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Data-driven structural diagnostics and autonomous alignment of complex optical systems

Year: 2026

Type: preprint

Abstract: The quest for autonomous alignment and maintenance of complex free-space optical systems is increasingly urgent for large-scale neutral-atom quantum processors. Leveraging a high-finesse optical cavity as a sensitive probe, we introduce a data-driven framework for structural diagnostics and closed-loop control that achieves cold-start convergence within tens of seconds. These results establish a rapid, scalable diagnostic-control methodology for autonomous alignment and continuous maintenance of complex free-space optical architectures.

Source: arXiv (Cornell University)

DOI: 10.48550/arxiv.2609.05984

Authors: Zhu, Peng, Chen, Chen, Ma, Shuchang, Deng, Dezhou, Chen, J. F., Chen, Peng

Institutions: The Hong Kong University of Science and Technology (Guangzhou), Southern University of Science and Technology

Topic: Optical Systems and Laser Technology

Subfield: Electrical and Electronic Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: green

Funders: National Natural Science Foundation of China, Hong Kong University of Science and Technology, Guangzhou Municipal Science and Technology Project

Awards: G2155038899, G3185255768

OpenAlex ID: W7212012809

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