FvJwS8zyzK0d8dYuzZeMxA+6izYi8Zi/JtiJ6OdpiEvV0I4DQbIVd5VdHfEgu0HpV3nPE29mW2Jwf5rt2kI7DjkBAhIK9xYRa1q68OGBr2wE5FcGduIrPymQVrHEEc9KWGe7wk48psWwZISUvhACdpBG4pXFj7Pm7oinqStkOCCvnICu07Ee+Qk/XMp57sYjjx+RrYxwzo0VHfzYbePGI08NxGgOu3VwMjwU3izM25AniNyZjtBDTctcPeqeemBZdPQRY3tMuXJ/JFJf2+0UrKeeHTbwrjVQb/tdENAd9VSR1loo35/6WFr08+xFHGmstl5PPUsqefVpBOq5JdqCn6fY4J376iG8UU9rQOkvK+SpZ/gFmx735xEvJBqDWL5HvIC08yy736i3Mic3b0NOb5knWQg5vcVBHViVgD1+tfP0QN2xZ5QlucywYWdGF+or4TgNr+f6z+jozda3lTF67rGgsBG1PY+jb+y94Zvt3HNffKbVAeK55xZFWzVVxz0L6bVJ3pvtLVxoKTbhEY/R+2qS89SzyZMvvlMvduJD4nkaQl+AeY7F+27l19Xc6KHn+S82FoaTclbR4d5kOFRj0R+S2RwTenYAyMwjQg+F4p51Dnt2Uinrep6Lc9C3xI+lrAjAMd9Y/oR6RU8PyfPgXqzjGfN1ndHbmFcIc/U5bsgL0/wZa/fLZWG6YYd+5Wd9dV165DPL1rPGhJ7jwKyksEWP9+GeVEmxJUehFWyZiU14tPQTyMTaPavo+P0UHL1lXOyTDofnGJTziyzLdDjkC79xIGeDrUeeBzXqaiJ0yLNLTs+ygyMeWjcYF4SeHFuHUno8XHOGX61E4i1cQ9DzPMV7vNacPLkWiO9sCu5hx45K0vpQUzBPvFpPRN37bmkI8MIpFO/5glCc1QcekEd6q2GPno5DWx0aa/fK3qimNdbu19HEtXvoiMflcNot7tGz9Ib8c50f2IjnOzEFicQLz0Ks6NITDxlgZilW7hu/4TGXaDbgV/tZDrt1C8PzfIcnvjX6gTJCNt/sgMccoQlPWrXeynDEnU8FXuvspyeeMUSptYQSHr0SQiYJZ2sErFUecQ1nawg8rEOKXbd8j8T2qRDZU/aDBw5iBQ/yG3bseQeevtzMW8jlISCwDI2OPh6hOs/KlBGBZ5+FrjKvB77x/rWEphyGvZ1fDrojnpFjW22dnnjuKtH1h+066gL+aNyjJyd1rIrGhwee29C5phja8wMuiHtC2609bjC524G3Spq0sEVPq4H3KBqTedYPAPAM23X0/TDHZ/LvkS/Mpe5266A5XMEaj9dMO+64tls25KGmFY4jVPDMmUOqNSbzYn11bYTjNXSruM95enBHXvnFp+jkO6af56oQeua5G9H7XK2rjvk+wC3DjsA8VG0gZGohsrfuXR4aj8zjNvwYUWjEozoiCVun1D3zzPHOA/0b8zy6v9pjNub5kSxd8ZtnHsvW5WyvdciDzgzL1IOPt6o3IqkY1p9iGjGZFzspnFbV0yPPo2olrYMhG/LUIrxuDsiDMSz/av2OyA8Yir3TXrhD2M5asUe+27mCM2vwyLP7uOUaw3rKewXvHvhmXzYYz5TMTyaOKnF/nlVy+NsZNurYxjVL75F45SGqEnjHXBH3xJYcvjVPSLdQsMcUoIl5nTvceOeJv3GeX/PAs6mJxx0D8Nxek7fbgx74ab2iOaTypnSJ6hKAh6yVOzPRx9s5uHEX1FtraV3bzBvvk0dlzhTW8Q79YKtLjVH9sErHMviedyQxChvcA+/8GlrSs77meLePgIxVIvW8c+mxxLF817g/Ueod7pAx2/XD3vwqMtayioyed64JrEnM42EfIOHTPuzAs5s4xPR02WmsnUSPu52IrOudPO5UCu5lxNodX4rfFgztOBxn99zaave4WxdTGxF3HiKu5R53NvFriyE9m5JyqzWcq6HkIQdNsXjX2IqGiON5tuhYCZH4RSpozMEF0RDRw3faZz9C7Y4qCrJLyOGp6WPtOgTeeZIihxY8pkQz55bCtjyN90BCGttuV2+Qph4dvPLMBI9PRd7ZTKbneT/HO33V2bDnaGcBLcEMhK5b2nR+PCXHTfnO74isIxmediy+wiPd7clP5iN1fQHE086v7yDdvdufm7aHn3vYk58QB6xA/GaVcML8HkcM6TtblejBIu7sAhbpMYlnMKP1TCQ874Ntqy2HtlvayME+vjveJ8SNxYoOXjqPWOnqVHfAmx1o6/s8G/FsfUBUHM7VUHc0yRlEe+L5LZ4xSjg9a3IoZ6nEE8/xdLYxO+IHjzTpkNiLAzHX3keODn6w1jBXhcYjP0A5UuISenFoUbT3/GuDehgYI57b3nCPmPIlwb5ma+rnVz5pBezf+vUPr65//+bV37959Tf4zatf8k2cpz5u9d3/l49bmXd+9/n0ncInP97+1BfZca9f/KF3XMvPtd+bh+sD83ABEHhlriVbJRtdIO7PL7Psg99egNf9IB6a7EX5rfif+Wl6/uw/+onl5peC2urR7GxsXV/p5EeK87vvIOe3n0xen0Hm8/G/ZOWx9dnlfzg/u5wVISydcj3/4df+RrZPHtHIQJt+9b3yr3z6kx96poeE5vLc73grnvuvNX/+449/+fnHr7/86q9vP9r86eV/AQoMS0oKZW5kc3RyZWFtCmVuZG9iagoxMiAwIG9iago2NzUyCmVuZG9iagoxMCAwIG9iagpbIF0KZW5kb2JqCjE3IDAgb2JqCjw8IC9MZW5ndGggMTY3IC9GaWx0ZXIgL0ZsYXRlRGVjb2RlID4+CnN0cmVhbQp4nDVQO7IDIQzrOYUuwIxlMODz7JtMis3929jO2wZ/hISEukAwHJ1jQ3nAGP7YOK3aT+Py6ngSVKgIqIKrKRWUH81ZZbP2B2a4q9FkpD7BuNTnjhvcA/0E2yQRLcGycLXHzN1WgYZ90N3gir4t2bLQ4wEy6kjyDLUHmPABxQl8xm4vaEhohozTUiBqGL2zhqWQzxT+xKJoBc2pgv9/xdXe7fUFgMc4LwplbmRzdHJlYW0KZW5kb2JqCjE4IDAgb2JqCjw8IC9MZW5ndGggMzc2IC9GaWx0ZXIgL0ZsYXRlRGVjb2RlID4+CnN0cmVhbQp4nEWSSW4FMQhE930KLvAlM3k4T6Ioi5/7b/OgO8rCAjEUReE5hgyZIS9VyQiZZ8unXjm2THI/l57be1+6h3h6e+vPOyk+l9hw8XXE1MTPkI/LbEgMFXMs4BaGPZWhM4yeOSXcxbZiV2VAi1BxpQIy7rf9uHw+EbDDD0j0WqHFgxssEYO3YbInmRzW3FJhS2/aBrnmpG8xkGphm4+17sHTgxRUaB56lqjXPslERYfkLWiybBazSNAh5ypgB9nZfI+8kMZvZWuxsqzIIh3xKa/Ver0qrntLiiKJwiDgVzA1upgQS+3xs8Ksh2Yr5Ky6nSIXtUHv2nUUiGnFmaXVt7AxeoqJIoMeIsqQwUztc0Fen3Md1IiU+4zIs1NsLUFYO23YD1Yl9OpqP8C2slHs6z5WZLSt9eLtWf2Z9uqe1NrTfd+l4JzuQvfUHle2aNyeBUPhZnaLS2aQMeurOato/cLzqOTjlB6IXP/6fX/rf6+/9ff19Qvy64+4CmVuZHN0cmVhbQplbmRvYmoKMTkgMCBvYmoKPDwgL0xlbmd0aCA4OCAvRmlsdGVyIC9GbGF0ZURlY29kZSA+PgpzdHJlYW0KeJxNjcsNgEAIRO9UQQmwfIR+jPGw9n8VNka9MG9C8saJkFCtjrmhZ+DOEFH96kjFCSP0A2dv2vwhZkVVKSqLkfVzyDJNkLQfLUfPvECVa2zCCccNeFgbYQplbmRzdHJlYW0KZW5kb2JqCjIwIDAgb2JqCjw8IC9MZW5ndGggMTM0IC9GaWx0ZXIgL0ZsYXRlRGVjb2RlID4+CnN0cmVhbQp4nDVPOQ7DMAzb/Qp+oIAoJ7b8nhRBh/T/a0SlHWIJFK/4Mhim40XCGWBfeLNx2wv6NrrVRkvShuQHjjYDXro+9O5DmGMSl2aykkEb2siVV+nZ80udQpSgmZexHiSiGG5/jdPLRMXSSCMThIcir1q67lKVUOVklFXlW81//3K0TztvyuksSwplbmRzdHJlYW0KZW5kb2JqCjIxIDAgb2JqCjw8IC9MZW5ndGggODAgL0ZpbHRlciAvRmxhdGVEZWNvZGUgPj4Kc3RyZWFtCnicTY3BCcAwDAP/msIj2ImjNPuU0oez/7cOpKUfcQh0oqqosGa0SuE45DRYtywmvLhQmwSM+iPvTMrVB2sYeBWb0h0oYz3EdgZuXA8YPhaICmVuZHN0cmVhbQplbmRvYmoKMjIgMCBvYmoKPDwgL0xlbmd0aCAzMTYgL0ZpbHRlciAvRmxhdGVEZWNvZGUgPj4Kc3RyZWFtCnicPVI5bgQxDOvnFXyCddvv2SBIsfl/G9ILpBkJEi2R1PRaWKjRJw1jC1/2KF34fVr1t4KtzcTPQqxhFl6IOIhyRDOOIc7G6wli0gfJyVn7E1l7PcpqBV/fLAaxD6rjTqgdep0HvTjTDW0O33Pj6/H+ZF6LiAOPZtQbd0edgbNa3GRH07TR9qY2VoYVcrEhMkudLjIwWJOJUV81uWkPvai8qpPcHJOXmnjcbRzeHjArdDosGEvCrRJNtA2hu0kn0KcvwYNZBecyOeysKlJufDwPmjAraSFln5RZxj07kdzRtCebnTJ1KK0jaCo3m5E2pWztKXIqCXLZG594SSvLYZeIpMXFI6bLiDw6kSE5IYa5DkkP2CmdmHgdSu9ok189IbNHeGoiNip4jrmGHxDyvn/QfyI3f57vP0N7dBsKZW5kc3RyZWFtCmVuZG9iagoyMyAwIG9iago8PCAvTGVuZ3RoIDM2MCAvRmlsdGVyIC9GbGF0ZURlY29kZSA+PgpzdHJlYW0KeJw1UTluRTEI7N8puEAksxqf50dRiuT+bWbwTwXCMJtrLVkSWz5UJdNl65JPfRxzjn4fy5rO9MiHi/YWdXk9mil2RK0lTXS1NMd8xvvGKFUK5RTGWLEYIjvK4nEwRhMrCRCgwXYuxRjXGSXAyo7BLk1ygqwihdxVZ8RU84XqNm6plhaon/X1eN9J5JLaLQH+i5YOmry2o3zqlcXOHLqwoRDCm3FHEAN630z+U3o935MYxP4+bsHGA6XFS+U0dYCbTvwA02B4IcygwkBemlBmKroPaoEk+OKgQ8jh0JP71u55gWa4+rkdo8VuVM91nBELvFRMgJ/cWPQ4WqAhdwk1ZZ8RmYfOqboWJjBRGuOQFQljn50xe2yY9/vGyAMUW3tQ9ew3jyInMit5oER3vLUpfo9qtfaonzr/xY4ef24H19xlCry+uRCPSRGfyZHxZkkNTJeamDZVTvyUDVS66GurY/7t6w8B+49jCmVuZHN0cmVhbQplbmRvYmoKMTUgMCBvYmoKPDwgL1R5cGUgL0ZvbnQgL0Jhc2VGb250IC9UQVBJQkIrSUJNUGxleFNhbnMtTWVkaXVtIC9GaXJzdENoYXIgMAovTGFzdENoYXIgMjU1IC9Gb250RGVzY3JpcHRvciAxNCAwIFIgL1N1YnR5cGUgL1R5cGUzCi9OYW1lIC9UQVBJQkIrSUJNUGxleFNhbnMtTWVkaXVtIC9Gb250QkJveCBbIC0yODAgLTI1OCAxMjgwIDExMzIgXQovRm9udE1hdHJpeCBbIDAuMDAxIDAgMCAwLjAwMSAwIDAgXSAvQ2hhclByb2NzIDE2IDAgUgovRW5jb2RpbmcgPDwgL1R5cGUgL0VuY29kaW5nCi9EaWZmZXJlbmNlcyBbIDQ0IC9jb21tYSA0NiAvcGVyaW9kIDQ4IC96ZXJvIC9vbmUgL3R3byA1MyAvZml2ZSA1NSAvc2V2ZW4gXQo+PgovV2lkdGhzIDEzIDAgUiA+PgplbmRvYmoKMTQgMCBvYmoKPDwgL1R5cGUgL0ZvbnREZXNjcmlwdG9yIC9Gb250TmFtZSAvVEFQSUJCK0lCTVBsZXhTYW5zLU1lZGl1bSAvRmxhZ3MgMzIKL0ZvbnRCQm94IFsgLTI4MCAtMjU4IDEyODAgMTEzMiBdIC9Bc2NlbnQgMTAyNSAvRGVzY2VudCAtMjc1IC9DYXBIZWlnaHQgMAovWEhlaWdodCAwIC9JdGFsaWNBbmdsZSAwIC9TdGVtViAwIC9NYXhXaWR0aCAxMzM5ID4+CmVuZG9iagoxMyAwIG9iagpbIDAgNDcyIDQ3MiA0NzIgNDcyIDQ3MiA0NzIgNDcyIDQ3MiA0NzIgNDcyIDQ3MiA0NzIgMjM2IDQ3MiA0NzIgNDcyIDQ3Mgo0NzIgNDcyIDQ3MiA0NzIgNDcyIDQ3MiA0NzIgNDcyIDQ3MiA0NzIgNDcyIDQ3MiA0NzIgNDcyIDIzNiAyOTggNDUxIDY3OCA1OTkKOTQ3IDcwNyAyNTMgMzM2IDMzNiA1MTQgNjAwIDI5MCA0MDEgMjkwIDQxNyA2MDAgNjAwIDYwMCA2MDAgNjAwIDYwMCA2MDAgNjAwCjYwMCA2MDAgMzEwIDMxMCA2MDAgNjAwIDYwMCA0ODcgODk2IDY2MiA2NTkgNjM0IDY4MyA1OTMgNTcwIDcwNSA3MTQgNDE2IDUzMQo2NjAgNTEzIDgxNCA3MTQgNzEyIDYyNyA3MTIgNjU1IDU5OCA1NzcgNjg2IDYyOCA5MjYgNjM5IDYxNyA1OTEgMzI1IDQxNyAzMjUKNjAwIDU2MSA2MDAgNTQ5IDU5MiA1MTAgNTkyIDU1NiAzNDAgNTM3IDU4MCAyNjUgMjY1IDU0NyAyODUgODgyIDU4MCA1NjQgNTkyCjU5MiAzODMgNDk0IDM2NSA1ODAgNTEyIDc5OSA1MzAgNTE0IDQ4NyAzNTQgMzUzIDM1NiA2MDAgNDcyIDYyNyA0NzIgMjg2IDQ4NAo1MDIgODQ2IDU0MCA1NDggNjAwIDEzMzkgNTk4IDMwOSA5OTAgNDcyIDU5MSA0NzIgNDcyIDI4NCAyODQgNTAxIDUwMCA0MTAKNTg4IDc4MCA2MDAgNjI5IDQ5NCAzMDkgOTIxIDQ3MiA0ODcgNjE3IDIzNiAyOTggNTI5IDU4OSA2MjAgNjIyIDM1MyA1NzcgNjAwCjc4MiA0MjAgNTMyIDYwMCA0MDEgNDcyIDYwMCA0NzAgNjAwIDM0NiAzNDUgNjAwIDU4NSA2NjMgMzU2IDYwMCAzNTMgNDE0IDUzMgo4NDcgODUwIDgyOSA0NzkgNjYyIDY2MiA2NjIgNjYyIDY2MiA2NjIgOTMzIDYzNCA1OTMgNTkzIDU5MyA1OTMgNDE2IDQxNiA0MTYKNDE2IDY4NyA3MTQgNzEyIDcxMiA3MTIgNzEyIDcxMiA2MDAgNzEyIDY4NiA2ODYgNjg2IDY4NiA2MTcgNjI3IDY2MiA1NDkgNTQ5CjU0OSA1NDkgNTQ5IDU0OSA4NjUgNTEwIDU1NiA1NTYgNTU2IDU1NiAyNjUgMjY1IDI2NSAyNjUgNTc0IDU4MCA1NjQgNTY0IDU2NAo1NjQgNTY0IDYwMCA1NzAgNTgwIDU4MCA1ODAgNTgwIDUxNCA1OTIgNTE0IF0KZW5kb2JqCjE2IDAgb2JqCjw8IC9jb21tYSAxNyAwIFIgL2ZpdmUgMTggMCBSIC9vbmUgMTkgMCBSIC9wZXJpb2QgMjAgMCBSIC9zZXZlbiAyMSAwIFIKL3R3byAyMiAwIFIgL3plcm8gMjMgMCBSID4+CmVuZG9iagoyOCAwIG9iago8PCAvTGVuZ3RoIDM4MyAvRmlsdGVyIC9GbGF0ZURlY29kZSA+PgpzdHJlYW0KeJxFkktupDEIhPf/KbhAJPO0fZ4eRVlk7r+dD1qaXlggbIqqwnVTluSRL1Upc9m65I8+GSm6TP6S2WS/T7pLXUk1oRb7iKm8nogAIpYOhscb6/X4ysmsSr5czJfQ+Xr0htgWrZCk5FfO6rK6KMMvAYx9RUlfTyWtpynaHaYelzJJrC3cRs7rXP2alqS7wfLUoJdWw/Oygsotqb3ARMzpG0PTRqAzvNV75kSU6Z4seF/0tfKq09MzQFszoxhcCwK5+6armm2XITANYv1OJeisIRlOF7d+Yec5EzviGdXOrFnaxSe2oj3RWEgh2NhRXhPD3dzj59kzRzc3hvbymclNOtxt/Ax4TVzjRrSdDsvJcLDfmtV06+2Jjacob3zFuZ6oNo7BQcExquzEeLh7J9Z6WJC1LHFOtVwHgCTwiK8QrjK8g4n8oSZ4CBxd/W9yxXt/uK9AZX+WGNe9+aE2FI5ros12Jzvteg/7ZJ6XrP/1J1u9m8j/8f25f57vf3RykXYKZW5