Displaying 1 to 20 from 31 results

qiskit-terra - Terra provides the foundations for Qiskit

  •    Python

The Quantum Information Science Kit (Qiskit for short) is a software development kit (SDK) for working with OpenQASM and the IBM Q Experience (QX). Use Qiskit to create quantum computing programs, compile them, and execute them on one of several backends (online Real quantum processors, online simulators, and local simulators). For the online backends, Qiskit uses our python API client to connect to the IBM Q Experience.

Cirq - A python framework for creating, editing, and invoking Noisy Intermediate Scale Quantum (NISQ) circuits

  •    Python

Cirq is a Python library for writing, manipulating, and optimizing quantum circuits and running them against quantum computers and simulators. Follow these instructions.

pyquil - A Python library for quantum programming using Quil.

  •    Python

Please Note: PyQuil, along with quilc, the QVM, and other libraries, make up what is called the Forest SDK. To make full use of pyQuil's functionality, you will need to additionally have installed quilc and the QVM. This can be done by following their respective READMEs, or by downloading them as binaries from here. PyQuil can be installed using conda, pip, or directly from source.

pyquil - A Python library for quantum programming using Quil.

  •    Python

A library for easily generating Quil programs to be executed using the Rigetti Forest platform. pyQuil is licensed under the Apache 2.0 license. pyQuil can be used to build and manipulate Quil programs without restriction. However, to run programs (e.g., to get wavefunctions, get multishot experiment data), you will need an API key for Rigetti Forest. This will allow you to run your programs on the Rigetti Quantum Virtual Machine (QVM) or on a real quantum processor (QPU).




OpenFermion - The electronic structure package for quantum computers.

  •    Python

OpenFermion is an open source library for compiling and analyzing quantum algorithms to simulate fermionic systems, including quantum chemistry. Among other functionalities, this version features data structures and tools for obtaining and manipulating representations of fermionic and qubit Hamiltonians. For more information, see our release paper. Installing OpenFermion requires pip. Make sure that you are using an up-to-date version of it. For information about getting started beyond what is provided below please see our tutorial in the examples folder as well as our detailed code documentation.

qiskit-api-py - A Python library for the Quantum Experience API

  •    Python

The official API Client to use IBM Quantum Experience in Python. This package can be used in Jupyter Notebook.

qiskit-tutorial - A collection of Jupyter notebooks using Qiskit

  •    Jupyter

In this repository, we've put together a collection of Jupyter notebooks aimed at teaching people who want to use the QISKit for writing quantum computing programs and executing them on one of several backends (online quantum processors, online simulators, and local simulators). The online quantum processors connects to the IBM Q devices. Please refer to this installation for installing and setting up QISKit and tutorials on your own machine.

openqasm - Gate and operation specification for quantum circuits

  •    TeX

Specs, examples and tools for the OpenQASM intermediate representation. The latest version is: 2.0.


grove - Quantum algorithms built using pyQuil.

  •    Python

A collection of quantum algorithms built using the Rigetti Forest platform. Grove is licensed under the Apache 2.0 license. Features in the alpha package are considered experimental.

qsel - Quantum programming language putting entanglement and superposition front and center

  •    Python

What makes quantum computers more powerful than classical computers? Ask any expert, or watch any public lecture on the subject and the answer is clear. Entanglement and Superposition are what give quantum computers their power over classical computers. If these two ideas are at the heart of the power of quantum computing, it therefore makes sense that any programing language for quantum computing should make these two ideas front and center. This is where Quantum Super Entangled Language (qsel) comes in. It is a quantum programming language made entirely from superposition and entanglement. where your measurement results may be different.

Quirk - A drag-and-drop quantum circuit simulator that runs in your browser

  •    Javascript

Quirk is a toy quantum circuit simulator, intended to help people in learning about quantum computing. If you want to quickly explore the behavior of a small quantum circuit, Quirk is the tool for you. There's no installing or configuring or scripting: just go to algassert.com/quirk, drag gates onto the circuit, and the output displays will update in real time.

jsquil - Quantum computer instructions for JavaScript developers

  •    Javascript

JavaScript interface for writing Quil programs, based on Rigetti Computing's pyQuil package. Make a list of instructions to run on a hybrid computer with both qubits and classical registers, and then use the measure instruction to store a qubit value onto a classical register.

cl-forest - Unofficial bindings to Rigetti Forest in Common Lisp.

  •    Common

Unofficial bindings to Rigetti Forest, a quantum computing service. These bindings are directly based off of the forest module of pyQuil. Currently, this library is written for pedagogical example of the API, not for efficiency.

grove - Quantum algorithms built using pyQuil

  •    Python

A collection of quantum algorithms built using the Rigetti Forest platform. Grove is licensed under the Apache 2.0 license. Features in the alpha package are considered experimental.

ibmqx-user-guides - The users guides for the IBM Q experience

  •    HTML

If quantum physics sounds challenging to you, you are not alone. All of our intuitions are based on day-to-day experiences and are defined by classical physics — so most of us find the concepts in quantum physics counterintuitive at first. In order to comprehend the quantum world, you must let go of your beliefs about our physical world, and develop an intuition for a completely different (and often surprising) set of laws. The guide is divided in two.

qiskit-vscode - Simplifying Qiskit to make developing quantum circuits and applications faster

  •    HTML

Simplifying Qiskit to make developing quantum circuits and applications faster. A Visual Studio Code extension with support for Qiskit and the OpenQASM language. It provides some useful commands to make easier launching jobs and visualizing results among others.

qiskit.org - The Qiskit official website

  •    Javascript

Qiskit is an open source framework for quantum computing. It allows users to create, compile, and execute quantum computing programs online, either in a simulator, or in a real IBM Q quantum processor.

QMLT - The Quantum Machine Learning Toolbox (QMLT) is a Strawberry Fields application that simplifies the optimization of variational quantum circuits (also known as parametrized quantum circuits)

  •    Python

The Quantum Machine Learning Toolbox (QMLT) is a Strawberry Fields application that simplifies the optimization of variational quantum circuits. Tasks for the QMLT range from variational eigensolvers and unitary learning to supervised and unsupervised machine learning with models based on a variational circuit. To get started, please see the online documentation.

quantum-learning - This repository contains the source code used to produce the results presented in the paper "Machine learning method for state preparation and gate synthesis on photonic quantum computers"

  •    Jupyter

This repository contains the source code used to produce the results presented in "Machine learning method for state preparation and gate synthesis on photonic quantum computers" arXiv:1807.10781. state_learner.py: a Python script to automate quantum state learning using continuous-variable (CV) variational quantum circuits. Simply specify your one- or two-mode target state, along with other hyperparameters, and this script automatically constructs and optimizes the variational quantum circuit.

SFOpenBoson - A plugin for Strawberry Fields and OpenFermion, providing methods of simulating bosonic Hamiltonians directly in Strawberry Fields

  •    Python

This Strawberry Fields plugin library allows Strawberry Fields to interface with OpenFermion. Strawberry Fields is a full-stack Python library for designing, simulating, and optimizing continuous variable (CV) quantum optical circuits.