Universität zu Köln

Calzavara, Martino ORCID: 0000-0002-1807-5567 (2025). Automated optimization, learning and control for cold atom platforms. PhD thesis, Universität zu Köln.

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Abstract

Quantum technologies based on cold atom platforms, while benefiting from highly stable and scalable atomic systems, still rely on the precise characterization, calibration, and control of complex experimental apparatuses. In this thesis, we develop automated approaches to address these critical tasks, integrating physical insight with optimization and learning methods, while complying with operational constraints. The bulk of the work presented here consists of three research papers. In the first one, we introduce physics-inspired machine-learning models to optimize optical dipole potentials for shaping ultracold gasses, achieving order-of-magnitude improvements in speed. In the second paper, we investigate atom transport between optical tweezers, a key auxiliary operation for scalable quantum processors, and demonstrate how shortcuts to adiabaticity and quantum optimal control can minimize heating and excitations during fast transport. The third and last paper analyzes a class of optimization landscapes relevant for quantum control, deriving from first principles a set of classical surrogates. We show how time and energy constraints translate into limited bandwidth and derivatives for the landscape, with consequences for the design of regression models and for optimization, which we relate to bounds in associated metrics. Together, these results provide concrete examples of how automated optimization, learning, and control can expand the toolset available for building quantum firmware for cold atom platforms. The methods presented not only improve experimental performance but keep implementation overhead at a minimum, thereby simplifying operations and facilitating scale-up efforts.

Item Type:	Thesis (PhD thesis)
Creators:	Creators Email ORCID ORCID Put Code Calzavara, Martino m.calzavara@fz-juelich.de https://orcid.org/0000-0002-1807-5567 UNSPECIFIED
URN:	urn:nbn:de:hbz:38-793633
Date:	2025
Language:	English
Faculty:	Faculty of Mathematics and Natural Sciences
Divisions:	Faculty of Mathematics and Natural Sciences > Department of Physics > Institute for Theoretical Physics
Subjects:	Physics
Uncontrolled Keywords:	Keywords Language cold atoms English quantum control English
Date of oral exam:	4 December 2025
Referee:	Name Academic Title Calarco, Tommaso Prof. Dr. Del Campo, Adolfo Prof. Dr.
Refereed:	Yes
URI:	http://kups.ub.uni-koeln.de/id/eprint/79363