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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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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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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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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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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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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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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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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Quantum-Cosmology-Integration
Complete computational framework for cosmological perturbation theory
Quantum-Corrected Cosmological Perturbation Solver License: Dual 🔬 Overview A complete computational framework for cosmological perturbation theory with first-principles quantum corrections. This package implements: Quantum-corrected Mukhanov-Sasaki equations with backreaction from quantum fields Full Boltzmann integration with quantum scattering terms Tensor perturbations (gravitational waves) with quantum sources Integration with CLASS/CAMB for validation Planck 2018 data validation with Bayesian evidence computation Production-ready pipeline for cosmological parameter constraints 🚀 Features Core Physics Quantum stress-energy perturbations using Schwinger-Keldysh formalism Bunch-Davies & α-vacuum initial conditions with quantum corrections Renormalization schemes: adiabatic (4th order), point-splitting, dimensional Self-consistent backreaction between metric and quantum fields -
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PetoronHash-System
PHASH | post-quantum XOF hashing algorithm | C++20
PHASH is a self-contained, dependency-free, post-quantum XOF hashing algorithm implemented in modern C++20. This release delivers the first fully stable production implementation of the PetoronHash-System — a 1600-bit sponge-based hash function with domain separation, extendable output, and deterministic behavior. Key Features No external dependencies — pure C++20 implementation. Extendable Output (XOF) — supports arbitrary output length (256–8192+ bits). Post-quantum oriented design — ARX-based sponge resistant to Grover-type attacks. Context and salt separation — unique hashing domains for each use-case. Optimized performance — ~120–130 MB/s Comprehensive verification — verify_all.sh performs KAT tests, determinism checks, and performance validation. Verification Script: chmod +x verify_all.sh ./verify_all.sh https://github.com/01alekseev/PetoronHash-System Ivan Alekseev | petoron.org -
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PetoronHash2
PH2 Permutation-based cryptographic post-quantum hash library with duplex construction (C++20)
PetoronHash2 (PH2) is a standalone ARX-based sponge construction that combines: A 4096-bit internal permutation core A sponge/duplex architecture with explicit capacity separation An extendable-output function (XOF) Memory-hard (HARD) and burn (BURN) modes A structured tagged absorb scheme A parameterized architecture suitable for hashing, KDF, and stress-oriented derivation PH2 is designed as a wide-state cryptographic primitive with explicit domain separation and configurable output length. https://github.com/01alekseev/PetoronHash2 Petoron | Ivan Alekseev | MIT license -
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Photon-DarkPhoton-Entanglement
Photon Dark Photon
Primordial Photon–Dark Photon Entanglement https://cosmic-entanglement-visualizer-cop-844bebeb.base44.app/ A research and analysis framework for testing the Photon–Dark Photon Entanglement Hypothesis, analyzing astronomical imaging data, and generating reproducible physics validation results using HST, JWST, and other observatory FITS products. 🚀 Overview This repository provides: Physics Validation Tests that compute predicted P–D entanglement observables. Expected Numerical Results for cross‑checking model predictions. Automated pipelines for running analyses on clusters (e.g., Abell 1689) and other astrophysical targets. Jupyter notebooks for full end‑to‑end scientific workflows. Data ingestion tools for MAST/HST/JWST FITS downloads. 📂 Repository Structure Primordial-Photon-Dark-Photon-Entanglement/ ├── Physics_Validation_Tests.py ├── Expected_Numerical_Results.py ├── utils/ │ ├── preprocessing.py -
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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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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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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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<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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Magnetar Quantum Vacuum Engineering
Stellaris QED Engine Quantum Vacuum Engineering
# Stellaris QED Engine ### Quantum Vacuum Engineering for Extreme Astrophysical Environments **A fully functional, real-time, closed-loop simulation of magnetar physics** Now with strong-field QED, dark photon conversion, general relativity, and force-free plasma dynamics — all in pure Python.  ## Current Capabilities (v0.5.0 – 100% complete Month-1 target) | Feature | Status | Description | |----------------------------------|------------|-----------| | Realistic 10¹⁵ G magnetar dipole | Done | 10 km neutron star surface field | | Time-dependent FDTD solver | Done | 2.5D TE-mode wave propagation (leapfrog) | | Euler–Heisenberg nonlinear vacuum| Done | Full strong-field QED corrections | | Dark photon → photon conversion | Done | Field-dependent probability & energy loss | | General relativity | Done | Null geodesic ray tracing -
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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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PDP-OmniSim
PDP-OmniSim simulating parallel and distributed processing systems
PDP-OmniSim 🧬 Scientific Overview PDP-OmniSim is an advanced computational framework for simulating parallel and distributed processing systems, with cutting-edge applications in computational neuroscience, distributed computing, and complex systems modeling. The framework provides researchers with robust tools for large-scale simulations of networked systems and their emergent behaviors. 🎯 Key Scientific Contributions 🔬 Interdisciplinary Research Domains Computational Neuroscience: Large-scale neural population dynamics, brain-inspired computing architectures, and neuro-symbolic AI systems Distributed Systems: Scalable parallel processing simulations, resource allocation optimization, and fault-tolerant computing Complex Systems: Emergent behavior in networked systems, self-organizing criticality, and adaptive network topologies
