QuantumFlow began life in late 2017 as an internal project at Rigetti Computing to explore quantum machine learning on near-term quantum computers. Many people have contributed either directly or indirectly.
QuantumFlow's model of hybrid quantum-classical programming is taken from Quil, Rigetti's quantum programming language detailed in A Practical Quantum Instruction Set Architecture, written by Robert S. Smith, Michael J. Curtis, and William J. Zeng [1]. Much code was borrowed from pyQuil and Rigetti's Grove, originally written by Robert Smith, Will Zeng, and Spike Curtis, with significant contributions from Anthony Polloreno, Peter Karalekas, Nikolas Tezak, Chris Osborn, Steven Heidel, and Matt Harrigan (among others). The quil parser is adapted from the python parser written by Steven Heidel. QuantumFlow's latex generation code was inspired by Anthony Polloreno's quil to latex module. Construction of the decomposition module was assisted by Eric C. Peterson (Of ECP gate fame), and Josh Combes made contributions to the measures module. Diamond norm was adapted from code originally written by Marcus P. da Silva. Keri McKerinan and Chris M. Wilson were early beta testers. And finally Nick Rubin undoubtably has the single greatest contribution, as the gate definitions, Kraus operators, and simulation model were all adapted from his reference-qvm [2].
Gavin E. Crooks (2018-11-01)
[1] A Practical Quantum Instruction Set Architecture Robert S. Smith, Michael J. Curtis, William J. Zeng arXiv:1608.03355 https://arxiv.org/abs/1608.03355
[2] reference-qvm: A reference implementation for a quantum virtual machine in Python https://github.com/rigetticomputing/reference-qvm