QuOCS: The Quantum Optimal Control Suite
Marco Rossignolo, Thomas Reisser, Alastair Marshall, Phila Rembold,, Alice Pagano, Philipp J. Vetter, Ressa S. Said, Matthias M. M\"uller, Felix, Motzoi, Tommaso Calarco, Fedor Jelezko, Simone Montangero

TL;DR
QuOCS is a versatile software suite that unifies experimental and model-based quantum optimal control algorithms, facilitating improved performance across various quantum technologies and physical phenomena.
Contribution
It introduces an easy-to-use, integrated framework combining gradient-free and gradient-based algorithms for quantum optimal control, with flexible experimental connectivity.
Findings
Successfully applied to optimize quantum systems in open- and closed-loop settings
Supports integration with existing experimental control software like Qudi
Available as open-source software on GitHub and PyPI
Abstract
Quantum optimal control includes the family of pulse-shaping algorithms that aim to unlock the full potential of a variety of quantum technologies. Our Quantum Optimal Control Suite (QuOCS) unites experimental focus and model-based approaches in a unified framework. The easy usage and installation of QuOCS and the availability of various combinable optimization strategies is designed to improve the performance of many quantum technology platforms, such as color defects in diamond, superconducting qubits, atom- or ion-based quantum computers. It can also be applied to the study of more general phenomena in physics. In this paper, we describe the software and the main toolbox of gradient-free and gradient-based algorithms. We then show how the user can connect it to their experiment. In addition, we provide illustrative examples where our optimization suite solves typical quantum optimal…
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Taxonomy
TopicsDiamond and Carbon-based Materials Research · Laser-Matter Interactions and Applications · Quantum Computing Algorithms and Architecture
