Quantum random numbers in Python
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Updated
May 26, 2024 - Python
Quantum computing is a field of computing that uses quantum phenomena such as superposition and entanglement to perform operations on data. It is a rapidly growing field with potential applications in fields such as cryptography, chemistry, and optimization. Quantum computers can solve certain problems much faster than classical computers. Various programming languages such as Q#, Python and C++ can be used to write quantum algorithms to be run on quantum computers. The development of quantum computers is an active area of research and engineering.
Quantum random numbers in Python
Pythonic tool for orchestrating machine-learning/high performance/quantum-computing workflows in heterogeneous compute environments.
Python data acquisition toolbox for measurements on quantum systems
Qiskit is an open-source SDK for working with quantum computers at the level of extended quantum circuits, operators, and primitives.
PennyLane is a cross-platform Python library for quantum computing, quantum machine learning, and quantum chemistry. Train a quantum computer the same way as a neural network.
A JIT compiler for hybrid quantum programs in PennyLane
measurement-based quantum computing (MBQC) compiler and simulator
A python-to-quantum compiler
Public repo for /azure/quantum documentation. For private repo, see quantum-docs-private (MS FTE only)
Machine learning algorithms for many-body quantum systems
|toqito> (Theory of Quantum Information Toolkit) in Python 🐍
The azure-quantum python package submits jobs to the Azure Quantum service.
A python library for quantum information and many-body calculations including tensor networks.
A platform-agnostic quantum runtime framework
QuTiP: Quantum Toolbox in Python
MPQP is a python library to create quantum circuits and run them on a multitude of backends from various providers.
A framework for quantum computing
Created by Richard Feynman and Yuri Manin