QR-Code Structure for Beam Shaping and Polarization Control via Machine Learning for Chip-Integrated Quantum Applications

¹ Technische Universität Braunschweig, Institute of Semiconductor Technology, Hans-Sommer-Str. 66, Braunschweig, 38106, Germany
² Laboratory for Emerging Nanometrology, Langer Kamp 6a/b, Braunschweig, 38106, Germany
³ Physikalisch-Technische Bundesanstalt, Bundesallee 100, Braunschweig, 38116, Germany
⁴ AMO GmbH, Otto-Blumenthal-Straße 25, 52074 Aachen, Germany
⁵ RWTH Aachen University, Chair of Electronic Devices, 52074 Aachen, Germany
⁶ Leibniz Universität Hannover, Institut für Quantenoptik, Welfengarten 1, Hannover, 30167, Germany
⁷ Leibniz Universität Hannover, Laboratorium für Nanound Quantenengineering, Welfengarten 1, Hannover, 30167, Germany

^* e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

Published online: 22 September 2025

Abstract

While many research fields are driven to higher levels of performance with photonic integrated circuits, the forward design of these systems faces certain limitations. This paper presents a machine learning based approach to design binary metasurfaces to facilitate beam shaping, angle, and polarization state. We implement Lumerical FDTD and Non-Dominated Sorting Genetic Algorithm III (NSGA-III) to optimize the topology of the outcoupling structure composed of subwavelength pixels, allowing a higher degree of control over the emitted light field. The generated pattern is shown to maintain the desired beam shape and angle while modulating the right/left circular and linear polarization states, allowing scalability of the design for different wavelengths without large distortion of the field properties and promising low fabrication complexity.