kc3RyZWFtCmVuZG9iagoyOSAwIG9iago8PCAvTGVuZ3RoIDgwIC9GaWx0ZXIgL0ZsYXRlRGVjb2RlID4+CnN0cmVhbQp4nDM3MFcwULA0BhJmhiYKZpYWCimGXKbGBgrGhmYKuVyG5uZgVg6YZQCkwWrBFEgxRBzBMrYESYL1w1kQWZjxEBZMDq4abEcGVxoA4pscBwplbmRzdHJlYW0KZW5kb2JqCjMwIDAgb2JqCjw8IC9MZW5ndGggNzEgL0ZpbHRlciAvRmxhdGVEZWNvZGUgPj4Kc3RyZWFtCnicMzY0VzBQsDRW0DU0NlcwMjVXMDczUEgx5IIJ5YJYILEcLpgshGVmaQ5kGZoZIbF0zU2gskgskCk5cPNyuDK40gA21RbVCmVuZHN0cmVhbQplbmRvYmoKMzEgMCBvYmoKPDwgL0xlbmd0aCA2OCAvRmlsdGVyIC9GbGF0ZURlY29kZSA+PgpzdHJlYW0KeJwzNjRXMFAwM1DQNTQ2VzAyMlEwB3JSDLlgzFwwCyybwwVTB2GZmwAZhqamSCwzS6gknAEyIwduWg5XBlcaAPpEFkYKZW5kc3RyZWFtCmVuZG9iagozMiAwIG9iago8PCAvTGVuZ3RoIDM3MSAvRmlsdGVyIC9GbGF0ZURlY29kZSA+PgpzdHJlYW0KeJxNUktuBTEI288puEAlPoYk53lV1UV7/20NM1W7iEAkGNshcUQFS97MJNUlfcu7Xb7OlL4vR0zmPG8ptkOWvC5L5kcsVGKJmUoZy0dlpyywElIhhmI1XYyAHONWE3Kz3MnZHCkR2a+jDsvsBpkQCkRvaCR6ZDTTLT0ap4ZKanc0t3RyJNcW0Ow7vq6wuxLAvIjlT0+cMyhwH1SAMZstqARBEou3ugS72Nei+31QURsV5hN9jcLOYssXWdr/zPBkdmgCUW0xBw9lUxOoJ+gTDTFb961G32zIPuKqQnZOr5e2VEIXZ5UKW5yP8tZZnQToY46P20ZkSGskVzNqdLqGUULvTIvcUNXIAA8d0OSs7qxejPB7M37X4XV9zmq0RVyNXJM5NwC5hiQwH6K0sEVyGdDiaTvs3hu+0V6MI7GbDq2suaE5MXbYzJ1IOq/byNOWgjL/suBHPlmvBFHj9BdTqM0XZ5DFIprePB/mreLjBwbyjagKZW5kc3RyZWFtCmVuZG9iagozMyAwIG9iago8PCAvTGVuZ3RoIDYxNCAvRmlsdGVyIC9GbGF0ZURlY29kZSA+PgpzdHJlYW0KeJxNlEmOHDEMBO/9Cn6gAXHRUu9pw/Bh5v9XR1IewJdiQhK3ZLJmHBtWae9wtxnD5ln2y1+C77ns+yIfj9XzAOpYzQ3YaZ9X+QQ+x3L+ixF7XPB5+Xku9HTAGPYsOR7uloISX6k9qu0pRczOO7nPstXhOd6ESqOCbR7TSEt8QCz7ej34D+PJKn2fcx0U9/CekD4Kn91Ow3xTU4X5wa6DlUejJ4jnuS3GMve0iK2yY84bNE4Y7unVhjo5Buxle1LGsIOJ4FhlFXnHtlrR5VQ37+Wwyc2Cc+XBZXZLAc8zyJqcMJtY135eObxRwsoMEq7Et2+EfFN3I2rPtW0ykNzYtfSGqU6qL0UBFzlkP6857sy/LnKhGvEfqpNC8FbELSqrwpbaVM011XdyKxrOtc1LI3XNQJPo8otmoMSwxs9tgAuOIiSafAbcTyIxp4ce6vLDDaQ6NMfD/HfAzWoLa/Xck9QL2HPd9LTRgm6cHhwuffFyqm+nai+pgxc5r22pNaIfvaAAp5CrD/TJ8IOrM1oXR01mNhBXLqAmxdNucYtggj9216jsZ7E+rz8vcfhGGd8XSRUEe4eYZWO8N2xoBZpYSEl9JVXG2UIte9ORH7Yjrl3aokZM1UMbJ4ndRYt2ViUp2fdCw2iOCySzuhA1wUPDPPJNqUcnd+ikezu73ZU/w356UV+aTKR+Hpq6UMJWsAspBaymbUkLqzWaqKxtdglCdPF1kX4u4jOyvSuf1gKI+bSqeKuM1Z1LA30Cb3oh7VwfzV9RNFdFbXvZEkr13Ihq9FbVyfvWq3jqQPHV0U+P6vf3X6x6+sYKZW5kc3RyZWFtCmVuZG9iagozNCAwIG9iago8PCAvTGVuZ3RoIDE3OCAvRmlsdGVyIC9GbGF0ZURlY29kZSA+PgpzdHJlYW0KeJxNkDsSgjEIhPucgiPwWBJynt9xLPT+rUB0tMkHbAJLfAYxheeBCHINusno/FVwmfQcMv8jmHa0v1EIYQrJzkqAVJWcla6hqHebdM1ubeLNa9g8wyCcN3I4skfeugaWZqZtx7YdmpQS5fU5wD+arE8E3mTlySfplmY6WH4qXkp6A5JcimYFqeReAJMyep9ryM7pCpJIipFUDy4Hkq4tNtUv2MKhRyvenuLgMe5vGQ1BKQplbmRzdHJlYW0KZW5kb2JqCjM1IDAgb2JqCjw8IC9MZW5ndGggMTI0IC9GaWx0ZXIgL0ZsYXRlRGVjb2RlID4+CnN0cmVhbQp4nE2Oyw3DMAxD756CI+hr2fO4KHJI979WVpKiF/HZAklpDxCG51AnOHe8uNX7s2V/nI37P5nwpqAfTZg5eHZY5onkZgRWEzM4dUhE+ZVn6WpP2VlkWkR6k/gsEtltmUgMY04fZ5LO7Mo7NOzSTFh1GaV3XHK09xfbGimZCmVuZHN0cmVhbQplbmRvYmoKMzYgMCBvYmoKPDwgL0xlbmd0aCAxOCAvRmlsdGVyIC9GbGF0ZURlY29kZSA+PgpzdHJlYW0KeJwzMjZTMIDDFEOuNAAd1gNRCmVuZHN0cmVhbQplbmRvYmoKMzcgMCBvYmoKPDwgL0xlbmd0aCAxNDMgL0ZpbHRlciAvRmxhdGVEZWNvZGUgPj4Kc3RyZWFtCnicNc87DgMxCATQnlNwgUgejD+cZ6Moxeb+bQZ73T0xNh+P0KIY+gLl07Sh6xvipS7+5BRvsQa+QyS9kdXVahA+iEq0oZeYZb/OGjIcncifbMSwWHIqImthnD4TjSF6to2h8NgroWLjkihb95alMHBoWPkqPgvHgRk0e+/FJ9Yx5QHH7+zcfMtXPn8zkDVjCmVuZHN0cmVhbQplbmRvYmoKMzggMCBvYmoKPDwgL0xlbmd0aCA3NyAvRmlsdGVyIC9GbGF0ZURlY29kZSA+PgpzdHJlYW0KeJxNzLERwDAIA8CeKTSCMTJeKJdL4ezfBrlI0qCH48QkGiJqMBzDE4fb3m9FTiyLniCzxP5Bv0L8xCF5J2bTqSpfKHfxssvOB2gRFxMKZW5kc3RyZWFtCmVuZG9iagoyNiAwIG9iago8PCAvVHlwZSAvRm9udCAvQmFzZUZvbnQgL1RBUElCQitJQk1QbGV4U2Fucy1SZWd1bGFyIC9GaXJzdENoYXIgMAovTGFzdENoYXIgMjU1IC9Gb250RGVzY3JpcHRvciAyNSAwIFIgL1N1YnR5cGUgL1R5cGUzCi9OYW1lIC9UQVBJQkIrSUJNUGxleFNhbnMtUmVndWxhciAvRm9udEJCb3ggWyAtMjYwIC0yNDUgMTI0MSAxMTE5IF0KL0ZvbnRNYXRyaXggWyAwLjAwMSAwIDAgMC4wMDEgMCAwIF0gL0NoYXJQcm9jcyAyNyAwIFIKL0VuY29kaW5nIDw8IC9UeXBlIC9FbmNvZGluZwovRGlmZmVyZW5jZXMgWyAzMiAvc3BhY2UgNzEgL0cgL0ggOTEgL2JyYWNrZXRsZWZ0IDkzIC9icmFja2V0cmlnaHQgMTAxIC9lIDEwMyAvZyAxMTAgL24KMTE0IC9yIDEyMSAveSAveiBdCj4+Ci9XaWR0aHMgMjQgMCBSID4+CmVuZG9iagoyNSAwIG9iago8PCAvVHlwZSAvRm9udERlc2NyaXB0b3IgL0ZvbnROYW1lIC9UQVBJQkIrSUJNUGxleFNhbnMtUmVndWxhciAvRmxhZ3MgMzIKL0ZvbnRCQm94IFsgLTI2MCAtMjQ1IDEyNDEgMTExOSBdIC9Bc2NlbnQgMTAyNSAvRGVzY2VudCAtMjc1IC9DYXBIZWlnaHQgMAovWEhlaWdodCAwIC9JdGFsaWNBbmdsZSAwIC9TdGVtViAwIC9NYXhXaWR0aCAxMzA2ID4+CmVuZG9iagoyNCAwIG9iagpbIDAgNDcyIDQ3MiA0NzIgNDcyIDQ3MiA0NzIgNDcyIDQ3MiA0NzIgNDcyIDQ3MiA0NzIgMjM2IDQ3MiA0NzIgNDcyIDQ3Mgo0NzIgNDcyIDQ3MiA0NzIgNDcyIDQ3MiA0NzIgNDcyIDQ3MiA0NzIgNDcyIDQ3MiA0NzIgNDcyIDIzNiAyODQgNDE5IDcxMyA1OTgKOTI3IDY5NCAyNDIgMzM1IDMzNSA0NTAgNjAwIDI3MiAzOTkgMjcyIDM4MyA2MDAgNjAwIDYwMCA2MDAgNjAwIDYwMCA2MDAgNjAwCjYwMCA2MDAgMjkyIDI5MiA2MDAgNjAwIDYwMCA0NzcgODkxIDY0MSA2NTMgNjIxIDY3MSA1ODMgNTU5IDY5NSA3MDcgNDAwIDUxMAo2MzQgNTAxIDgxMiA3MDcgNzA4IDYwNiA3MDggNjQwIDU4MSA1NzIgNjc4IDYwOSA4OTEgNjEzIDU5MyA1ODAgMzE3IDM4MyAzMTcKNjAwIDU2NSA2MDAgNTM0IDU4MCA1MDMgNTgwIDU0OSAzMjQgNTI4IDU2OCAyNTAgMjUwIDUyNyAyNzIgODczIDU2OCA1NjAgNTgwCjU4MCAzNjcgNDg3IDM1MSA1NjggNDkyIDc2OCA1MDcgNDk5IDQ2NCAzNDMgMzE0IDM0MyA2MDAgNDcyIDYyNSA0NzIgMjc0IDQ4NQo0NzUgODAzIDU1MiA1NTIgNjAwIDEzMDYgNTgxIDMwNCA5ODUgNDcyIDU4MCA0NzIgNDcyIDI3MyAyNzMgNDc1IDQ3NCAzOTYKNTg4IDc4MCA2MDAgNjU4IDQ4NyAzMDQgOTMxIDQ3MiA0NjQgNTkzIDIzNiAyODQgNTE0IDU5NSA2MTIgNjA1IDMxNCA1ODYgNjAwCjc3NiAzOTkgNTEzIDYwMCAzOTkgNDc2IDYwMCA0NjggNjAwIDM0NiAzNDYgNjAwIDU3MyA2NTIgMzI2IDYwMCAzNTkgMzk4IDUxMwo4NDcgODcyIDgyNCA0NjcgNjQxIDY0MSA2NDEgNjQxIDY0MSA2NDEgOTA3IDYyMSA1ODMgNTgzIDU4MyA1ODMgNDAwIDQwMCA0MDAKNDAwIDY3NCA3MDcgNzA4IDcwOCA3MDggNzA4IDcwOCA2MDAgNzA4IDY3OCA2NzggNjc4IDY3OCA1OTMgNjA2IDY0MCA1MzQgNTM0CjUzNCA1MzQgNTM0IDUzNCA4NjQgNTAzIDU0OSA1NDkgNTQ5IDU0OSAyNTAgMjUwIDI1MCAyNTAgNTU1IDU2OCA1NjAgNTYwIDU2MAo1NjAgNTYwIDYwMCA1NjggNTY4IDU2OCA1NjggNTY4IDQ5OSA1ODAgNDk5IF0KZW5kb2JqCjI3IDAgb2JqCjw8IC9HIDI4IDAgUiAvSCAyOSAwIFIgL2JyYWNrZXRsZWZ0IDMwIDAgUiAvYnJhY2tldHJpZ2h0IDMxIDAgUiAvZSAzMiAwIFIKL2cgMzMgMCBSIC9uIDM0IDAgUiAvciAzNSAwIFIgL3NwYWNlIDM2IDAgUiAveSAzNyAwIFIgL3ogMzggMCBSID4+CmVuZG9iago0MyAwIG9iago8PCAvTGVuZ3RoIDMzMCAvRmlsdGVyIC9GbGF0ZURlY29kZSA+PgpzdHJlYW0KeJw9kktuxEAIRPc+BRcYqfn15zyORllM7r/No9vJwipkoCio7prSJLq81CWHSvYmX3rFVHEz+XmiITFN3A10cMp97SiCPwGug5k7Q7RSYlBvXaKyfGTs/PX19OXB+/J2GGyUniXm1adkrMGCPB1dfIA5t7b7X+Xn+r4y6clSrHRV9LnUi2eJ+hCzP6xOhd3YfWNbD8aTqQmaTdRq6pS1towuA32R0k1s9QJ0e1Tg3K6juIr2CRDBfYIOKhNq1diSkZBoi6xfnKcJ3RMH9hXQ/dImrmNbYtM2nvEVaQxBd8OROg4zxygD1eaGtaezTZaZ4kyuu2VxrBJolNZpqS3Bs+p1UcwZzEArhWiOVmMrQ7NDX2/D+0FmeNtRjEUtVXr2vLECw/rY7yn04HkYO4I3Mdkt6MdKViGDFpswdZaud/jYeWPt+xdE834qCmVuZHN0cmVhbQplbmRvYmoKNDQgMCBvYmoKPDwgL0xlbmd0aCAxODEgL0ZpbHRlciAvRmxhdGVEZWNvZGUgPj4Kc3RyZWFtCnicPZBLEgMhCET3nqKPID/R8ySVymJy/20aJ2ah/QQKG2wpOobzcjVkVzylFYYnPs37gmfiamr9R5IKmX1Th4zFM3mKExKKR5MxIO7YauuncTLCDLssJmZgroqvRC6oUALqUfJoZqPgaqaCvn3EVpn1FhcIRQImLGcr/p8D0+sWHQwWmO03y7M89grTdCzMe4Z5D0UjfgblWm5gZa2Dn4Ydmve2aCj/5Cd7Fni1d3t9AWR8QxMKZW5kc3RyZWFtCmVuZG9iago0NSAwIG9iago8PCAvTGVuZ3RoIDk1IC9GaWx0ZXIgL0ZsYXRlRGVjb2RlID4+CnN0cmVhbQp4nD2MQQ7AIAgE77xiP9AEERX/0zQ92P9fu0bbC0x2YUo3KA4rnFUVxRvOJB8+kr3DWseQoplHQ5zd3BYOS40Uq1gWFp5hEaS0Ncz4vChrYEop6mln9b+75XoB/58cLAplbmRzdHJlYW0KZW5kb2JqCjQxIDAgb2JqCjw8IC9UeXBlIC9Gb250IC9CYXNlRm9udCAvR0NXWERWK0RlamFWdVNhbnMtT2JsaXF1ZSAvRmlyc3RDaGFyIDAKL0xhc3RDaGFyIDI1NSAvRm9udERlc2NyaXB0b3IgNDAgMCBSIC9TdWJ0eXBlIC9UeXBlMwovTmFtZSAvR0NXWERWK0RlamFWdVNhbnMtT2JsaXF1ZSAvRm9udEJCb3ggWyAtMTAxNiAtMzUxIDE2NjAgMTA2OCBdCi9Gb250TWF0cml4IFsgMC4wMDEgMCAwIDAuMDAxIDAgMCBdIC9DaGFyUHJvY3MgNDIgMCBSCi9FbmNvZGluZyA8PCAvVHlwZSAvRW5jb2RpbmcgL0RpZmZlcmVuY2VzIFsgMTAxIC9lIDExNiAvdCAxMjAgL3ggXSA+PgovV2lkdGhzIDM5IDAgUiA+PgplbmRvYmoKNDAgMCBvYmoKPDwgL1R5cGUgL0ZvbnREZXNjcmlwdG9yIC9Gb250TmFtZSAvR0NXWERWK0RlamFWdVNhbnMtT2JsaXF1ZSAvRmxhZ3MgOTYKL0ZvbnRCQm94IFsgLTEwMTYgLTM1MSAxNjYwIDEwNjggXSAvQXNjZW50IDkyOSAvRGVzY2VudCAtMjM2IC9DYXBIZWlnaHQgMAovWEhlaWdodCAwIC9JdGFsaWNBbmdsZSAwIC9TdGVtViAwIC9NYXhXaWR0aCAxMzUwID4+CmVuZG9iagozOSAwIG9iagpbIDYwMCA2MDAgNjAwIDYwMCA2MDAgNjAwIDYwMCA2MDAgNjAwIDYwMCA2MDAgNjAwIDYwMCA2MDAgNjAwIDYwMCA2MDAgNjAwCjYwMCA2MDAgNjAwIDYwMCA2MDAgNjAwIDYwMCA2MDAgNjAwIDYwMCA2MDAgNjAwIDYwMCA2MDAgMzE4IDQwMSA0NjAgODM4IDYzNgo5NTAgNzgwIDI3NSAzOTAgMzkwIDUwMCA4MzggMzE4IDM2MSAzMTggMzM3IDYzNiA2MzYgNjM2IDYzNiA2MzYgNjM2IDYzNiA2MzYKNjM2IDYzNiAzMzcgMzM3IDgzOCA4MzggODM4IDUzMSAxMDAwIDY4NCA2ODYgNjk4IDc3MCA2MzIgNTc1IDc3NSA3NTIgMjk1CjI5NSA2NTYgNTU3IDg2MyA3NDggNzg3IDYwMyA3ODcgNjk1IDYzNSA2MTEgNzMyIDY4NCA5ODkgNjg1IDYxMSA2ODUgMzkwIDMzNwozOTAgODM4IDUwMCA1MDAgNjEzIDYzNSA1NTAgNjM1IDYxNSAzNTIgNjM1IDYzNCAyNzggMjc4IDU3OSAyNzggOTc0IDYzNCA2MTIKNjM1IDYzNSA0MTEgNTIxIDM5MiA2MzQgNTkyIDgxOCA1OTIgNTkyIDUyNSA2MzYgMzM3IDYzNiA4MzggNjAwIDYzNiA2MDAgMzE4CjM1MiA1MTggMTAwMCA1MDAgNTAwIDUwMCAxMzUwIDYzNSA0MDAgMTA3MCA2MDAgNjg1IDYwMCA2MDAgMzE4IDMxOCA1MTggNTE4CjU5MCA1MDAgMTAwMCA1MDAgMTAwMCA1MjEgNDAwIDEwMjggNjAwIDUyNSA2MTEgMzE4IDQwMSA2MzYgNjM2IDYzNiA2MzYgMzM3CjUwMCA1MDAgMTAwMCA0NzEgNjE3IDgzOCAzNjEgMTAwMCA1MDAgNTAwIDgzOCA0MDEgNDAxIDUwMCA2MzYgNjM2IDMxOCA1MDAKNDAxIDQ3MSA2MTcgOTY5IDk2OSA5NjkgNTMxIDY4NCA2ODQgNjg0IDY4NCA2ODQgNjg0IDk3NCA2OTggNjMyIDYzMiA2MzIgNjMyCjI5NSAyOTUgMjk1IDI5NSA3NzUgNzQ4IDc4NyA3ODcgNzg3IDc4NyA3ODcgODM4IDc4NyA3MzIgNzMyIDczMiA3MzIgNjExIDYwOAo2MzAgNjEzIDYxMyA2MTMgNjEzIDYxMyA2MTMgOTk1IDU1MCA2MTUgNjE1IDYxNSA2MTUgMjc4IDI3OCAyNzggMjc4IDYxMiA2MzQKNjEyIDYxMiA2MTIgNjEyIDYxMiA4MzggNjEyIDYzNCA2MzQgNjM0IDYzNCA1OTIgNjM1IDU5MiBdCmVuZG9iago0MiAwIG9iago8PCAvZSA0MyAwIFIgL3QgNDQgMCBSIC94IDQ1IDAgUiA+PgplbmRvYmoKNTAgMCBvYmoKPDwgL1R5cGUgL1hPYmplY3QgL1N1YnR5cGUgL0Zvcm0gL0JCb3ggWyAtMTAyMSAtNDYzIDE3OTQgMTIzMyBdCi9MZW5ndGggMjQ2IC9GaWx0ZXIgL0ZsYXRlRGVjb2RlID4+CnN0cmVhbQp4nEWRS27EMAxD9z6FjmDJ+tjnGaDoYub+2yGVpF0EEiyZj3TG8pDII59hh52JBSpOzVxCS15Dt4rXEc0pbrvrSueE3ZzCDfPTd0wVE6roXkJVzRByNA4mD/E9fof76tPP8GO9F8v6XuSjlDNbO62a1bXp7OiHG/THO5djqjADVZmJHDJff0TS6aSK0QHe4DHJRE5HxljY3kBP2hWrLit5jMZDBdMw6/XAGM9xYFPxDNBL9w6doXfoMmJp4L/j9D3C0NHiRhjFt86tWLBERi38grjqFZ6dVQo36JF3LtNUYQyqIlUD644+QaOXp2LAl/j5Ahu0YdQKZW5kc3RyZWFtCmVuZG9iago1MSAwIG9iago8PCAvVHlwZSAvWE9iamVjdCAvU3VidHlwZSAvRm9ybSAvQkJveCBbIC0xMDIxIC00NjMgMTc5NCAxMjMzIF0gL0xlbmd0aCA3NgovRmlsdGVyIC9GbGF0ZURlY29kZSA+PgpzdHJlYW0KeJxFzcENwCAMA8B/pvAIkNS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If set to true, sideband transitions with multiple subsystems changing excitation levels are included as well:" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": {}, + "outputs": [ + { + "data": { + "application/pdf": 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T4X1q1OUsGd4HDVuYzozhnX2Q8awCR1AhlStDo4HnOMQ++zCe41ym5IBvM4xPwVXhuPisjxSfuQODHT+sipYCvjKdmsuq22ngufx51VMM8NwhqE9v4Fmb5boVBzy2UdrjfBTx1MIIv32uHk+ItYfR9sTPLMTwqTssFEseK/BQwHdG8X0ltl6ceKguxuVUppp4IEu7OronflDyw7TZmniiDTl1qTssFHZwdG/h8YaI1vcSm2Ieny+pRN8ZQzkKQ1bp0jAPOWJ7qKvJEW4GbuKhh0GR2ZbmoMePCINXadlAD/tZ2ZTloId1hocXq8ceGJcGq5099p1tDEseDfaDz7Vzo7FniAzd5PpluCkhMb9msJ97NUJa9T2FvQinM/1WTb2wdJT68FYeu1WZuOmOeshpTAievFtPM5lGKr44xwaIIkvlGuo54RJ8cW56xtih4lpoYi1TO00fy1BPpYj1EUc9plzoF5yZeUgPxdSbee7i2MMPTT2nhsUYFnpZE/BuPTseGjPIjnmhmYLMuCI8X99qbc2n7rBOCBtaepXUHXuzpYSWi4Oek9hL3yfosUswB3llSE7QQ3NBu+dcrVu/FEpfhlUxzx4Gwb4mx/ygSQxl+Hw97T+muwJkxTyTZY3J2AvMz6MbnvnC9E4L3rHvcJlz2GvoivnBAmqqzSfv2DIEycnOs4ezxATPshGKea4lwpWzQH4ufZA9pj4xP9vlAzweF8inwFMpPXTPPD4p71KqmKcugGcwFmQaenZe9+h75SjWAxB1b+rZwABPOrt+OW4XYKtnvv0McPruMljo4dyF6qHvs46ShivJr3wJvPjmoKevLhRfBz25CZBl1z03+UPcehbLYxwBSE4O+rWNWL1kqOfq5/JY9D9hz5dXcCa+TAeVS7cye1svMzTJ4qN5jPeRV4fLy2MfKWODp5sM9hiGuxeiwx6QlhTqsPm7FBs2XUa1+bvEhFnIqXpbz9J5gZL13TfThqaVrDbc81dzKN7WNzokIqt3RnFPWYboTIHX3OP1eOqYvYMPpCnhzdt6ttYBtOq4J2hSYKNd0p5KMZE5l8BLEY/C0y3O1nORE4ediz/PXDVZiWDNPcZzwAN1yz1Wv7LU5bnnx4Z9mor7FBOeJOwug+a+zdDNUw9TGUM7q9NBkiFeeVXgFfUDsgVCzzJ4EK7GXswz6hHpw1VZXSua+spuuFzOqGcTCBbQO/jCpNk4c/DnZuGDW7LUU7l2FkZctx3HEf3suJ6oX3tYmuud5eLzXMVw1PP1jco1Weq5+GxPiC5pTyUNCMaU/ZennqktbJ1rok2ZXXSsI1nqES/TTHfr4ScQmiEY2VM/VyouT/5E/VKnYc/tKeq5cczCN0f9mK9v1TXd0aeTvjpFNPTkGeGva7qDa49FhBKKnnlIQpIcna2nqxJD3X0SzTyzIJCL6JinRgRY3fXjTAXKQmh0zK9Fq9nb+rXG3TfecUuwUynY6jxfHqBAo+vHATBYNMQbZ8wTrLJTfGKeKhrRe4vOwedmwQ/e64yKeqjuyEqga61dqpsRraOeWeGKd/Jh/TxSCGE4s/XMuYaz/loGEPS0zqrzdCFHKeKq85NivP/u+J+oj0zGgl1XqeM29r5WX0PPlKvstXwFfSrUoG2l/RT0PASDaEZc4p6rDwUdZw1ZQz97F2rOr2PqM0s01DCWecgUI2DbZwv9x3ctwebtU8Lb1bi7zpZ5egCueX6KHfYiu0xeYjNcWFUhgzyD67QKJRr5zuT03mXmmIf5X56bg56NOmc9eEyGJdmDdA19gwBCvFwP/bKs4t37xBJY9Hl7wtliXn6hJj7P0vzq2DPEcz8Z/5wTTyUcbWl+V9npjPj18rMOPP4msFtOkyG+zSqjb7alYQIQK1OuiKcmyPIYup+Ip6LMiMaGT+TRy4ZMVN+BR7HPsYpP5OEtMcs9tlbEz3ZpPqQnvtNc1O6Jx/wlQE94O09FnIu4dhwsJFtxV9pVEQ+yK4R+pfc08VNtJ+/c72q7VNeOQ06AQHKJ++kRS1iy8PLAFzYC8pYBS3zhlQJhJUsU8cyENbYrWOIxLbol3YX0mRCwg9QTL0x+7Dl3RTxVXSbDDnnhBGSdjtXID9jhnPdzNxp5/Ihopbtzbszo4Mc2CzcaeUogRqOr1sHI8FB4nW6eQZ4gsjLtoYeY5rF61DX1wDJLb9379phyYX3EU1/q6RSspp4dNrCuxVE/611YoDPqKSK1Vpe+3+UxV2/n2YvYQ19tvZp6plTi6tNw1LMkWp2d57LBOrfVQ3iintqAq7+0kKae7hd0uq/Pw18IVAY+fQ9/AWHnnnY/UT/TnCzeuph+Rp5kwcX00w9qwCo77PGrjacHisWeXlaKebiC3VS6EN/kjtPw9dz/4Q391PV1RYyae2wodESpr2PoK3tv+GSWe9bFR1gdIJp7lijqyqkq7plILzVF22w/3YUafBMe8eitrSY5TT2bPPnglvo0T3wkf56G0GdgHn3yvs3062pu1NDz/BcbC91JuZnRYW3SHaqZ3h+C2egDenYApBG7hx4CxZp1dDW7VLjWZT8Xp6CvgZelLA9AMV+Z/oR4eUuPlefBPZ/Hm8yXdUbPMC9YzNXnaJBPDPOHz90vk4Xpugr9is/a6rrUyEemrUfxAT3HgVkOrkSP52FNKgffkiOQCrbM+CY8avoBZHzunll0/H5whn5GXOyTdofn6JTzRpalOhTymXccpL3BViPPgxplNREq5NklJ3vaQREPqev0C1xPztyHnJs/XLO7XzV74qe7BqfndZL3eKwxeHLNEd/YFNxcxY5CUluXKWCaeJk9EcX23VIR4IGDS97zASE4qw/cIY/wVlyNnoZDaunic/fC3qgqxefu19HEVT1UxOPlMNrV1+iZekP8uc4PGOL5TAxBPPGJZyGWd6mJxxpgZsFn7ivv8BhraQzwq/0sumrdwnA/36GJr5V2IHcXzdd5wGN014SXapm9le6IOz8VeK2zn5p4+hC5lOxSeLRKcJmSO1uTwFrhEVd3tobAQzsE33XL5whsn3KePde+88CBz+Bh/fo89myBpy2f6s3F8lggsAyJ9jYerjrPyuTugWefhaw0rwa+8v1Ldk05dHsbbw46I56eY11tnZp4VpVo+l25jrKAP+Jr9OSk9JXReHngWYaOJXjXnhe4wO9xbbfz4zqDOwv8zKSl6kr01Bp4jiw+mGf+AAAPV66j7Yc63oN/jXxmLHVWrYPkcAeLP14z5nHHVW4xyENMCwyHy+BNY45VLT6YT7OvrnZ3vIZmFe+znx60yAtvfPJGvmH6cawMoWae1YjWxmpdVcy3Dm7pdjjmIWodLlN1nv3s3uWhcc883oaXEblGPIojgrB1Sl0zzxhvP9BvmOfR/dUeY5jnJVmy/DfNPLatpb29ViEPOiM0U3M2fma94Ul5t35fpu6D+TRPCoeV9dTI86haDutgiEGeUoTHjQ55MIbtX63fHvkORWE77RMrhHXPFWvk2zxXsEcNGnl2H9dYvFvP9V7Ouwa+zpsN+isF84OBoyRfn2eWHPZ2uEId27hGbs0TLzxElR3vmCv8Ht+Sw6fmCenqEvaYAiQxrnOHhnee+Ov7+TUNPJuaeNzRAc/yWnosD2rgx+wVjS6Un0IXKC4OeKy1sDLjbfw8B9fPnPrZWlpWmdnwPnhUZg9hFe+QD7a6FO/V95npWApf844gRqCDm+Odt6EF2fNrivd5CUhfKVLNO7ceW+zTd5X1iVzOcMcas13f1eZXkrHklWTUvHNPoE18HA/9gBXe9YMFnt3EzqenyQ59VRI17vNEZFnPpHGnULCW4XN3fCjeLejacTjO7rlVate4zy6m2j3uPERc8jnubOKX6l16NiXFWoo7V8OVxzpI8Mm7ylY0eByvU6JjJiT5G6kgMRs3RJxHD9s5r/1wuTuKKMjOLoanpPdVdXC88yRFdC14DIlGjDW4sjyVd0dA6ttuV2+QhOYNvPDMBI9Ped7ZTCb7eT/FO23V3rCnaGcCLUANuK5b6nRenhJ9Ub7xHpF1JEPTjs0XWKSzmvxgPFLWDSCadt6+g3D3rD43Zg0/NleTH1gOaAF/Z1XihHkfh3fpG1uVaME87uwCTqn5IJ7OjJQ9kNC8d7at1ujabqkjO/v4zngfWG5sljfwqfGIlaxOdQX81AN13c9jiGfrA7xid66GsiMh7U60Jp538fSe3enZuQ55T5Vo4jke9jZmRXznkSbpyffiYJlLaz16A9+ZaxgrQ6OR76AcIXF2vTjUKNJa/K5OPRTMJJ5lb5hHTPkQoF/jbOrnLZ/UAvPf2vFXnxx/up3up9vpfrqd7j27ne6R4cQ/k2Fab3CMIG2RXG+y+0O43+ra1Td3X4Vx7+U3P91y9f1dfXPloquXvvrmx3DX1aMOiGM35AL+864K4pHJh7Kb8tu64D06LH/l7OyVYzXXWm2vdd1d6bS9dqrm6tnZH9NR+e/rKN21s7PXDtXc219/9VDNtbOz/0Bn5Z+8gbb/1+kJSAud3kBhdL8H96HcVAUv23h/ZzveleYck8G/mIh7eFZ5/XIb3b2ds3+vbvk7O2evddTcKK9frrZdLq9fTb3fG5nb1PuFfrmHd2iQvbsr/nqD7Lv0yz3SOnT8XR+9+MqUHANxer7xtuG+cX3l+32b3ZXbK7+XO2rft6srv5977F74Tqur99hdvrnyyj21d95DfeWe2he+tvLeK+xe5j6rJ5ONheFB1pqhBDqwnn+dJjs+GvDbJvuHcC7+u5yRvXQu/lmXYVy49OLhZS69eNnT7/cehL3zSNzVg7B33nlx9ZKbK5da2TsvLt1t8fAud1vcfc79ZQ68PvLdtEse9xx7mGm78oj+bb7foy4601Nzsbb28Lza2pXmGdMvd7ET9uFFOmH/Pn1xV3pk7i2imaL5xQa4h3freDUNcJc6Wx/epbP13j63l2h6eYRVHhPpkRWxJ3KPNKVP7vlNWN+nI6z3Hly/djHV1Zsnr9wwfe3myTsvqbl6YcW1g+vf4RDr93Gk7erhljs73a8cabt6iPXahRXXLp/8vq6YvvOWmmsXVlw7un7vmbYXanV/KpLvpfBK+93Do09OlVATJga35ZJKuNyp8nCl5fThWedKrh0av3aY7N6W02staO/UlHKxi+vhWaexrp26vnrXgjmDeak98+E5/Vq6e2MXnNko9fRN1narL36P9qUvx8Z7Pfs7t/FafnP2eafG8UanxgHSAFxYxXqkgu/PL8mwg388wBE8H8SHhvmg/Nrub/kt4fxZf/8iNoaFrLq+shLL9fiFiWGWofr+lbTx8dtr1zfS8vPxX5gnFdY34P7T/g244BOKATqm7P/wXX8jzoocv+MMm/6O73X/b1z8zl02KyEmpSHsj8tz/sW5n3/zzZ+//earL//wt8fvz71e3j/eLu+r7eeR/87jqGb/n0aNAKjRuyQgzobE/qMXgfiyInCq7h6fX91VohD4/RrRCsI+ZsTgaewuIZg5jfhjF4H0wlpARyLPLuudZIA3WGQ4olYdnEa1HOjReySBV7cyVP7Rq4P8srIwtCvw7KKRkoWOSIR9ykYUHgeNJJwG7xIEeKCNtw++x3IQ/wE8g6e6wfGOuoGSA2xYwxycIDyNGklQo3eJQk1sa3i/XYTXkIUXdhGatg/PzjErWSiQmtqsJOxjRg6exu6SAkTiAXHnj1wGXthHOKUuj3ekLpUM4Cf2bzh98DRq5ECN3iUJ88x0er99hPTDtw2nnNXxjpyVkoXA+/Rc9uBp0EjCafAuQWBDbHy/swevIQcvYBc+Pfw/YjGaHAplbmRzdHJlYW0KZW5kb2JqCjEyIDAgb2JqCjc2OTkKZW5kb2JqCjEwIDAgb2JqClsgXQplbmRvYmoKMTcgMCBvYmoKPDwgL0xlbmd0aCAxNjcgL0ZpbHRlciAvRmxhdGVEZWNvZGUgPj4Kc3RyZWFtCnicNVA7sgMhDOs5hS7AjGUw4PPsm0yKzf3b2M7bBn+EhIS6QDAcnWNDecAY/tg4rdpP4/LqeBJUqAiogqspFZQfzVlls/YHZrir0WSkPsG41OeOG9wD/QTbJBEtwbJwtcfM3VaBhn3Q3eCKvi3ZstDjATLqSPIMtQeY8AHFCXzGbi9oSGiGjNNSIGoYvbOGpZDPFP7EomgFzamC/3/F1d7t9QWAxzgvCmVuZHN0cmVhbQplbmRvYmoKMTggMCBvYmoKPDwgL0xlbmd0aCAzNzYgL0ZpbHRlciAvRmxhdGVEZWNvZGUgPj4Kc3RyZWFtCnicRZJJbgUxCET3fQou8CUzeThPoiiLn/tv86A7ysICMRRF4TmGDJkhL1XJCJlny6deObZMcj+Xntt7X7qHeHp76887KT6X2HDxdcTUxM+Qj8tsSAwVcyzgFoY9laEzjJ45JdzFtmJXZUCLUHGlAjLut/24fD4RsMMPSPRaocWDGywRg7dhsieZHNbcUmFLb9oGueakbzGQamGbj7XuwdODFFRoHnqWqNc+yURFh+QtaLJsFrNI0CHnKmAH2dl8j7yQxm9la7GyrMgiHfEpr9V6vSque0uKIonCIOBXMDW6mBBL7fGzwqyHZivkrLqdIhe1Qe/adRSIacWZpdW3sDF6iokigx4iypDBTO1zQV6fcx3UiJT7jMizU2wtQVg7