Using reinforcement learning for quantum control
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Updated
Jun 13, 2022 - Jupyter Notebook
Using reinforcement learning for quantum control
A toolbox to interface reinforcement learning with quantum systems!
Master thesis in quantum control theory.
Code and results for quantum optimal control based on switching time optimization
Matlab code for quantum spin-1/2 networks. It provides code to analyse the geometry of such networks, and some basic quantum control and characterisation code.
Entanglement engineering of optomechanical systems by reinforcement learning
A Julia implementation of the Gradient Optimization of Analytic conTrols (GOAT) optimal control methodology.
Projeto que usa MPC (Modelo de controle preditivo) juntamente com o controle quântico para manipulação da função de onda apresentada na equação de Schrodinger, a base para mecânica quântica
Trajectory optimization (indirect with iLQR, direct with SQP), model predictive control, and additional tools for quantum optimal control.
Robustness characterization of quantum controls and quantum control algorithms.
Evolve any unitary using solve_ivp
Quantum control algorithms for multiple examples based on the package Qutip
quantum control using Hamiltonian Switching
Code for the paper Bilinear Dynamic Mode Decomposition for Quantum Control
Reinforcement learning model-free quantum control on many coupled qubits.
A Julia package to simulate the open-system dynamics of a noisy spin qubit driven by customizable quantum control protocols.
Dynamic Gradients for Quantum Control
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