A PyTorch-based framework for Quantum Classical Simulation, Quantum Machine Learning, Quantum Neural Networks, Parameterized Quantum Circuits with support for easy deployments on real quantum computers.

Tensor network based quantum software framework for the NISQ era

Tutorials for Quantum Algorithms with Qiskit implementations.

Library for pulse-level/analog control of neutral atom devices. Emulator with QuTiP.

Tensor Train Toolbox

Companion code for Learn Quantum Computing with Python and Q# Book by Dr. Sarah Kaiser and Dr. Cassandra Granade 💖

Quantum computational chemistry based on TensorCircuit

A reference implementation for a quantum virtual machine in Python

An OCaml based implementation of a Quil QVM

QuEra's Neutral Atom SDK for Analog QPUs

Library for fast computations involving indistinguishable bosons

Type an M x M matrix for your open quantum system Hamiltonian, and give a spectral density (analytic or numerical). FeynDyn gives the density matrix dynamics according to the Leggett-Caldeira bath or the Feynman-Vernon bath at any temperature. Can do up to 16 qubits (65536 levels) and infinitely many bath modes. Email nike@hpqc.org for the lates…

Quantum Harmonic Oscillator Synthesizer.

EntropiQ - design and run large-scale simulations of quantum systems using Tensor Networks

Official implementation of spectrum bifurcation renormalization group(SBRG), which is suitable for quantum simulation on strong disordered systems for 1D and 2D. Paper: arXiv:2008.02285[https://arxiv.org/abs/2008.02285], Phys. Rev. B 93, 104205 (2016)[https://arxiv.org/abs/1508.03635]

Source code of Hiperwalk project

A framework for quantum state preparation and tomography. Source code for the paper entitled "Universal compilation for quantum state tomography"

simple quantum virtual machine

An experimental python library to compile and analyze the cost of any desired composite simulation in real or imaginary time, and with or without local interactions. It also contains methods to self optimize simulation parameters for optimal performance.

Reinforcement learning model-free quantum control on many coupled qubits.