bdgPViX06mo/wLayUezrPlZktK314u1Z/Zn26p7U2tN936XgnO5C99QeV7Zo3J4FQ+FmdotLZpAx66s5q2j9wvOo5OOUHohc//p9f+t/r7/19/X1C/Lrj7gKZW5kc3RyZWFtCmVuZG9iagoxOSAwIG9iago8PCAvTGVuZ3RoIDg4IC9GaWx0ZXIgL0ZsYXRlRGVjb2RlID4+CnN0cmVhbQp4nE2Nyw2AQAhE71RBCbB8hH6M8bD2fxU2Rr0wb0LyxomQUK2OuaFn4M4QUf3qSMUJI/QDZ2/a/CFmRVUpKouR9XPIMk2QtB8tR8+8QJVrbMIJxw14WBthCmVuZHN0cmVhbQplbmRvYmoKMjAgMCBvYmoKPDwgL0xlbmd0aCAxMzQgL0ZpbHRlciAvRmxhdGVEZWNvZGUgPj4Kc3RyZWFtCnicNU85DsMwDNv9Cn6ggCgntvyeFEGH9P9rRKUdYgkUr/gyGKbjRcIZYF94s3HbC/o2utVGS9KG5AeONgNeuj707kOYYxKXZrKSQRvayJVX6dnzS51ClKCZl7EeJKIYbn+N08tExdJIIxOEhyKvWrruUpVQ5WSUVeVbzX//crRPO2/K6SxLCmVuZHN0cmVhbQplbmRvYmoKMjEgMCBvYmoKPDwgL0xlbmd0aCA4MCAvRmlsdGVyIC9GbGF0ZURlY29kZSA+PgpzdHJlYW0KeJxNjcEJwDAMA/+awiPYiaM0+5TSh7P/tw6kpR9xCHSiqqiwZrRK4TjkNFi3LCa8uFCbBIz6I+9MytUHaxh4FZvSHShjPcR2Bm5cDxg+FogKZW5kc3RyZWFtCmVuZG9iagoyMiAwIG9iago8PCAvTGVuZ3RoIDUyMSAvRmlsdGVyIC9GbGF0ZURlY29kZSA+PgpzdHJlYW0KeJw9lEkO3EAMA+9+hT4wgJZe3O9JEOQw+f81RdnJYSC5F4ki2bPcza3SPhE2022H28+4cqUNlv5c5bOzqm2DAzVvG3Xbj6s22VxW97Fxe8fpRzvKYtn3ycZttYk7uU28+0wdW87tSFsxLamm+OPKMZ4VKizfFqdsnmQnlqqwMt0mnaOGzXJ2VPZMGnJiMcIdtnIaS6vULZzqsyyS2mtaDLru2TXd1s0KE6wzLL1su2omBTYIc0bTkvcTwR7VWYFUJ4rJ1hEnw1XFYYo+4kezLGEfi2wsGzCxEi4PEF0IpiecMCMYJ+x2fKby98sHDFPtcG9rZ6jHzOZ9FFUXu9l94GW4OqOZzjNFNeMDbUo6wWXt8f56HmVL9NVRFigurehamlIoh1TsToVf2EGHin9Y8ixQEqUz3XOqozyQ8C9jZeyO0Up2Rp8ZAxU1e5o0eqpBxthl8iDcQyHLeSw1mTQENiAEHBk/8M9NGTh3dES7eleY+YNhEPgTr9poza4aR9eUO+RetaWdHKTFOeUiGkAiDyRCDQNfBrp+r0iQLKFnj2tyVDxeQ5dA4YCpYOrAZ9HvIm6+XKjCZDU2TzsNBkAoo4FBU9z12oykcA1PoAD2gCisI9KaDJGk+NqP6y4hO2sL0A5z1NoYeDdn1OJMyQ56Zghf/fCCs8q+nenRf///EXyv39evv39cxsgKZW5kc3RyZWFtCmVuZG9iagoyMyAwIG9iago8PCAvTGVuZ3RoIDMxNiAvRmlsdGVyIC9GbGF0ZURlY29kZSA+PgpzdHJlYW0KeJw9UjluBDEM6+cVfIJ12+/ZIEix+X8b0gukGQkSLZHU9FpYqNEnDWMLX/YoXfh9WvW3gq3NxM9CrGEWXog4iHJEM44hzsbrCWLSB8nJWfsTWXs9ymoFX98sBrEPquNOqB16nQe9ONMNbQ7fc+Pr8f5kXouIA49m1Bt3R52Bs1rcZEfTtNH2pjZWhhVysSEyS50uMjBYk4lRXzW5aQ+9qLyqk9wck5eaeNxtHN4eMCt0OiwYS8KtEk20DaG7SSfQpy/Bg1kF5zI57KwqUm58PA+aMCtpIWWflFnGPTuR3NG0J5udMnUorSNoKjebkTalbO0pcioJctkbn3hJK8thl4ikxcUjpsuIPDqRITkhhrkOSQ/YKZ2YeB1K72iTXz0hs0d4aiI2KniOuYYfEPK+f9B/Ijd/nu8/Q3t0GwplbmRzdHJlYW0KZW5kb2JqCjI0IDAgb2JqCjw8IC9MZW5ndGggMzYwIC9GaWx0ZXIgL0ZsYXRlRGVjb2RlID4+CnN0cmVhbQp4nDVROW5FMQjs3ym4QCSzGp/nR1GK5P5tZvBPBcIwm2stWRJbPlQl02Xrkk99HHOOfh/Lms70yIeL9hZ1eT2aKXZErSVNdLU0x3zG+8YoVQrlFMZYsRgiO8ricTBGEysJEKDBdi7FGNcZJcDKjsEuTXKCrCKF3FVnxFTzheo2bqmWFqif9fV430nkktotAf6Llg6avLajfOqVxc4curChEMKbcUcQA3rfTP5Tej3fkxjE/j5uwcYDpcVL5TR1gJtO/ADTYHghzKDCQF6aUGYqug9qgST44qBDyOHQk/vW7nmBZrj6uR2jxW5Uz3WcEQu8VEyAn9xY9DhaoCF3CTVlnxGZh86puhYmMFEa45AVCWOfnTF7bJj3+8bIAxRbe1D17DePIicyK3mgRHe8tSl+j2q19qifOv/Fjh5/bgfX3GUKvL65EI9JEZ/JkfFmSQ1Ml5qYNlVO/JQNVLroa6tj/u3rDwH7j2MKZW5kc3RyZWFtCmVuZG9iagoxNSAwIG9iago8PCAvVHlwZSAvRm9udCAvQmFzZUZvbnQgL1RBUElCQitJQk1QbGV4U2Fucy1NZWRpdW0gL0ZpcnN0Q2hhciAwCi9MYXN0Q2hhciAyNTUgL0ZvbnREZXNjcmlwdG9yIDE0IDAgUiAvU3VidHlwZSAvVHlwZTMKL05hbWUgL1RBUElCQitJQk1QbGV4U2Fucy1NZWRpdW0gL0ZvbnRCQm94IFsgLTI4MCAtMjU4IDEyODAgMTEzMiBdCi9Gb250TWF0cml4IFsgMC4wMDEgMCAwIDAuMDAxIDAgMCBdIC9DaGFyUHJvY3MgMTYgMCBSCi9FbmNvZGluZyA8PCAvVHlwZSAvRW5jb2RpbmcKL0RpZmZlcmVuY2VzIFsgNDQgL2NvbW1hIDQ2IC9wZXJpb2QgNDggL3plcm8gL29uZSAvdHdvIC90aHJlZSA1MyAvZml2ZSA1NSAvc2V2ZW4gXQo+PgovV2lkdGhzIDEzIDAgUiA+PgplbmRvYmoKMTQgMCBvYmoKPDwgL1R5cGUgL0ZvbnREZXNjcmlwdG9yIC9Gb250TmFtZSAvVEFQSUJCK0lCTVBsZXhTYW5zLU1lZGl1bSAvRmxhZ3MgMzIKL0ZvbnRCQm94IFsgLTI4MCAtMjU4IDEyODAgMTEzMiBdIC9Bc2NlbnQgMTAyNSAvRGVzY2VudCAtMjc1IC9DYXBIZWlnaHQgMAovWEhlaWdodCAwIC9JdGFsaWNBbmdsZSAwIC9TdGVtViAwIC9NYXhXaWR0aCAxMzM5ID4+CmVuZG9iagoxMyAwIG9iagpbIDAgNDcyIDQ3MiA0NzIgNDcyIDQ3MiA0NzIgNDcyIDQ3MiA0NzIgNDcyIDQ3MiA0NzIgMjM2IDQ3MiA0NzIgNDcyIDQ3Mgo0NzIgNDcyIDQ3MiA0NzIgNDcyIDQ3MiA0NzIgNDcyIDQ3MiA0NzIgNDcyIDQ3MiA0NzIgNDcyIDIzNiAyOTggNDUxIDY3OCA1OTkKOTQ3IDcwNyAyNTMgMzM2IDMzNiA1MTQgNjAwIDI5MCA0MDEgMjkwIDQxNyA2MDAgNjAwIDYwMCA2MDAgNjAwIDYwMCA2MDAgNjAwCjYwMCA2MDAgMzEwIDMxMCA2MDAgNjAwIDYwMCA0ODcgODk2IDY2MiA2NTkgNjM0IDY4MyA1OTMgNTcwIDcwNSA3MTQgNDE2IDUzMQo2NjAgNTEzIDgxNCA3MTQgNzEyIDYyNyA3MTIgNjU1IDU5OCA1NzcgNjg2IDYyOCA5MjYgNjM5IDYxNyA1OTEgMzI1IDQxNyAzMjUKNjAwIDU2MSA2MDAgNTQ5IDU5MiA1MTAgNTkyIDU1NiAzNDAgNTM3IDU4MCAyNjUgMjY1IDU0NyAyODUgODgyIDU4MCA1NjQgNTkyCjU5MiAzODMgNDk0IDM2NSA1ODAgNTEyIDc5OSA1MzAgNTE0IDQ4NyAzNTQgMzUzIDM1NiA2MDAgNDcyIDYyNyA0NzIgMjg2IDQ4NAo1MDIgODQ2IDU0MCA1NDggNjAwIDEzMzkgNTk4IDMwOSA5OTAgNDcyIDU5MSA0NzIgNDcyIDI4NCAyODQgNTAxIDUwMCA0MTAKNTg4IDc4MCA2MDAgNjI5IDQ5NCAzMDkgOTIxIDQ3MiA0ODcgNjE3IDIzNiAyOTggNTI5IDU4OSA2MjAgNjIyIDM1MyA1NzcgNjAwCjc4MiA0MjAgNTMyIDYwMCA0MDEgNDcyIDYwMCA0NzAgNjAwIDM0NiAzNDUgNjAwIDU4NSA2NjMgMzU2IDYwMCAzNTMgNDE0IDUzMgo4NDcgODUwIDgyOSA0NzkgNjYyIDY2MiA2NjIgNjYyIDY2MiA2NjIgOTMzIDYzNCA1OTMgNTkzIDU5MyA1OTMgNDE2IDQxNiA0MTYKNDE2IDY4NyA3MTQgNzEyIDcxMiA3MTIgNzEyIDcxMiA2MDAgNzEyIDY4NiA2ODYgNjg2IDY4NiA2MTcgNjI3IDY2MiA1NDkgNTQ5CjU0OSA1NDkgNTQ5IDU0OSA4NjUgNTEwIDU1NiA1NTYgNTU2IDU1NiAyNjUgMjY1IDI2NSAyNjUgNTc0IDU4MCA1NjQgNTY0IDU2NAo1NjQgNTY0IDYwMCA1NzAgNTgwIDU4MCA1ODAgNTgwIDUxNCA1OTIgNTE0IF0KZW5kb2JqCjE2IDAgb2JqCjw8IC9jb21tYSAxNyAwIFIgL2ZpdmUgMTggMCBSIC9vbmUgMTkgMCBSIC9wZXJpb2QgMjAgMCBSIC9zZXZlbiAyMSAwIFIKL3RocmVlIDIyIDAgUiAvdHdvIDIzIDAgUiAvemVybyAyNCAwIFIgPj4KZW5kb2JqCjI5IDAgb2JqCjw8IC9MZW5ndGggMzgzIC9GaWx0ZXIgL0ZsYXRlRGVjb2RlID4+CnN0cmVhbQp4nEWSS26kMQiE9/8puEAk87R9nh5FWWTuv50PWppeWCBsiqrCdVOW5JEvVSlz2brkjz4ZKbpM/pLZZL9PuktdSTWhFvuIqbyeiAAilg6Gxxvr9fjKyaxKvlzMl9D5evSG2BatkKTkV87qsroowy8BjH1FSV9PJa2nKdodph6XMkmsLdxGzutc/ZqWpLvB8tSgl1bD87KCyi2pvcBEzOkbQ9NGoDO81XvmRJTpnix4X/S18qrT0zNAWzOjGFwLArn7pquabZchMA1i/U4l6KwhGU4Xt35h5zkTO+IZ1c6sWdrFJ7aiPdFYSCHY2FFeE8Pd3OPn2TNHNzeG9vKZyU063G38DHhNXONGtJ0Oy8lwsN+a1XTr7YmNpyhvfMW5nqg2jsFBwTGq7MR4uHsn1npYkLUscU61XAeAJPCIrxCuMryDifyhJngIHF39b3LFe3+4r0Blf5YY1735oTYUjmuizXYnO+16D/tknpes//UnW72byP/x/bl/nu9/dHKRdgplbmRzdHJlYW0KZW5kb2JqCjMwIDAgb2JqCjw8IC9MZW5ndGggODAgL0ZpbHRlciAvRmxhdGVEZWNvZGUgPj4Kc3RyZWFtCnicMzcwVzBQsDQGEmaGJgpmlhYKKYZcpsYGCsaGZgq5XIbm5mBWDphlAKTBasEUSDFEHMEytgRJgvXDWRBZmPEQFkwOrhpsRwZXGgDimxwHCmVuZHN0cmVhbQplbmRvYmoKMzEgMCBvYmoKPDwgL0xlbmd0aCA3MSAvRmlsdGVyIC9GbGF0ZURlY29kZSA+PgpzdHJlYW0KeJwzNjRXMFCwNFbQNTQ2VzAyNVcwNzNQSDHkggnlglggsRwumCyEZWZpDmQZmhkhsXTNTaCySCyQKTlw83K4MrjSADbVFtUKZW5kc3RyZWFtCmVuZG9iagozMiAwIG9iago8PCAvTGVuZ3RoIDY4IC9GaWx0ZXIgL0ZsYXRlRGVjb2RlID4+CnN0cmVhbQp4nDM2NFcwUDAzUNA1NDZXMDIyUTAHclIMuWDMXDALLJvDBVMHYZmbABmGpqZILDNLqCScATIjB25aDlcGVxoA+kQWRgplbmRzdHJlYW0KZW5kb2JqCjMzIDAgb2JqCjw8IC9MZW5ndGggMzcxIC9GaWx0ZXIgL0ZsYXRlRGVjb2RlID4+CnN0cmVhbQp4nE1SS24FMQjbzym4QCU+hiTneVXVRXv/bQ0zVbuIQCQY2yFxRAVL3swk1SV9y7tdvs6Uvi9HTOY8bym2Q5a8LkvmRyxUYomZShnLR2WnLLASUiGGYjVdjIAc41YTcrPcydkcKRHZr6MOy+wGmRAKRG9oJHpkNNMtPRqnhkpqdzS3dHIk1xbQ7Du+rrC7EsC8iOVPT5wzKHAfVIAxmy2oBEESi7e6BLvY16L7fVBRGxXmE32Nws5iyxdZ2v/M8GR2aAJRbTEHD2VTE6gn6BMNMVv3rUbfbMg+4qpCdk6vl7ZUQhdnlQpbnI/y1lmdBOhjjo/bRmRIayRXM2p0uoZRQu9Mi9xQ1cgADx3Q5KzurF6M8HszftfhdX3OarRFXI1ckzk3ALmGJDAforSwRXIZ0OJpO+zeG77RXowjsZsOray5oTkxdtjMnUg6r9vI05aCMv+y4Ec+Wa8EUeP0F1OozRdnkMUimt48H+at4uMHBvKNqAplbmRzdHJlYW0KZW5kb2JqCjM0IDAgb2JqCjw8IC9MZW5ndGggNjE0IC9GaWx0ZXIgL0ZsYXRlRGVjb2RlID4+CnN0cmVhbQp4nE2USY4cMQwE7/0KfqABcdFS72nD8GHm/1dHUh7Al2JCErdksmYcG1Zp73C3GcPmWfbLX4Lvuez7Ih+P1fMA6ljNDdhpn1f5BD7Hcv6LEXtc8Hn5eS70dMAY9iw5Hu6WghJfqT2q7SlFzM47uc+y1eE53oRKo4JtHtNIS3xALPt6PfgP48kqfZ9zHRT38J6QPgqf3U7DfFNThfnBroOVR6MniOe5LcYy97SIrbJjzhs0Thju6dWGOjkG7GV7Usawg4ngWGUVece2WtHlVDfv5bDJzYJz5cFldksBzzPImpwwm1jXfl45vFHCygwSrsS3b4R8U3cjas+1bTKQ3Ni19IapTqovRQEXOWQ/rznuzL8ucqEa8R+qk0LwVsQtKqvCltpUzTXVd3IrGs61zUsjdc1Ak+jyi2agxLDGz22AC44iJJp8BtxPIjGnhx7q8sMNpDo0x8P8d8DNagtr9dyT1AvYc930tNGCbpweHC598XKqb6dqL6mDFzmvbak1oh+9oACnkKsP9Mnwg6szWhdHTWY2EFcuoCbF025xi2CCP3bXqOxnsT6vPy9x+EYZ3xdJFQR7h5hlY7w3bGgFmlhISX0lVcbZQi1705EftiOuXdqiRkzVQxsnid1Fi3ZWJSnZ90LDaI4LJLO6EDXBQ8M88k2pRyd36KR7O7vdlT/DfnpRX5pMpH4emrpQwlawCykFrKZtSQurNZqorG12CUJ08XWRfi7iM7K9K5/WAoj5tKp4q4zVnUsDfQJveiHtXB/NX1E0V0Vte9kSSvXciGr0VtXJ+9areOpA8dXRT4/q9/dfrHr6xgplbmRzdHJlYW0KZW5kb2JqCjM1IDAgb2JqCjw8IC9MZW5ndGggMTc4IC9GaWx0ZXIgL0ZsYXRlRGVjb2RlID4+CnN0cmVhbQp4nE2QOxKCMQiE+5yCI/BYEnKe33Es9P6tQHS0yQdsAkt8BjGF54EIcg26yej8VXCZ9Bwy/yOYdrS/UQhhCsnOSoBUlZyVrqGod5t0zW5t4s1r2DzDIJw3cjiyR966BpZmpm3Hth2alBLl9TnAP5qsTwTeZOXJJ+mWZjpYfipeSnoDklyKZgWp5F4AkzJ6n2vIzukKkkiKkVQPLgeSri021S/YwqFHK96e4uAx7m8ZDUEpCmVuZHN0cmVhbQplbmRvYmoKMzYgMCBvYmoKPDwgL0xlbmd0aCAxMjQgL0ZpbHRlciAvRmxhdGVEZWNvZGUgPj4Kc3RyZWFtCnicTY7LDcMwDEPvnoIj6GvZ87gockj3v1ZWkqIX8dkCSWkPEIbnUCc4d7y41fuzZX+cjfs/mfCmoB9NmDl4dljmieRmBFYTMzh1SET5lWfpak/ZWWRaRHqT+CwS2W2ZSAxjTh9nks7syjs07NJMWHUZpXdccrT3F9saKZkKZW5kc3RyZWFtCmVuZG9iagozNyAwIG9iago8PCAvTGVuZ3RoIDE4IC9GaWx0ZXIgL0ZsYXRlRGVjb2RlID4+CnN0cmVhbQp4nDMyNlMwgMMUQ640AB3WA1EKZW5kc3RyZWFtCmVuZG9iagozOCAwIG9iago8PCAvTGVuZ3RoIDE0MyAvRmlsdGVyIC9GbGF0ZURlY29kZSA+PgpzdHJlYW0KeJw1zzsOAzEIBNCeU3CBSB6MP5xnoyjF5v5tBnvdPTE2H4/Qohj6AuXTtKHrG+KlLv7kFG+xBr5DJL2R1dVqED6ISrShl5hlv84aMhydyJ9sxLBYcioia2GcPhONIXq2jaHw2CuhYuOSKFv3lqUwcGhY+So+C8eBGTR778Un1jHlAcfv7Nx8y1c+fzOQNWMKZW5kc3RyZWFtCmVuZG9iagozOSAwIG9iago8PCAvTGVuZ3RoIDc3IC9GaWx0ZXIgL0ZsYXRlRGVjb2RlID4+CnN0cmVhbQp4nE3MsRHAMAgDwJ4pNIIxMl4ol0vh7N8GuUjSoIfjxCQaImowHMMTh9veb0VOLIueILPE/kG/QvzEIXknZtOpKl8od/Gyy84HaBEXEwplbmRzdHJlYW0KZW5kb2JqCjI3IDAgb2JqCjw8IC9UeXBlIC9Gb250IC9CYXNlRm9udCAvVEFQSUJCK0lCTVBsZXhTYW5zLVJlZ3VsYXIgL0ZpcnN0Q2hhciAwCi9MYXN0Q2hhciAyNTUgL0ZvbnREZXNjcmlwdG9yIDI2IDAgUiAvU3VidHlwZSAvVHlwZTMKL05hbWUgL1RBUElCQitJQk1QbGV4U2Fucy1SZWd1bGFyIC9Gb250QkJveCBbIC0yNjAgLTI0NSAxMjQxIDExMTkgXQovRm9udE1hdHJpeCBbIDAuMDAxIDAgMCAwLjAwMSAwIDAgXSAvQ2hhclByb2NzIDI4IDAgUgovRW5jb2RpbmcgPDwgL1R5cGUgL0VuY29kaW5nCi9EaWZmZXJlbmNlcyBbIDMyIC9zcGFjZSA3MSAvRyAvSCA5MSAvYnJhY2tldGxlZnQgOTMgL2JyYWNrZXRyaWdodCAxMDEgL2UgMTAzIC9nIDExMCAvbgoxMTQgL3IgMTIxIC95IC96IF0KPj4KL1dpZHRocyAyNSAwIFIgPj4KZW5kb2JqCjI2IDAgb2JqCjw8IC9UeXBlIC9Gb250RGVzY3JpcHRvciAvRm9udE5hbWUgL1RBUElCQitJQk1QbGV4U2Fucy1SZWd1bGFyIC9GbGFncyAzMgovRm9udEJCb3ggWyAtMjYwIC0yNDUgMTI0MSAxMTE5IF0gL0FzY2VudCAxMDI1IC9EZXNjZW50IC0yNzUgL0NhcEhlaWdodCAwCi9YSGVpZ2h0IDAgL0l0YWxpY0FuZ2xlIDAgL1N0ZW1WIDAgL01heFdpZHRoIDEzMDYgPj4KZW5kb2JqCjI1IDAgb2JqClsgMCA0NzIgNDcyIDQ3MiA0NzIgNDcyIDQ3MiA0NzIgNDcyIDQ3MiA0NzIgNDcyIDQ3MiAyMzYgNDcyIDQ3MiA0NzIgNDcyCjQ3MiA0NzIgNDcyIDQ3MiA0NzIgNDcyIDQ3MiA0NzIgNDcyIDQ3MiA0NzIgNDcyIDQ3MiA0NzIgMjM2IDI4NCA0MTkgNzEzIDU5OAo5MjcgNjk0IDI0MiAzMzUgMzM1IDQ1MCA2MDAgMjcyIDM5OSAyNzIgMzgzIDYwMCA2MDAgNjAwIDYwMCA2MDAgNjAwIDYwMCA2MDAKNjAwIDYwMCAyOTIgMjkyIDYwMCA2MDAgNjAwIDQ3NyA4OTEgNjQxIDY1MyA2MjEgNjcxIDU4MyA1NTkgNjk1IDcwNyA0MDAgNTEwCjYzNCA1MDEgODEyIDcwNyA3MDggNjA2IDcwOCA2NDAgNTgxIDU3MiA2NzggNjA5IDg5MSA2MTMgNTkzIDU4MCAzMTcgMzgzIDMxNwo2MDAgNTY1IDYwMCA1MzQgNTgwIDUwMyA1ODAgNTQ5IDMyNCA1MjggNTY4IDI1MCAyNTAgNTI3IDI3MiA4NzMgNTY4IDU2MCA1ODAKNTgwIDM2NyA0ODcgMzUxIDU2OCA0OTIgNzY4IDUwNyA0OTkgNDY0IDM0MyAzMTQgMzQzIDYwMCA0NzIgNjI1IDQ3MiAyNzQgNDg1CjQ3NSA4MDMgNTUyIDU1MiA2MDAgMTMwNiA1ODEgMzA0IDk4NSA0NzIgNTgwIDQ3MiA0NzIgMjczIDI3MyA0NzUgNDc0IDM5Ngo1ODggNzgwIDYwMCA2NTggNDg3IDMwNCA5MzEgNDcyIDQ2NCA1OTMgMjM2IDI4NCA1MTQgNTk1IDYxMiA2MDUgMzE0IDU4NiA2MDAKNzc2IDM5OSA1MTMgNjAwIDM5OSA0NzYgNjAwIDQ2OCA2MDAgMzQ2IDM0NiA2MDAgNTczIDY1MiAzMjYgNjAwIDM1OSAzOTggNTEzCjg0NyA4NzIgODI0IDQ2NyA2NDEgNjQxIDY0MSA2NDEgNjQxIDY0MSA5MDcgNjIxIDU4MyA1ODMgNTgzIDU4MyA0MDAgNDAwIDQwMAo0MDAgNjc0IDcwNyA3MDggNzA4IDcwOCA3MDggNzA4IDYwMCA3MDggNjc4IDY3OCA2NzggNjc4IDU5MyA2MDYgNjQwIDUzNCA1MzQKNTM0IDUzNCA1MzQgNTM0IDg2NCA1MDMgNTQ5IDU0OSA1NDkgNTQ5IDI1MCAyNTAgMjUwIDI1MCA1NTUgNTY4IDU2MCA1NjAgNTYwCjU2MCA1NjAgNjAwIDU2OCA1NjggNTY4IDU2OCA1NjggNDk5IDU4MCA0OTkgXQplbmRvYmoKMjggMCBvYmoKPDwgL0cgMjkgMCBSIC9IIDMwIDAgUiAvYnJhY2tldGxlZnQgMzEgMCBSIC9icmFja2V0cmlnaHQgMzIgMCBSIC9lIDMzIDAgUgovZyAzNCAwIFIgL24gMzUgMCBSIC9yIDM2IDAgUiAvc3BhY2UgMzcgMCBSIC95IDM4IDAgUiAveiAzOSAwIFIgPj4KZW5kb2JqCjQ0IDAgb2JqCjw8IC9MZW5ndGggMzMwIC9GaWx0ZXIgL0ZsYXRlRGVjb2RlID4+CnN0cmVhbQp4nD2SS27EQAhE9z4FFxip+fXnPI5GWUzuv82j28nCKmSgKKjumtIkurzUJYdK9iZfesVUcTP5eaIhMU3cDXRwyn3tKII/Aa6DmTtDtFJiUG9dorJ8ZOz89fX05cH78nYYbJSeJebVp2SswYI8HV18gDm3tvtf5ef6vjLpyVKsdFX0udSLZ4n6ELM/rE6F3dh9Y1sPxpOpCZpN1GrqlLW2jC4DfZHSTWz1AnR7VODcrqO4ivYJEMF9gg4qE2rV2JKRkGiLrF+cpwndEwf2FdD90iauY1ti0zae8RVpDEF3w5E6DjPHKAPV5oa1p7NNlpniTK67ZXGsEmiU1mmpLcGz6nVRzBnMQCuFaI5WYytDs0Nfb8P7QWZ421GMRS1Veva8sQLD+tjvKfTgeRg7gjcx2S3ox0pWIYMWmzB1lq53+Nh5Y+37F0TzfioKZW5kc3RyZWFtCmVuZG9iago0NSAwIG9iago8PCAvTGVuZ3RoIDE4MSAvRmlsdGVyIC9GbGF0ZURlY29kZSA+PgpzdHJlYW0KeJw9kEsSAyEIRPeeoo8gP9HzJJXKYnL/bRonZqH9BAobbCk6hvNyNWRXPKUVhic+zfuCZ+Jqav1HkgqZfVOHjMUzeYoTEopHkzEg7thq66dxMsIMuywmZmCuiq9ELqhQAupR8mhmo+BqpoK+fcRWmfUWFwhFAiYsZyv+nwPT6xYdDBaY7TfLszz2CtN0LMx7hnkPRSN+BuVabmBlrYOfhh2a97ZoKP/kJ3sWeLV3e30BZHxDEwplbmRzdHJlYW0KZW5kb2JqCjQ2IDAgb2JqCjw8IC9MZW5ndGggOTUgL0ZpbHRlciAvRmxhdGVEZWNvZGUgPj4Kc3RyZWFtCnicPYxBDsAgCATvvGI/0AQRFf/TND3Y/1+7RtsLTHZhSjcoDiucVRXFG84kHz6SvcNax5CimUdDnN3cFg5LjRSrWBYWnmERpLQ1zPi8KGtgSinqaWf1v7vlegH/nxwsCmVuZHN0cmVhbQplbmRvYmoKNDIgMCBvYmoKPDwgL1R5cGUgL0ZvbnQgL0Jhc2VGb250IC9HQ1dYRFYrRGVqYVZ1U2Fucy1PYmxpcXVlIC9GaXJzdENoYXIgMAovTGFzdENoYXIgMjU1IC9Gb250RGVzY3JpcHRvciA0MSAwIFIgL1N1YnR5cGUgL1R5cGUzCi9OYW1lIC9HQ1dYRFYrRGVqYVZ1U2Fucy1PYmxpcXVlIC9Gb250QkJveCBbIC0xMDE2IC0zNTEgMTY2MCAxMDY4IF0KL0ZvbnRNYXRyaXggWyAwLjAwMSAwIDAgMC4wMDEgMCAwIF0gL0NoYXJQcm9jcyA0MyAwIFIKL0VuY29kaW5nIDw8IC9UeXBlIC9FbmNvZGluZyAvRGlmZmVyZW5jZXMgWyAxMDEgL2UgMTE2IC90IDEyMCAveCBdID4+Ci9XaWR0aHMgNDAgMCBSID4+CmVuZG9iago0MSAwIG9iago8PCAvVHlwZSAvRm9udERlc2NyaXB0b3IgL0ZvbnROYW1lIC9HQ1dYRFYrRGVqYVZ1U2Fucy1PYmxpcXVlIC9GbGFncyA5NgovRm9udEJCb3ggWyAtMTAxNiAtMzUxIDE2NjAgMTA2OCBdIC9Bc2NlbnQgOTI5IC9EZXNjZW50IC0yMzYgL0NhcEhlaWdodCAwCi9YSGVpZ2h0IDAgL0l0YWxpY0FuZ2xlIDAgL1N0ZW1WIDAgL01heFdpZHRoIDEzNTAgPj4KZW5kb2JqCjQwIDAgb2JqClsgNjAwIDYwMCA2MDAgNjAwIDYwMCA2MDAgNjAwIDYwMCA2MDAgNjAwIDYwMCA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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "sweep[\"ng\":0.0].plot_transitions(subsystems=[tmon1, resonator], sidebands=True);" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Custom sweeps\n", + "`ParameterSweep` generates data commonly needed in a multi-component quantum system. Other quantities of interest can be generated by defining a custom sweep function generating the data and calling `.add_sweep(...)`.\n", + "\n", + "To do so, define a function of the following form:\n", + "\n", + "``def custom_func(paramsweep, paramindex_tuple, paramvals_tuple, **kwargs):\n", + " ...\n", + " return data``\n", + " \n", + "As a toy example, here is a function that returns the 01 charge matrix element for `tmon2` at each parameter point:" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "metadata": {}, + "outputs": [], + "source": [ + "def tmon2_n01(paramsweep, paramindex_tuple, paramvals_tuple, **kwargs):\n", + " # We could recalculate matrix elements from scratch, but it is advantageous to use the bare spectral \n", + " # data we have already calculated.\n", + " bare_evecs = sweep[\"bare_evecs\"][\"subsys\":1][paramindex_tuple]\n", + " n_matrix_elements = tmon2.matrixelement_table(\n", + " operator=\"n_operator\",\n", + " evecs=bare_evecs,\n", + " evals_count=tmon2.truncated_dim,\n", + " )\n", + " return np.abs(n_matrix_elements[0,1])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The `add_sweep` method takes the callable function one argument, and the name under which the scan should be stored as the second argument:" + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "metadata": {}, + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "sweeping tmon2_n01: 0%| | 0/1911 [00:00, )" + ] + }, + "execution_count": 33, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "application/pdf": 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "sweep[\"n01\"][\"flux\":15].plot()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Dispersive limit: Stark shifts and Kerr\n", + "\n", + "Coupled systems of qubits and harmonic modes are frequently operated in the **dispersive regime** where relevant transition frequencies are detuned from each other and hybridization among levels can be treated perturbatively. \n", + "An effective description of this dispersive regime involves energy corrections and dispersive couplings phrased in terms of \n", + "\n", + "* **Lamb shifts**, \n", + "* **ac Stark shifts**, and \n", + "* **Kerr terms**, \n", + "\n", + "to leading order. scqubits computes the associated coefficients as part of `ParameterSweep` and makes them accessible through \n", + "\n", + "* `\"lamb\"`: `NamedSlotsNdarray` with axes `\"subsys\", , `\n", + "* `\"chi\"`: `NamedSlotsNdarray` with axes `\"subsys1\", \"subsys2\", , `\n", + "* `\"kerr\"`: `NamedSlotsNdarray` with axes `\"subsys1\", \"subsys2\", , `\n", + "\n", + "For instance, here are dispersive ac Stark shifts associated with `tmon1` (subsystem 0) and `resonator` (subsystem 2):" + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "NamedSlotsNdarray([[[ 0.00000000e+00, -4.28976197e-04, -7.08859396e-04,\n", + " nan],\n", + " [ 7.10542736e-15, -4.28992818e-04, -7.08785111e-04,\n", + " nan],\n", + " [ 7.10542736e-15, -4.29008394e-04, -7.08715140e-04,\n", + " nan],\n", + " ...,\n", + " [-7.10542736e-15, -4.28680983e-04, -7.10116107e-04,\n", + " nan],\n", + " [ 