Open Source Linux Quantum Computing Software - Page 2

Quantum Computing Software for Linux

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  • 1
    PyQuil

    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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  • 2
    Q-CTRL Open Controls

    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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  • 3
    QPanda 2

    QPanda 2

    QPanda 2 is an open source quantum computing framework

    QPanda2 is an open source quantum computing framework developed by Origin Quantum, which can be used to build, run and optimize quantum algorithms. QPanda2 is the basic library of a series of software developed by Origin Quantum, which provides core components for QRunes, Qurator and quantum computing services.
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  • 4
    Qbsolv

    Qbsolv

    A decomposing solver

    Qbsolv,a decomposing solver, finds a minimum value of a large quadratic unconstrained binary optimization (QUBO) problem by splitting it into pieces solved either via a D-Wave system or a classical tabu solver. (Note that qbsolv by default uses its internal classical solver. Access to a D-Wave system must be arranged separately.)
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  • 5
    QuCAT

    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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  • 6
    QuTiP

    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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  • 7
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  • 8
    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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  • 9
    QNC is a Environment for developing quantum computer simulations.
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  • 10
    Quantum++

    Quantum++

    Modern C++ quantum computing library

    Quantum++ is a modern C++ general-purpose quantum computing library, composed solely of template header files. Quantum++ is written in standard C++17 and has very low external dependencies, using only the Eigen 3 linear algebra header-only template library and, if available, the OpenMP multiprocessing library. Quantum++ is not restricted to qubit systems or specific quantum information processing tasks, being capable of simulating arbitrary quantum processes. The main design factors taken in consideration were ease of use, high portability, and high performance. The library's simulation capabilities are only restricted by the amount of available physical memory. On a typical machine (Intel i5 8Gb RAM) Quantum++ can successfully simulate the evolution of 25 qubits in a pure state or of 12 qubits in a mixed state reasonably fast.
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  • 11
    A graph presentation and manipulation tool for the "CPM construction" quantum graphical calculus.
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  • 12
    ScaffCC

    ScaffCC

    Compilation and optimization framework for the Scaffold language

    ScaffCC is a compiler and scheduler for the Scaffold programing language. It is written using the LLVM open-source infrastructure. It is for the purpose of writing and analyzing code for quantum computing applications. ScaffCC enables researchers to compile quantum applications written in Scaffold to a low-level quantum assembly format (QASM), apply error correction, and generate time and area metrics. It is written to be scalable up to problem sizes in which quantum algorithms outperform classical ones, and as such provide valuable insight into the overheads involved and possible optimizations for a realistic implementation on a future device technology.
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  • 13

    Simuquant

    A quantum circuit simulator written in Scala

    Simuquant is made to construct and simulate universal quantum circuits. It's GUI enables intuitive access and direct graphical feedback, making it useful in a classroom situation and the like. Simulation processing is done in parallel, utilizing parallel collections introduced in scala 2.9. This application has been created as part a bachelor-thesis at the Hamburg University of Applied Sciences. The thesis is available at: http://opus.haw-hamburg.de/volltexte/2012/1843/pdf/ba_dahl.pdf Future plans: - Operator grouping (enables repeated blocks) - Editable library
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  • 14
    Superstaq

    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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  • 15
    Tequila

    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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  • 16
    TorchQuantum

    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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  • 17
    Yao

    Yao

    Extensible, Efficient Quantum Algorithm Design for Humans

    An intermediate representation to construct and manipulate your quantum circuit and let you make own abstractions on the quantum circuit in native Julia. Yao supports both forward-mode (faithful gradient) and reverse-mode automatic differentiation with its builtin engine optimized specifically for quantum circuits. Top performance for quantum circuit simulations. Its CUDA backend and batched quantum register support can make typical quantum circuits even faster. Yao is designed to be extensible. Its hierarchical architecture allows you to extend the framework to support and share your new algorithm and hardware.
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  • 18
    New project name is Atomlight. https://sourceforge.net/projects/atomlight
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  • 19
    This is a set of octave-functions to simulate grover's quantum search algorithm in which we introduce spontaneously decaying qubits. See http://arxiv.org/abs/quant-ph/0609047. This is a modification to account for multiple item searching.
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  • 20

    ossGathering

    ossGathering collects information of the open source software.

    ossGathering collects information of the open source software. And shows the information that is collected in a variety of ways.
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  • 21
    qaqarot

    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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  • 22
    Package quantum-octave is a set of GNU Octave functions for simulating quantum computers.
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  • 23
    staq

    staq

    Full-stack quantum processing toolkit

    staq is a modern C++ library for the synthesis, transformation, optimization and compilation of quantum circuits. staq is written in standard C++17 and has very low external dependencies. It is usable either through the provided binary tools, or as a header-only library that can be included to provide direct support for parsing & manipulating circuits written in the OpenQASM circuit description language. Inspired by Clang, staq is designed to manipulate OpenQASM syntax trees directly, rather than through an intermediate representation which makes retrieving the original source code impossible. In particular, OpenQASM circuits can be inspected and transformed (in most cases) without losing the original source structure. This makes staq ideally suited for source-to-source transformations, where only specific changes are desired. Likewise, this allows translations to other common circuit description languages and libraries to closely follow the OpenQASM source.
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