This document is a list of projects that have been developed using the Forest quantum programming enviornment.
Please read the contribution guidelines before contributing.
pyQuil - [Python] The core development library for working with Forest and Quil on QVMs and QPUs.
jsquil - [JavaScript] A JavaScript wrapper for the Forest API.
Hasquil - [Haskell] A Haskell library for representing Quil programs. (blog post)
jquil - [Java] A Java library for quantum programming using Quil.
forestopenfermion - [Python] A library for interfacing Forest with OpenFermion, a Python library for quantum simulations on quantum computers.
XaCC-rigetti - [Python] A library for interfacing Forest as a backend in the XaCC quantum programming framework.
qasm2pyQuil - [Javascript] A web library for converting OpenQASM code to pyQuil.
reference-qvm - [Python] A lightweight implementation of a quantum virtual machine.
oqaml - [OCaml] Another lightweight quantum virtual machine implementation.
grove - [Python] A core algorithm and application library with examples of quantum algorithms including the variational quantum eigensolver and the quantum approximate optimization algorithm.
Du, Yuxuan et al. (2018) Implementable Quantum Classifier for Nonlinear Data - arXiv
Khatri, Sumeet et al. (2018) Quantum Assisted Quantum Compiling - arXiv
Verdon, Guillaume et al. (2018) Universal Training Algorithm for Quantum Deep Learning - arXiv
Zhao et al. (2018) Bayesian Deep Learning on a Quantum Computer - arXiv
Lamm & Lawrence (2018) Simulation of Nonequilibrium Dynamics on a Quantum Computer - arXiv
Otten & Gray (2018) Recovering noise-free quantum observables - arXiv
Ryabinkin, Ilya et al. (2018) Constrained variational quantum eigensolver: Quantum computer search engine in the Fock space - arXiv
Du, Yuxuan et al. (2018) Bayesian Quantum Circuit - arXiv
Babej, Tomas et al. (2018) A quantum alternating operator ansatz with hard and soft constraints for lattice protein folding - link
Cincio, Lukasz et al. (2018) Learning the quantum algorithm for state overlap - arXiv
Dumitrescu, E. F. et al. (2018) Cloud Quantum Computing of an Atomic Nucleus - arXiv
Otterbach, J. S. et al. (2017) Unsupervised Machine Learning on a Hybrid Quantum Computer - arXiv
Verdon, Guillame et al. (2017) A quantum algorithm to train neural networks using low depth circuits - arXiv
Rubin, Nicholas C. (2016) A Hybrid Classical/Quantum Approach for Large-Scale Studies of Quantum Systems with Density Matrix Embedding Theory - arXiv
Introductory quantum algorithms blog - Part [1][2][3]
A Link to Quantum - [Python] Collection of mini video-games that run on a quantum computer.
QCompress - [Python] Implementation and demonstration of the quantum autoencoder using Forest and OpenFermion.
For a list of open source quantum software projects in general check out this great list.