0.00000000e+00, -4.28649766e-04, -7.10242303e-04,\n", + " nan],\n", + " [-7.10542736e-15, -4.28617406e-04, -7.10371822e-04,\n", + " nan]],\n", + "\n", + " [[-7.10542736e-15, -4.53851797e-04, -7.43089937e-04,\n", + " nan],\n", + " [ 7.10542736e-15, -4.53869412e-04, -7.43037055e-04,\n", + " nan],\n", + " [ 0.00000000e+00, -4.53885918e-04, -7.42987157e-04,\n", + " nan],\n", + " ...,\n", + " [ 7.10542736e-15, -4.53538814e-04, -7.43968944e-04,\n", + " nan],\n", + " [-7.10542736e-15, -4.53505706e-04, -7.44055459e-04,\n", + " nan],\n", + " [ 0.00000000e+00, -4.53471381e-04, -7.44143892e-04,\n", + " nan]],\n", + "\n", + " [[ 0.00000000e+00, -5.32668771e-04, -8.53318240e-04,\n", + " nan],\n", + " [ 0.00000000e+00, -5.32689674e-04, -8.53347305e-04,\n", + " nan],\n", + " [ 7.10542736e-15, -5.32709260e-04, -8.53374269e-04,\n", + " nan],\n", + " ...,\n", + " [ 0.00000000e+00, -5.32296693e-04, -8.52753164e-04,\n", + " nan],\n", + " [ 0.00000000e+00, -5.32257264e-04, -8.52688177e-04,\n", + " nan],\n", + " [ 0.00000000e+00, -5.32216373e-04, -8.52619786e-04,\n", + " nan]],\n", + "\n", + " ...,\n", + "\n", + " [[ 7.10542736e-15, -5.65775964e-04, -8.81582018e-04,\n", + " nan],\n", + " [ 0.00000000e+00, -5.65797724e-04, -8.81206560e-04,\n", + " nan],\n", + " [ 0.00000000e+00, -5.65818116e-04, -8.80852826e-04,\n", + " nan],\n", + " ...,\n", + " [ 0.00000000e+00, -5.65389658e-04, -8.87921379e-04,\n", + " nan],\n", + " [ 0.00000000e+00, -5.65348834e-04, -8.88556854e-04,\n", + " nan],\n", + " [ 0.00000000e+00, -5.65306520e-04, -8.89208902e-04,\n", + " nan]],\n", + "\n", + " [[ 0.00000000e+00, -5.04945307e-04, -7.78340219e-04,\n", + " nan],\n", + " [ 0.00000000e+00, -5.04965228e-04, -7.79114056e-04,\n", + " nan],\n", + " [ 0.00000000e+00, -5.04983886e-04, -7.79837453e-04,\n", + " nan],\n", + " ...,\n", + " [ 0.00000000e+00, -5.04589817e-04, -7.64254828e-04,\n", + " nan],\n", + " [ 0.00000000e+00, -5.04552043e-04, -7.62726860e-04,\n", + " nan],\n", + " [-7.10542736e-15, -5.04512849e-04, -7.61134898e-04,\n", + " nan]],\n", + "\n", + " [[ 0.00000000e+00, -4.86674364e-04, -7.60296164e-04,\n", + " nan],\n", + " [ 0.00000000e+00, -4.86692762e-04, -7.60440317e-04,\n", + " nan],\n", + " [ 0.00000000e+00, -4.86709997e-04, -7.60575075e-04,\n", + " nan],\n", + " ...,\n", + " [-7.10542736e-15, -4.86345983e-04, -7.57677077e-04,\n", + " nan],\n", + " [-7.10542736e-15, -4.86311155e-04, -7.57392697e-04,\n", + " nan],\n", + " [ 7.10542736e-15, -4.86275024e-04, -7.57096569e-04,\n", + " nan]]])" + ] + }, + "execution_count": 34, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sweep[\"chi\"][\"subsys1\":0, \"subsys2\":2]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Note that the occurence of `nan` signals that in some instances the breakdown of the dispersive approximation prevents the identification of states with bare product states. Such breakdown regions will result in \"interruptions\" in plots. While not visually pleasing, they do inform us that the dispersive regime is invalid in those regions and their immediate vicinity.\n", + "\n", + "Simple visualization of the dispersive shift associated with level 1 (ordinarily denoted $\\chi_{01}$):" + ] + }, + { + "cell_type": "code", + "execution_count": 35, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(
, )" + ] + }, + "execution_count": 35, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "application/pdf": 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" \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", - " \n", - " \n", + " \n", + " \n", " \n", " \n", "\n" @@ -14292,6729 +17281,26 @@ } ], "source": [ - "sweep[\"ng\":0.0].plot_transitions(subsystems=[tmon1]);" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### `initial` and `final`\n", - "By default, the ground state is taken as origin for all transitions. In case of thermal excitations, other states can be of interest as initial states. Specification of an alternative initial state uses dispersive labeling of states:\n", - "\n", - "e.g., (1,0,0) uses the 1st excited `tmon1` state as the initial state:" - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "metadata": {}, - "outputs": [ - { - "data": { - "image/svg+xml": [ - "\r\n", - "\r\n", - "\r\n", - "\r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " 2021-07-05T08:38:16.532261\r\n", - " image/svg+xml\r\n", - " \r\n", - " \r\n", - " Matplotlib v3.3.4, https://matplotlib.org/\r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - 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" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "sweep[\"ng\":0.0].plot_transitions(initial=(1,0,0));" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Similarly `final` option may be used if only the transitions to a specific state should be highlighted:" - ] - }, - { - "cell_type": "code", - "execution_count": 22, - "metadata": {}, - "outputs": [ - { - "data": { - "image/svg+xml": [ - "\r\n", - "\r\n", - "\r\n", - "\r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " 2021-03-12T19:47:25.093046\r\n", - " image/svg+xml\r\n", - " \r\n", - " \r\n", - " Matplotlib v3.3.2, https://matplotlib.org/\r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - 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" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "sweep[\"ng\":0.0].plot_transitions(final=(0,1,0));" + "sweep[\"chi\"][\"subsys1\":0, \"subsys2\":2][\"ng\":0][:, 1].plot()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "#### `make_positive`\n", - "When considering excited as in the previous example, some of the transition energies will naturally be negative. Experimentally, these transitions are driven at the absolute frequency. By default, absolute values of transition energies are displayed. This can be disabled by setting `make_positive=False`.\n", - "\n", + "(Interruptions again mark dispersive-limit breakdown. The unattractive \"spikes\" actually correspond to capturing part of the transmon's straddling regime, close to the breakdown of perturbation theory.)\n", "\n", - "#### `sidebands`\n", - "By default, sideband transitions are not highlighted. If set to true, sideband transitions with multiple subsystems changing excitation levels are included as well:" + "Inspection of the transition spectrum matches the positions of singular behavior in $\\chi$ with avoided crossings:" ] }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 36, "metadata": {}, "outputs": [ { "data": { - "application/pdf": 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" \n", " \n", - " \n", + " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -24842,15 +19381,15 @@ " \n", " \n", " \n", - " \n", - " \n", + " \n", + " \n", " \n", - " \n", + " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", + " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", " \n", " \n", " \n", - " \n", + " \n", " \n", " \n", " \n", @@ -25065,4921 +19472,6 @@ "output_type": "display_data" } ], - "source": [ - "sweep[\"ng\":0.0].plot_transitions(subsystems=[tmon1, resonator], sidebands=True);" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Custom sweeps\n", - "`ParameterSweep` generates data commonly needed in a multi-component quantum system. Other quantities of interest can be generated by defining a custom sweep function generating the data and calling `.add_sweep(...)`.\n", - "\n", - "To do so, define a function of the following form:\n", - "\n", - "``def custom_func(paramsweep, paramindex_tuple, paramvals_tuple, **kwargs):\n", - " ...\n", - " return data``\n", - " \n", - "As a toy example, here is a function that returns the 01 charge matrix element for `tmon2` at each parameter point:" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [], - "source": [ - "def tmon2_n01(paramsweep, paramindex_tuple, paramvals_tuple, **kwargs):\n", - " # We could recalculate matrix elements from scratch, but it is advantageous to use the bare spectral \n", - " # data we have already calculated.