Showing 9 open source projects for "framework-3-offline"

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  • 1
    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.
    Downloads: 1 This Week
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  • 2
    BQSKit

    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.
    Downloads: 0 This Week
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  • 3
    Perceval

    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.
    Downloads: 0 This Week
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  • 4
    Cirq

    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.
    Downloads: 0 This Week
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  • 5
    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. ...
    Downloads: 0 This Week
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  • 6
    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.
    Downloads: 0 This Week
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  • 7
    Paddle Quantum

    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. ...
    Downloads: 0 This Week
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  • 8
    ProjectQ

    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.
    Downloads: 0 This Week
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  • 9
    LabRAD Experimenter
    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
    Downloads: 0 This Week
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