Quantum Limits of Passive Optical Surface Metrology and Defect Detection
ArXiv 2603.10796 (2026)
Diffractive neural networks for mode-sorting with flexible detection regions
Optics & Laser Technology Elsevier 195 (2026) 114544
Abstract:
Mode-sorting is a procedure that decomposes a light field into a basis of transverse modes, directing each mode into a separate spatial location, allowing the constituent mode intensities to be measured simultaneously. We demonstrate a mode-sorter based on a diffractive optical neural network and show that it is advantageous to include the output detection regions in the trainable set of parameters of that network. This approach outperforms traditional mode-sorting methods, achieving lower crosstalk levels for the same efficiency. For example, in sorting 25 Hermite-Gaussian modes with a 3 plate sorter, at 12 % efficiency, the experimentally measured crosstalk decreases from 37.5 % for fixed detection to 8.7 % for flexible detection.Machine learning of quantum data using optimal similarity measurements
ArXiv 2602.23501 (2026)
Time Crystals as Passively Protected Oscillating Qubits
(2026)
Enhancing quantum memories with light–matter interference
Optica Optica Publishing Group 12:9 (2025) 1514