\n", - " bare_evecs = sweep[\"bare_evecs\"][\"subsys\":1][paramindex_tuple]\n", - " n_matrix_elements = tmon2.matrixelement_table(\n", - " operator=\"n_operator\",\n", - " evecs=bare_evecs,\n", - " evals_count=tmon2.truncated_dim,\n", - " )\n", - " return np.abs(n_matrix_elements[0,1])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The `add_sweep` method takes the callable function one argument, and the name under which the scan should be stored as the second argument:" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [ - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "HBox(children=(HTML(value='sweeping tmon2_n01'), FloatProgress(value=0.0, max=8379.0), HTML(value='')))" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "sweep[:].add_sweep(tmon2_n01, \"n01\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Pre-slicing is required; here the sweep is to extend over all parameter sets associated with sweep. The resulting data is accessible by dict-like access, and yields a `NamedSlotsNdarray`:" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "NamedSlotsNdarray([[1.30478755, 1.30478755, 1.30478755, ..., 1.30478755,\n", - " 1.30478755, 1.30478755],\n", - " [1.30446711, 1.30446711, 1.30446711, ..., 1.30446711,\n", - " 1.30446711, 1.30446711],\n", - " [1.30350512, 1.30350512, 1.30350512, ..., 1.30350512,\n", - " 1.30350512, 1.30350512],\n", - " ...,\n", - " [1.04703072, 1.04703072, 1.04703072, ..., 1.04703072,\n", - " 1.04703072, 1.04703072],\n", - " [1.02349545, 1.02349545, 1.02349544, ..., 1.02349544,\n", - " 1.02349545, 1.02349545],\n", - " [0.99863368, 0.99863367, 0.99863365, ..., 0.99863365,\n", - " 0.99863367, 0.99863368]])" - ] - }, - "execution_count": 12, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "sweep[\"n01\"]" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We can easily take a slice for fixed flux and plot the result:" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "(
, )" - ] - }, - "execution_count": 13, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/svg+xml": [ - "\r\n", - "\r\n", - "\r\n", - "\r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " 2021-07-05T09:03:50.038348\r\n", - " image/svg+xml\r\n", - " \r\n", - " \r\n", - " Matplotlib v3.3.4, https://matplotlib.org/\r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - "\r\n" - ], - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "sweep[\"n01\"][\"flux\":35].plot()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Dispersive limit: Stark shifts and Kerr\n", - "\n", - "Coupled systems of qubits and harmonic modes are frequently operated in the **dispersive regime** where relevant transition frequencies are detuned from each other and hybridization among levels can be treated perturbatively. \n", - "An effective description of this dispersive regime involves energy corrections and dispersive couplings phrased in terms of \n", - "\n", - "* **Lamb shifts**, \n", - "* **ac Stark shifts**, and \n", - "* **Kerr terms**, \n", - "\n", - "to leading order. scqubits computes the associated coefficients as part of `ParameterSweep` and makes them accessible through \n", - "\n", - "* `\"lamb\"`: `NamedSlotsNdarray` with axes `\"subsys\", , `\n", - "* `\"chi\"`: `NamedSlotsNdarray` with axes `\"subsys1\", \"subsys2\", , `\n", - "* `\"kerr\"`: `NamedSlotsNdarray` with axes `\"subsys1\", \"subsys2\", , `\n", - "\n", - "For instance, here are dispersive ac Stark shifts associated with `tmon1` (subsystem 0) and `resonator` (subsystem 2):" - ] - }, - { - "cell_type": "code", - "execution_count": 25, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "NamedSlotsNdarray([[[ 7.10542736e-15, -4.28976197e-04, nan],\n", - " [-7.10542736e-15, -4.28992818e-04, nan],\n", - " [-7.10542736e-15, -4.29008394e-04, nan],\n", - " ...,\n", - " [ 0.00000000e+00, -4.28680983e-04, nan],\n", - " [ 0.00000000e+00, -4.28649766e-04, nan],\n", - " [ 0.00000000e+00, -4.28617406e-04, nan]],\n", - "\n", - " [[ 0.00000000e+00, -4.30205841e-04, nan],\n", - " [ 7.10542736e-15, -4.30222514e-04, nan],\n", - " [ 7.10542736e-15, -4.30238139e-04, nan],\n", - " ...,\n", - " [ 0.00000000e+00, -4.29909697e-04, nan],\n", - " [ 0.00000000e+00, -4.29878381e-04, nan],\n", - " [ 7.10542736e-15, -4.29845917e-04, nan]],\n", - "\n", - " [[ 0.00000000e+00, -4.33902772e-04, nan],\n", - " [ 0.00000000e+00, -4.33919601e-04, nan],\n", - " [ 0.00000000e+00, -4.33935373e-04, nan],\n", - " ...,\n", - " [ 7.10542736e-15, -4.33603826e-04, nan],\n", - " [-7.10542736e-15, -4.33572211e-04, nan],\n", - " [-7.10542736e-15, -4.33539436e-04, nan]],\n", - "\n", - " ...,\n", - "\n", - " [[ 0.00000000e+00, -4.90206224e-04, nan],\n", - " [ 0.00000000e+00, -4.90225124e-04, nan],\n", - " [ 7.10542736e-15, -4.90242829e-04, nan],\n", - " ...,\n", - " [ 0.00000000e+00, -4.89869250e-04, nan],\n", - " [-7.10542736e-15, -4.89833477e-04, nan],\n", - " [ 7.10542736e-15, -4.89796366e-04, nan]],\n", - "\n", - " [[ 0.00000000e+00, -4.87527712e-04, nan],\n", - " [ 0.00000000e+00, -4.87546333e-04, nan],\n", - " [ 0.00000000e+00, -4.87563776e-04, nan],\n", - " ...,\n", - " [ 7.10542736e-15, -4.87195730e-04, nan],\n", - " [ 0.00000000e+00, -4.87160488e-04, nan],\n", - " [ 0.00000000e+00, -4.87123928e-04, nan]],\n", - "\n", - " [[ 0.00000000e+00, -4.86674364e-04, nan],\n", - " [ 0.00000000e+00, -4.86692762e-04, nan],\n", - " [ 0.00000000e+00, -4.86709997e-04, nan],\n", - " ...,\n", - " [-7.10542736e-15, -4.86345983e-04, nan],\n", - " [ 0.00000000e+00, -4.86311155e-04, nan],\n", - " [-7.10542736e-15, -4.86275024e-04, nan]]])" - ] - }, - "execution_count": 25, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "sweep[\"chi\"][\"subsys1\":0, \"subsys2\":2]" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Note that the occurence of `nan` signals that in some instances the breakdown of the dispersive approximation prevents the identification of states with bare product states. Such breakdown regions will result in \"interruptions\" in plots. While not visually pleasing, they do inform us that the dispersive regime is invalid in those regions and their immediate vicinity.\n", - "\n", - "Simple visualization of the dispersive shift associated with level 1 (ordinarily denoted $\\chi_{01}$):" - ] - }, - { - "cell_type": "code", - "execution_count": 26, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "(
, )" - ] - }, - "execution_count": 26, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/svg+xml": [ - "\r\n", - "\r\n", - "\r\n", - "\r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " 2021-07-05T08:41:17.607507\r\n", - " image/svg+xml\r\n", - " \r\n", - " \r\n", - " Matplotlib v3.3.4, https://matplotlib.org/\r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - "\r\n" - ], - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "sweep[\"chi\"][\"subsys1\":0, \"subsys2\":2][\"ng\":0][:, 1].plot()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "(Interruptions again mark dispersive-limit breakdown. The unattractive \"spikes\" actually correspond to capturing part of the transmon's straddling regime, close to the breakdown of perturbation theory.)\n", - "\n", - "Inspection of the transition spectrum matches the positions of singular behavior in $\\chi$ with avoided crossings:" - ] - }, - { - "cell_type": "code", - "execution_count": 27, - "metadata": {}, - "outputs": [ - { - "data": { - "image/svg+xml": [ - "\r\n", - "\r\n", - "\r\n", - "\r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " 2021-07-05T08:41:23.565361\r\n", - " image/svg+xml\r\n", - " \r\n", - " \r\n", - " Matplotlib v3.3.4, https://matplotlib.org/\r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - " \r\n", - 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"execution_count": 30, + "execution_count": 39, "metadata": {}, "output_type": "execute_result" } diff --git a/examples/demo_qutip_fluxoniumcz.ipynb b/examples/demo_qutip_fluxoniumcz.ipynb index 978ece5..322d76c 100644 --- a/examples/demo_qutip_fluxoniumcz.ipynb +++ b/examples/demo_qutip_fluxoniumcz.ipynb @@ -219,7 +219,9 @@ "outputs": [ { "data": { - "text/plain": "Text(0.5, 0, 't (ns)')" + "text/plain": [ + "Text(0.5, 0, 't (ns)')" + ] }, "execution_count": 7, "metadata": {}, @@ -227,9 +229,1110 @@ }, { "data": { - "text/plain": "
