Open Source Python Quantum Computing Software for Linux
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Python Quantum Computing Software for Linux
View 6 business solutionsBrowse free open source Python Quantum Computing Software for Linux and projects below. Use the toggles on the left to filter open source Python Quantum Computing Software for Linux by OS, license, language, programming language, and project status.
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Qiskit
Qiskit is an open-source SDK for working with quantum computers
Qiskit [kiss-kit] is an open-source SDK for working with quantum computers at the level of pulses, circuits, and application modules. When you are looking to start Qiskit, you have two options. You can start Qiskit locally, which is much more secure and private, or you get started with Jupyter Notebooks hosted in IBM Quantum Lab. Qiskit includes a comprehensive set of quantum gates and a variety of pre-built circuits so users at all levels can use Qiskit for research and application development. The transpiler translates Qiskit code into an optimized circuit using a backend’s native gate set, allowing users to program for any quantum processor or processor architecture with minimal inputs. Users can run and schedule jobs on real quantum processors, and employ Qiskit Runtime to orchestrate quantum programs on cloud-based CPUs, QPUs, and GPUs. -
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QuTiP
QuTiP: Quantum Toolbox in Python
QuTiP is open-source software for simulating the dynamics of open quantum systems. The QuTiP library depends on the excellent Numpy, Scipy, and Cython numerical packages. In addition, graphical output is provided by Matplotlib. QuTiP aims to provide user-friendly and efficient numerical simulations of a wide variety of Hamiltonians, including those with arbitrary time-dependence, commonly found in a wide range of physics applications such as quantum optics, trapped ions, superconducting circuits, and quantum nanomechanical resonators. QuTiP is freely available for use and/or modification on all major platforms such as Linux, Mac OSX, and Windows*. Being free of any licensing fees, QuTiP is ideal for exploring quantum mechanics and dynamics in the classroom. -
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Cirq
A python framework for creating, editing, and invoking NISQ
Cirq is a Python library for writing, manipulating, and optimizing quantum circuits and running them against quantum computers and simulators. -
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Paddle Quantum
Paddle Quantum
Paddle Quantum (量桨) is the world's first cloud-integrated quantum machine learning platform based on Baidu PaddlePaddle. It supports the building and training of quantum neural networks, making PaddlePaddle the first deep-learning framework in China. Paddle Quantum is feature-rich and easy to use. It provides comprehensive API documentation and tutorials help users get started right away. Paddle Quantum aims at establishing a bridge between artificial intelligence (AI) and quantum computing (QC). It has been utilized for developing several quantum machine learning applications. With the PaddlePaddle deep learning platform empowering QC, Paddle Quantum provides strong support for the scientific research community and developers in the field to easily develop QML applications. Moreover, it provides a learning platform for quantum computing enthusiasts. -
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Perceval
An open source framework for programming photonic quantum computers
An open-source framework for programming photonic quantum computers. Through a simple object-oriented Python API, Perceval provides tools for composing circuits from linear optical components, defining single-photon sources, manipulating Fock states, running simulations, reproducing published experimental papers and experimenting with a new generation of quantum algorithms. It aims to be a companion tool for developing photonic circuits – for simulating and optimizing their design, modeling both the ideal and realistic behaviors, and proposing a normalized interface to control them through the concept of backends. -
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ProjectQ
An open source software framework for quantum computing
ProjectQ is an open-source effort for quantum computing. It features a compilation framework capable of targeting various types of hardware, a high-performance quantum computer simulator with emulation capabilities, and various compiler plug-ins. -
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Q-CTRL Open Controls
Q-CTRL Open Controls
Q-CTRL Open Controls is an open-source Python package that makes it easy to create and deploy established error-robust quantum control protocols from the open literature. The aim of the package is to be the most comprehensive library of published and tested quantum control techniques developed by the community, with easy-to-use export functions allowing users to deploy these controls on. -
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Superstaq
Quantum software platform that is optimized across the quantum stack
This repository is the home of the Superstaq development team's open-source work. Our quantum software platform is optimized across the quantum stack and enables users to write quantum programs in Cirq or Qiskit and target a variety of quantum computers and simulators. -
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BQSKit
Berkeley Quantum Synthesis Toolkit
