Tools & Practice

IBM's open-source SDK for programming quantum computers. Features circuit construction, transpilation, simulation, and access to IBM quantum hardware.

Google's open-source framework for designing, simulating, and running quantum circuits on NISQ devices. Strong noise modeling capabilities.

AWS's open-source SDK for building quantum algorithms and running them on multiple hardware backends (IonQ, Rigetti, D-Wave).

Rigetti's SDK featuring the Quil quantum instruction language and the pyQuil library for hybrid quantum-classical computing.

Quantinuum's high-performance quantum SDK with advanced circuit optimization, retargeting to multiple hardware backends, and a comprehensive toolchain.

Microsoft's quantum programming SDK with the Q# language, resource estimation, and integration with Azure Quantum services.

D-Wave's open-source SDK for quantum annealing and hybrid quantum-classical solvers, with tools for optimization and sampling problems.

Cross-platform quantum machine learning library with automatic differentiation. Integrates with PyTorch, TensorFlow, and JAX for hybrid QML workflows. Also functions as a full QML framework.

A full-stack quantum computing framework for quantum simulation, hardware control, and quantum algorithm development with accelerator support.

A high-performance quantum computing framework written in Julia, offering flexible quantum circuit construction and GPU-accelerated simulation.

A Julia framework for simulating quantum optical systems and open quantum systems, including master equations and Monte Carlo simulations.

A powerful open-source library for simulating quantum systems, including master equations, Bloch-Redfield, and quantum stochastic processes.

Microsoft's domain-specific programming language for quantum computing. Part of the Azure Quantum Development Kit.

A scalable, functional programming language for quantum computing embedded in Haskell. Used for circuit description and verification.

An intermediate quantum instruction language developed by Rigetti, designed for hybrid quantum-classical computing.

IBM's open-source quantum assembly language for describing quantum circuits and protocols, widely adopted across quantum platforms.

A high-level quantum programming language with an intuitive type system and automatic uncomputation, designed for safe quantum programming.

A fast stabilizer circuit simulator for quantum error correction research. Can handle millions of measurement rounds per second.

Google's high-performance quantum circuit simulator with support for multi-threading and GPU acceleration.

A fast quantum circuit simulator written in C++ with Python bindings, supporting GPU acceleration and variational algorithm simulation.

A Python library for quantum information and many-body calculations, featuring tensor networks, quantum circuits, and entanglement measures.

An open-source quantum computing framework with powerful compilation capabilities, supporting various hardware backends and high-performance simulation.

A high-performance GPU-accelerated quantum simulator written in C++ with support for OpenCL, CUDA, and multi-threaded CPU simulation.

IBM's high-performance Qiskit Aer simulator for quantum circuits, supporting noise models, GPU acceleration, and circuit optimization.

The most popular free browser-based visual quantum circuit simulator. Drag-and-drop gates, instant statevector updates, and shareable circuit URLs. No account or installation needed.

Unitary Fund's open-source error mitigation toolkit. Implements zero-noise extrapolation, probabilistic error cancellation, Clifford data regression, and more.

A fast Python/C++ library for decoding quantum error correcting codes using Minimum Weight Perfect Matching (MWPM) on the surface code.