A tiny quantum optimal control library.
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Updated
Jan 12, 2023 - 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.
A tiny quantum optimal control library.
Learning sparse Pauli noise using the population recovery algorithm.
Where I Explore and Experiment with Julia Programming Language!
cim-optimizer wrapper for JuMP
Unofficial julia interface for quri-parts. (That is Goma goma kyu kkyu)
🔵 QUBO Annealing & Sampling MOI Interfaces
A Classical Simulation of the Quantum Game of Life
Julia package for analyzing two-qubit gates in the Weyl chamber
Qiskit compatible circuit manipulation in Julia
Bosons/Fermions Superfluid problem with morden tools.
Unofficial Julia interface for qulacs.
Client for simulating quantum computers in cloud
A high-performance library for gradient based quantum optimal control
Schrödinger-like simulator of quantum computers
Design scalable noise characterisation experiments for quantum computers
Compile quantum circuits to surface code architectures using edge-disjoint paths
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.
Created by Richard Feynman and Yuri Manin