The Berkeley Quantum Synthesis Toolkit (BQSKit) [bis • kit] is a powerful and portable quantum compiler framework. It can be used with ease to compile quantum programs to efficient physical circuits for any QPU. A standard workflow utilizing BQSKit consists of loading a program into the framework, modeling the target QPU, compiling the program, and exporting the resulting circuit. -
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A python package that allows scientists to easily create configurable and reusable experiments. Intended for use with the LabRAD framework. Developed by the Haeffner group studying quantum simulation at UC Berkeley. Wiki at lrexp.wikispaces.com
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Mitiq
Mitiq is an open source toolkit for implementing error mitigation
Mitiq is a Python toolkit for implementing error mitigation techniques on quantum computers. Current quantum computers are noisy due to interactions with the environment, imperfect gate applications, state preparation and measurement errors, etc. Error mitigation seeks to reduce these effects at the software level by compiling quantum programs in clever ways. -
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OpenFermion
The electronic structure package for quantum computers
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. Currently, OpenFermion is tested on Mac, Windows, and Linux. We recommend using Mac or Linux because the electronic structure plugins are only compatible on these platforms. However, for those who would like to use Windows, or for anyone having other difficulties with installing OpenFermion or its plugins, we have provided a Docker image and usage instructions in the docker folder. The Docker image provides a virtual environment with OpenFermion and select plugins pre-installed. The Docker installation should run on any operating system. -
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OpenQASM
Quantum assembly language for extended quantum circuits
OpenQASM is an imperative programming language designed for near-term quantum computing algorithms and applications. Quantum programs are described using the measurement-based quantum circuit model with support for classical feed-forward flow control based on measurement outcomes. OpenQASM presents a parameterized set of physical logic gates and concurrent real-time classical computations. Its main goal is to serve as an intermediate representation for higher-level compilers to communicate with quantum hardware. Allowances have been made for human usability. In particular, the language admits different representations of the same program as it is transformed from a high-level description to a pulse representation. -
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PyQuil
A Python library for quantum programming using Quil
PyQuil is a Python library for quantum programming using Quil, the quantum instruction language developed at Rigetti Computing. PyQuil serves three main functions. PyQuil has a ton of other features, which you can learn more about in the docs. However, you can also keep reading below to get started with running your first quantum program. Without installing anything, you can quickly get started with quantum programming by exploring our interactive Jupyter Notebook tutorials and examples. To run them in a preconfigured execution environment on Binder, click the "launch binder" badge at the top of the README or the link here! To learn more about the tutorials and how you can add your own, visit the rigetti/forest-tutorials repository. If you'd rather set everything up locally, or are interested in contributing to pyQuil, continue to the next section for instructions on installing pyQuil and the Forest SDK. -
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QuCAT
Quantum Circuit Analyzer Tool
QuCAT stands for Quantum Circuit Analyzer Tool. This open source python library provides standard analysis tools for superconducting electronic circuits, built around Josephson junctions. QuCAT features an intuitive graphical or programmatical interface to create circuits, the ability to compute their Hamiltonian, and a set of complimentary functionalities such as calculating dissipation rates or visualizing current flows in the circuit. QuCAT currently supports quantization in the basis of normal modes. -
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Quantum Information Toolkit is a comprehensive, easy-to-use interactive numerical toolkit for quantum information and computing, available for both MATLAB and Python.
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Tequila
A High-Level Abstraction Framework for Quantum Algorithms
Tequila is an abstraction framework for (variational) quantum algorithms. It operates on abstract data structures allowing the formulation, combination, automatic differentiation and optimization of generalized objectives. Tequila can execute the underlying quantum expectation values on state-of-the-art simulators as well as on real quantum devices. -
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TorchQuantum
A PyTorch-based framework for Quantum Classical Simulation
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. Researchers on quantum algorithm design, parameterized quantum circuit training, quantum optimal control, quantum machine learning, and quantum neural networks. Dynamic computation graph, automatic gradient computation, fast GPU support, batch model terrorized processing. -
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qaqarot
Quantum Computer Library for Everyone
The Blueqat project has been renamed the Qaqarot Project because of the branding strategy of blueqat inc.
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