Quantum spatial search on graphs with dynamical noise
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Updated
Nov 14, 2018 - 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.
Quantum spatial search on graphs with dynamical noise
QuantumWalk.jl: Package for building algorithms based on quantum walks
QSWalk.jl: simulating the evolution of open quantum systems on graphs
Quantum Toolbox and Circuit Simulator written in Julia
Bidirectional transformation between Yao IR and QASM.
Wire location types for quantum circuit
YaoBlocks interafce for the IBMQClient package.
A toolkit for the quantum and classical Dicke model in Julia.
Library for solving quantum optimal control problems in Julia. Currently offers support for GRAPE and dCRAB algorithms using piecewise constant controls.
Abstract type and interface definition for quantum circuit blocks.
Simulated Full Amplitude Quantum Register (moved to Yao.jl/lib)
Standard basic quantum circuit simulator building blocks. (archived, for it is moved to Yao.jl)
The Yao compiler project
Topological Evaluation of Quantum Information
Implementation of a fast exponential matrix for large matrices (full and sparse)
Unitary and Lindbladian evolution in Julia
Learning sparse Pauli noise using the population recovery algorithm.
A tiny quantum optimal control library.
Unofficial julia interface for quri-parts. (That is Goma goma kyu kkyu)
Created by Richard Feynman and Yuri Manin