Taming quantum systems: A tutorial for using shortcuts-to-adiabaticity, quantum optimal control, and reinforcement learning

This repository contains the Jupyter notebooks accompanying arXiv:2501.16436 Taming quantum systems: A tutorial for using shortcuts-to-adiabaticity, quantum optimal control, and reinforcement learning by Duncan et al., and instructions for using them.

Sec II: Shortcuts to Adiabaticity

• Notebook 2.1:

Sec III: Quantum Optimal Control

• Notebook 3.1:

Sec IV: Reinforcement Learning for Optimal Quantum Control

• Notebook 4.1: Universal single-qubit state preparation
• Notebook 4.2: RL vs. counter-diabatic driving in the presence of Trotterization errors
• Notebook 4.3: Continuous single-qubit feedback control using quantum data

Required packages can be found in requirements.txt.

You may create a virtual environment using pip and install all packages at once by running:

.. python -m venv .ctrl_tutor
.. source .ctrl_tutor/bin/activate
.. python -m pip install --upgrade pip
.. python -m pip install -r requirements.txt

To run the jupyter notebooks, run

.. jupyter lab

and select tje notebook you're interested in.