luigiannelli / threeLS_populationtransfer

A Tutorial on Optimal Control and Reinforcement Learning methods for Quantum Technologies, notebooks

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A Tutorial on Optimal Control and Reinforcement Learning methods for Quantum Technologies

by Luigi Giannelli, Sofia Sgroi, Jonathon Brown, Gheorghe Sorin Paraoanu, Mauro Paternostro, Elisabetta Paladino, and Giuseppe Falci
Physics Letters A 434, 128054 (2022)
arXiv:2112.07453

DOI

Installation

Tested with python 3.9.7.

  1. Clone the repository
git clone https://www.github.com/luigiannelli/threeLS_populationTransfer
cd threeLS_populationTransfer
  1. (Optionally) Create a python environment (instructions using pyenv with pyenv-virtualenv)
pyenv install 3.9.7
pyenv local 3.9.7
pyenv virtualenv threeLS
pyenv local threeLS
  1. Install dependencies
pip install --upgrade pip setuptools wheel
pip install -r requirements.txt
  1. Run jupyterlab and play with the notebooks in notebooks
jupyterlab

About

A Tutorial on Optimal Control and Reinforcement Learning methods for Quantum Technologies, notebooks

License:GNU General Public License v3.0


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Language:Jupyter Notebook 95.0%Language:Python 5.0%