Compare the Top Quantum Computing Software for Linux as of November 2024

What is Quantum Computing Software for Linux?

Quantum computing software is designed to simulate quantum systems. It enables developers to explore the potential of quantum computing and can be used for a variety of applications such as cryptography, search optimization, materials simulation, machine learning and artificial intelligence. Quantum computers are powered by algorithms that use qubits instead of classical bits which allow them to calculate with a much higher speed than regular computers. The open-source nature of many quantum computing software packages allows anyone who has an interest in this technology to create projects and new algorithms. Compare and read user reviews of the best Quantum Computing software for Linux currently available using the table below. This list is updated regularly.

  • 1
    TensorFlow

    TensorFlow

    TensorFlow

    An end-to-end open source machine learning platform. TensorFlow is an end-to-end open source platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries and community resources that lets researchers push the state-of-the-art in ML and developers easily build and deploy ML powered applications. Build and train ML models easily using intuitive high-level APIs like Keras with eager execution, which makes for immediate model iteration and easy debugging. Easily train and deploy models in the cloud, on-prem, in the browser, or on-device no matter what language you use. A simple and flexible architecture to take new ideas from concept to code, to state-of-the-art models, and to publication faster. Build, deploy, and experiment easily with TensorFlow.
    Starting Price: Free
  • 2
    InQuanto

    InQuanto

    Quantinuum

    Quantum computing offers a path forward to rapid and cost-effective development of new molecules and materials. InQuanto, a state-of-the-art quantum computational chemistry platform, represents a critical step toward this goal. Quantum chemistry aims to accurately describe and predict the fundamental properties of matter and hence is a powerful tool in the design and development of new molecules and materials. However, molecules and materials of industrial relevance are complex and not easy to accurately simulate. Today’s capabilities force a trade to either use highly accurate methods on the smallest-sized systems or use approximating techniques. InQuanto’s modular workflow enables both computational chemists and quantum algorithm developers to easily mix and match the latest quantum algorithms with advanced subroutines and error mitigation techniques to get the best out of today’s quantum platforms.
  • 3
    LIQUi|>

    LIQUi|>

    Microsoft

    LIQUi|> is a software architecture and tool suite for quantum computing. It includes a programming language, optimization and scheduling algorithms, and quantum simulators. LIQUi|> can be used to translate a quantum algorithm written in the form of a high-level program into the low-level machine instructions for a quantum device. LIQUi|> is being developed by the quantum architectures and computation Group (QuArC) at Microsoft Research. To aid in the development and understanding of quantum protocols, quantum algorithms, quantum error correction, and quantum devices, QuArC has developed an extensive software platform called LIQUi|>. LIQUi|> allows the simulation of Hamiltonians, quantum circuits, quantum stabilizer circuits, and quantum noise models, and supports client, service, and cloud operation.
  • 4
    QX Simulator

    QX Simulator

    Quantum Computing Simulation

    The realization of large-scale physical quantum computers appears to be challenging, alongside the efforts to design quantum computers, significant efforts are focusing on the development of useful quantum algorithms. In the absence of a large physical quantum computer, an accurate software simulation of quantum computers on a classical computer is required to simulate the execution of those quantum algorithms and to study the behavior of a quantum computer and improve its design. Besides simulating error-free execution quantum circuits on a perfect quantum computer, the QX simulator can simulate realistic noisy execution using different error models such as the depolarizing noise. The user can activate the error model and define a physical error probability to simulate a specific target quantum computer. This error rate can be defined based on the gate fidelity and the qubit decoherence of the target platform.
  • 5
    QuEST

    QuEST

    QuEST

    The Quantum exact simulation toolkit is a high-performance simulator of quantum circuits, state-vectors and density matrices. QuEST uses multithreading, GPU acceleration and distribution to run lightning first on laptops, desktops and networked supercomputers. QuEST just works; it is stand-alone, requires no installation, and is trivial to compile and get running. QuEST has no setup; it can be downloaded, compiled and run in a matter of seconds. QuEST has no external dependencies and compiles natively on Windows, Linux and MacOS. Whether on a laptop, a desktop, a supercomputer, a microcontroller, or in the cloud, you can almost always get QuEST running with only a few terminal commands.
  • 6
    Bayesforge

    Bayesforge

    Quantum Programming Studio

    Bayesforge™ is a Linux machine image that curates the very best open source software for the data scientist who needs advanced analytical tools, as well as for quantum computing and computational mathematics practitioners who seek to work with one of the major QC frameworks. The image combines common machine learning frameworks, such as PyTorch and TensorFlow, with open source software from D-Wave, Rigetti as well as the IBM Quantum Experience and Google's new quantum computing language Cirq, as well as other advanced QC frameworks. For instance our quantum fog modeling framework, and our quantum compiler Qubiter which can cross-compile to all major architectures. All software is made accessible through the Jupyter WebUI which, due to its modular architecture, allows the user to code in Python, R, and Octave.
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