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" 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" + ] }, "metadata": {}, "output_type": "display_data" @@ -305,8 +1408,21 @@ "outputs": [ { "data": { - "text/plain": "Quantum object: dims = [[2, 2], [2, 2]], shape = (4, 4), type = oper, isherm = False\nQobj data =\n[[ 9.99997558e-01+0.00000000e+00j 7.35241090e-08-9.49725529e-08j\n 3.99463511e-05+2.18320693e-05j -8.53948262e-07+2.82839250e-08j]\n [-7.01944586e-08-9.48664962e-08j 9.95520147e-01+0.00000000e+00j\n 2.17470258e-06-6.46731035e-06j -7.57443647e-05+2.00623781e-05j]\n [-3.99721921e-05+2.17851550e-05j -9.74663830e-07-3.01235561e-06j\n 9.99620205e-01+0.00000000e+00j -3.47478033e-06-6.59973136e-07j]\n [ 2.42061470e-07+1.48908800e-07j -7.02332015e-05-3.47883383e-05j\n -3.53709345e-06-4.98170249e-08j -9.77936404e-01-2.00098574e-01j]]", - "text/latex": "Quantum object: dims = [[2, 2], [2, 2]], shape = (4, 4), type = oper, isherm = False $ \\\\ \\left(\\begin{matrix}1.000 & (7.352\\times10^{-08}-9.497\\times10^{-08}j) & (3.995\\times10^{-05}+2.183\\times10^{-05}j) & (-8.539\\times10^{-07}+2.828\\times10^{-08}j)\\\\(-7.019\\times10^{-08}-9.487\\times10^{-08}j) & 0.996 & (2.175\\times10^{-06}-6.467\\times10^{-06}j) & (-7.574\\times10^{-05}+2.006\\times10^{-05}j)\\\\(-3.997\\times10^{-05}+2.179\\times10^{-05}j) & (-9.747\\times10^{-07}-3.012\\times10^{-06}j) & 1.000 & (-3.475\\times10^{-06}-6.600\\times10^{-07}j)\\\\(2.421\\times10^{-07}+1.489\\times10^{-07}j) & (-7.023\\times10^{-05}-3.479\\times10^{-05}j) & (-3.537\\times10^{-06}-4.982\\times10^{-08}j) & (-0.978-0.200j)\\\\\\end{matrix}\\right)$" + "text/latex": [ + "Quantum object: dims = [[2, 2], [2, 2]], shape = (4, 4), type = oper, isherm = False $ \\\\ \\left(\\begin{matrix}1.000 & (7.352\\times10^{-08}-9.497\\times10^{-08}j) & (3.995\\times10^{-05}+2.183\\times10^{-05}j) & (-8.539\\times10^{-07}+2.828\\times10^{-08}j)\\\\(-7.019\\times10^{-08}-9.487\\times10^{-08}j) & 0.996 & (2.175\\times10^{-06}-6.467\\times10^{-06}j) & (-7.574\\times10^{-05}+2.006\\times10^{-05}j)\\\\(-3.997\\times10^{-05}+2.179\\times10^{-05}j) & (-9.747\\times10^{-07}-3.012\\times10^{-06}j) & 1.000 & (-3.475\\times10^{-06}-6.600\\times10^{-07}j)\\\\(2.421\\times10^{-07}+1.489\\times10^{-07}j) & (-7.023\\times10^{-05}-3.479\\times10^{-05}j) & (-3.537\\times10^{-06}-4.982\\times10^{-08}j) & (-0.978-0.200j)\\\\\\end{matrix}\\right)$" + ], + "text/plain": [ + "Quantum object: dims = [[2, 2], [2, 2]], shape = (4, 4), type = oper, isherm = False\n", + "Qobj data =\n", + "[[ 9.99997558e-01+0.00000000e+00j 7.35241090e-08-9.49725529e-08j\n", + " 3.99463511e-05+2.18320693e-05j -8.53948262e-07+2.82839254e-08j]\n", + " [-7.01944586e-08-9.48664962e-08j 9.95520147e-01+0.00000000e+00j\n", + " 2.17470258e-06-6.46731035e-06j -7.57443646e-05+2.00623781e-05j]\n", + " [-3.99721921e-05+2.17851550e-05j -9.74663830e-07-3.01235561e-06j\n", + " 9.99620205e-01+0.00000000e+00j -3.47478033e-06-6.59973135e-07j]\n", + " [ 2.42061470e-07+1.48908800e-07j -7.02332015e-05-3.47883383e-05j\n", + " -3.53709345e-06-4.98170244e-08j -9.77936404e-01-2.00098574e-01j]]" + ] }, "execution_count": 10, "metadata": {}, @@ -328,7 +1444,9 @@ "outputs": [ { "data": { - "text/plain": "0.9906027020232415" + "text/plain": [ + "0.990602702039944" + ] }, "execution_count": 11, "metadata": {}, @@ -343,14 +1461,17 @@ { "cell_type": "code", "execution_count": null, - "outputs": [], - "source": [], "metadata": { "collapsed": false, + "jupyter": { + "outputs_hidden": false + }, "pycharm": { "name": "#%%\n" } - } + }, + "outputs": [], + "source": [] } ], "metadata": { @@ -369,7 +1490,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.9.15" + "version": "3.9.16" }, "vscode": { "interpreter": { @@ -378,5 +1499,5 @@ } }, "nbformat": 4, - "nbformat_minor": 2 -} \ No newline at end of file + "nbformat_minor": 4 +} diff --git a/examples/demo_qutip_fluxoniumreset.ipynb b/examples/demo_qutip_fluxoniumreset.ipynb index 139c4b2..e703e51 100644 --- a/examples/demo_qutip_fluxoniumreset.ipynb +++ b/examples/demo_qutip_fluxoniumreset.ipynb @@ -273,7 +273,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -296,6594 +296,9 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Text(0, 0.5, 'population')" - ] - }, - "execution_count": 9, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "application/pdf": 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "for i in range(4):\n", " plt.plot(tlist, result.expect[i], label=r\"$|%u\\rangle$\" % (i))\n", diff --git a/examples/demo_zeropi.ipynb b/examples/demo_zeropi.ipynb index 6d90425..327b4bf 100644 --- a/examples/demo_zeropi.ipynb +++ b/examples/demo_zeropi.ipynb @@ -21,7 +21,7 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 1, "metadata": { "ExecuteTime": { "end_time": "2020-03-27T13:04:04.721293Z", @@ -40,7 +40,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ @@ -48,7 +47,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ @@ -66,7 +64,7 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 2, "metadata": { "ExecuteTime": { "end_time": "2020-03-27T13:04:05.513875Z", @@ -77,26 +75,12 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "272ebf4df0a5423f8dc35aaafc756be9", + "model_id": "a16573f1ff294284b1d47613e88a6101", "version_major": 2, "version_minor": 0 }, "text/plain": [ - "HBox(children=(VBox(children=(HBox(children=(Label(value='EJ [GHz]'), FloatText(value=10.0, layout=Layout(widt…" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "c01e02e4e1234a458314feff3780aaae", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "Output()" + "Row(children=[Row(children=[ValidatedNumberField(class_='ml-2 py-0', dense=True, error=False, filled=True, lab…" ] }, "metadata": {}, @@ -108,7 +92,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ @@ -119,7 +102,7 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 3, "metadata": { "ExecuteTime": { "end_time": "2020-03-27T12:55:37.604003Z", @@ -143,14 +126,14 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 4, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "ZeroPi--------------| [ZeroPi_4]\n", + "ZeroPi--------------| [ZeroPi_2]\n", " | EJ: 10.0\n", " | EL: 0.04\n", " | ECJ: 20.0\n", @@ -172,7 +155,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ @@ -181,7 +163,7 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 5, "metadata": {}, "outputs": [], "source": [ @@ -189,7 +171,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ @@ -198,7 +179,7 @@ }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 6, "metadata": {}, "outputs": [ { @@ -207,7 +188,7 @@ "0.04008016032064128" ] }, - "execution_count": 26, + "execution_count": 6, "metadata": {}, "output_type": "execute_result" } @@ -225,7 +206,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ @@ -234,7 +214,7 @@ }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 7, "metadata": { "ExecuteTime": { "end_time": "2020-02-07T03:18:47.984128Z", @@ -249,7 +229,7 @@ " 18.93090846, 19.16555977, 19.18024366, 19.92838159, 20.0925804 ])" ] }, - "execution_count": 27, + "execution_count": 7, "metadata": {}, "output_type": "execute_result" } @@ -260,7 +240,7 @@ }, { "cell_type": "code", - "execution_count": 28, + "execution_count": 8, "metadata": { "ExecuteTime": { "end_time": "2020-02-07T03:19:42.994539Z", @@ -271,7 +251,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "91df4bdf1cd94dc683bced2cd0995a1b", + "model_id": "", "version_major": 2, "version_minor": 0 }, @@ -285,25 +265,1236 @@ { "data": { "text/plain": [ - "(
,\n", - " )" + "(
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" ] @@ -545,7 +29649,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ @@ -553,7 +29656,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ @@ -643,7 +29745,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ @@ -658,7 +29759,7 @@ "metadata": { "celltoolbar": "Initialisation Cell", "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -672,7 +29773,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.10.6" + "version": "3.9.16" }, "pycharm": { "stem_cell": { diff --git a/examples/testing.ipynb b/examples/testing.ipynb index f7fdd37..b9018ed 100644 --- a/examples/testing.ipynb +++ b/examples/testing.ipynb @@ -1009,7 +1009,7 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -1023,7 +1023,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.5" + "version": "3.9.16" }, "toc": { "base_numbering": 1, @@ -1069,5 +1069,5 @@ } }, "nbformat": 4, - "nbformat_minor": 2 + "nbformat_minor": 4 } diff --git a/workflow-requirements.info b/workflow-requirements.info index 8bd91f2..0ca08de 100644 --- a/workflow-requirements.info +++ b/workflow-requirements.info @@ -1,9 +1,14 @@ -cython>=0.28.5 +cython>=0.29.20,<3.0.0 numpy>=1.14.2 scipy>=1.1.0 -matplotlib>=3.0.0 +matplotlib>=3.5 qutip>=4.3.1 h5py cycler tqdm pathos +ipyvuetify +pyyaml +sympy +tqdm +typing_extensions