Open Source Mac Quantum Computing Software
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Quantum Computing Software for Mac
View 5 business solutionsBrowse free open source Quantum Computing software and projects for Mac below. Use the toggles on the left to filter open source Quantum Computing software 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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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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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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Azure Quantum Development Kit
Azure Quantum Development Kit
Azure Quantum Development Kit, including the Q# programming language, resource estimator, and Quantum Katas. The playground is a small website that loads the Q# editor, compiler, samples, katas, and documentation for the standard library. It's a way to manually validate any changes you make to these components. The easiest way to develop in this repo is to use VS Code. When you open the project root, by default VS Code will recommend you install the extensions listed in .vscode/extensions.json. These extensions provide language services for editing, as well as linters and formatters to ensure the code meets the requirements (which are checked by the build.py script and CI). -
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Qulacs
Variational Quantum Circuit Simulator for Quantum Computation Research
Variational Quantum Circuit Simulator for Quantum Computation Research. Qulacs is a Python/C++ library for fast simulation of large, noisy, or parametric quantum circuits. Qulacs is developed at QunaSys, Osaka University, NTT, and Fujitsu. -
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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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CUDA-Q
C++ and Python support for the CUDA Quantum programming model
CUDA-Q is an open-source platform for developing hybrid quantum-classical applications using a unified programming model across CPUs, GPUs, and quantum processing units. It provides a full toolchain that includes compilers, runtimes, and libraries for writing quantum programs in both C++ and Python. The platform is designed to be hardware-agnostic, allowing developers to run applications on different quantum backends or simulate them efficiently using GPU acceleration when physical quantum hardware is unavailable. It enables complex workflows where classical and quantum computations are tightly integrated, supporting advanced research and real-world applications in quantum computing. The repository includes components such as the nvq++ compiler and runtime systems that manage execution across heterogeneous environments. -
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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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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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A C/C++ library for Cavity Quantum Electrodynamics Simulations. CQEDSimulator is a framework that provides all basic mathematical elements and methods to perform quantum numerical simulations. It's crossplatform, that works on Windows, Linux, Mac...
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AnharmoniCAOS
Cagliari-Orsay model for anharmonic molecular spectra in 2nd order PT
Given dynamical coefficients and/or derivatives of the ionic potential with respect to normal (harmonic) vibrational modes, compute anharmonic energies and electric dipole-permitted transitions and intensities using nearly-degenerate perturbation theory (i.e. properly accounting for Fermi and Darling-Dennison resonances). -
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3 levels density matrix simulation. Currently it enables you to get time solvetions for three-level systems. It's generates files with time solvetions for density matrix. In the future It will solve multilevel atomic system on MPI.
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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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CUDA-QX
Accelerated libraries for quantum-classical computing built on CUDA-Q
CUDA-QX is a collection of accelerated libraries built on top of the CUDA-Q platform, designed to enable rapid development of hybrid quantum-classical applications. It extends the CUDA-Q programming model by providing optimized implementations of domain-specific quantum computing primitives and workflows. The libraries are intended to help researchers and developers leverage GPUs, CPUs, and quantum processing units together in a unified computational model. CUDA-QX focuses on key areas such as quantum error correction and hybrid solver algorithms, offering high-level APIs that simplify complex quantum workflows. By abstracting low-level details and providing ready-to-use components, it accelerates experimentation and development in quantum computing research. The project is part of NVIDIA’s broader effort to enable scalable quantum-classical computing systems through hardware-agnostic programming models. -
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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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<Temporarily Unavailable Online> This project is aiming at completing a library of open codes (mainly based on MATLAB at present) to deal with Dipoles-Cavity Interaction problems. Common methods, including Green's function method and Master Equation method et al, will be applied to the coding. Samples of calculations and standard comparison with publications using the library will be given for demonstration of the usage. Interface to some commonly used software, such as Lumerical FDTD Solutions, will also be developed in the project. This project is titled under nanophotonics, quantum optics, nano-optics, computational physics and physics.
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Repository moving to https://github.com/cmendl/fermifab ! A quantum physics toolbox for small fermionic systems. Keywords: quantum mechanics, reduced density matrices, Slater determinants, second quantization, creation and annihilation operators
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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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Matrix Product State (MPS) Simulations
Numerical routines for variational matrix product state simulations.
Open Source MPS (OSMPS) is a collection of numerical routines for performing tensor network algorithms to simulate entangled, 1D many-body quantum systems. Our applications reach from ground state and excited states for statics to the dynamics of time-dependent Hamiltonians. We offer various time evolution methods with an emphasis on the support of long-range interactions through the matrix product state formalism. For more algorithms, see the list of features below. Please cite "M. L. Wall and L. D. Carr, New J. Phys. 14, 125015 (2012)" and "D. Jaschke, M. L. Wall, and L. D. Carr, Computer Physics Communications 225, 59–91 (2018)" if your publication involves OSMPS. -
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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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NBO Analyzer
Analyze output of NBO computations
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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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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.
