Tailoring 3D non-Rayleigh speckles via physics-informed neural networks.

Authors

Ze-Huan Zheng, Jin-Hui Chen

Published in

Optics letters. Volume 51. Issue 21. Pages 5930-5933. Nov 01, 2026. Epub Sep 24, 2026.

Abstract

Optical speckles, a disordered photonic phenomenon that originates from the interference of multiple scattered coherent waves, typically obey Rayleigh statistics. Beyond this classical regime, featuring customizable statistical properties and high-order correlations, non-Rayleigh speckles present potential in both fundamental and applied research. Here, we introduce a physics-informed neural network for designing three-dimensional non-Rayleigh speckle fields. As a proof of concept, we experimentally realize volumetric sub-Rayleigh and propagation-persistent super-Rayleigh speckles on this versatile framework. Our work paves a novel, to the best of our knowledge, way for statistical light manipulation and engineering implementation.

PMID:
42962090
Bibliographic data and abstract were imported from PubMed on 31 Oct 2026.

Read full publication at:
Please sign in to see all details.

Stats

1-terrible, 9-excellent. How would you rate this publication? Sign in in to submit your rating.

Post a comment

You need to be signed in to post comments. You can sign in here.

Comments

There are no comments yet.