Extensible, Efficient Quantum Algorithm Design for Humans.
-
Updated
Jul 8, 2024 - Julia
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.
Extensible, Efficient Quantum Algorithm Design for Humans.
Clifford circuits, graph states, and other quantum Stabilizer formalism tools.
⟨Grassmann-Clifford-Hodge⟩ multilinear differential geometric algebra
A Julia package for numerical computation in quantum information theory
Package for Simulation, Tomography and Analysis of Quantum Computers
A curated implementation of quantum algorithms with Yao.jl
A Julia/JuMP Package for Optimal Quantum Circuit Design
Unitary and Lindbladian evolution in Julia
Standard basic quantum circuit simulator building blocks. (archived, for it is moved to Yao.jl)
A full stack simulator of quantum hardware, from the low-level analog physics to high-level network dynamics. Includes discrete event simulator, symbolic representation for quantum object, and works with many backend simulators.
Parsers and Tools for OpenQASM
Quantum Optimal Control with Direct Collocation
The Yao compiler project
variational quantum circuit
Abstract type and interface definition for quantum circuit blocks.
Fast and easy simulation of quantum mechanical systems.
Experimental Julia implementation of the Amazon Braket SDK
Simulated Full Amplitude Quantum Register (moved to Yao.jl/lib)
Julia Framework for Quantum Dynamics and Control
Created by Richard Feynman and Yuri Manin