Simulating non-Gaussian quantum state preparation with loss via the fastest known classical method to calculate loop hafnians.
This repository contains the source code used to produce the results presented in "Simulating realistic non-Gaussian state preparation" Phys. Rev. A 100, 022341 (2019)
The included script cubic_phase.py uses the loop hafnian algorithm to explore the loss
parameter space of a heralded weak cubic phase state, as given in
Phys. Rev. A 100, 022341 (2019). The script generates
contour plots of the resulting fidelity, Wigner Log Negativity, and probability as a function
of heralding and heralded loss.
To perform the quantum state preparation and parameter search, the script uses the Gaussian backend of Strawberry Fields, the The Walrus library is required for loop hafnian evaluation, and matplotlib for graph generation.
All of these prerequisites can be installed via pip:
pip install strawberryfields thewalrus matplotlibNicolás Quesada, Luke Helt, Josh Izaac, Juan Miguel Arrazola, Rahaneh Shahrokhshahi, Casey Myers, and Krishna Kumar Sabapathy.
If you are doing any research using this source code, the Hafnian library, and Strawberry Fields, please cite the following three papers:
Nicolás Quesada, Luke Helt, Josh Izaac, Juan Miguel Arrazola, Rahaneh Shahrokhshahi, Casey Myers, and Krishna Kumar Sabapathy. "Simulating realistic non-Gaussian state preparation", Phys. Rev. A 100, 022341 (2019).
Andreas Björklund, Brajesh Gupt, and Nicolás Quesada. "A faster hafnian formula for complex matrices and its benchmarking on the Titan supercomputer", Journal of Experimental Algorithmics (JEA) 24.1 (2019): 11.
Nathan Killoran, Josh Izaac, Nicolás Quesada, Ville Bergholm, Matthew Amy, and Christian Weedbrook. "Strawberry Fields: A Software Platform for Photonic Quantum Computing", Quantum, 3, 129 (2019).
This source code is free and open source, released under the Apache License, Version 2.0.