Presentation + Paper
13 March 2024 Scattering on the cloud: scaling-up wave physics computations
Author Affiliations +
Proceedings Volume 12903, AI and Optical Data Sciences V; 129030O (2024) https://doi.org/10.1117/12.3002884
Event: SPIE OPTO, 2024, San Francisco, California, United States
Abstract
With applications from photonics to seismology, wave scattering is ubiquitous in physics. Yet, to study scattering in highly heterogeneous materials, evidence must be obtained from theoretical approximations and surface measurements. Numerical approaches can offer an insight into the wave behavior deep within a complex structure; however, the large scale, with respect to the short wavelength of light, of most systems of interest makes photonic simulations some of the most challenging numerical problems. Memory and time constraints typically limit coherent light scattering calculations to the micrometer scale in 2D and to the nanoscale in 3D. The study of large photonic structures, or scattering in biological samples larger than a few cells, remains out of reach of conventional computational methods. Here, we highlight a connection between the wave equation that governs light-scattering and the structure of a recurrent network. A one-to-one correspondence enables us to leverage efficient machine learning infrastructure and address coherent scattering problems on an unprecedented scale.
Conference Presentation
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Tom Vettenburg and Laurynas Valantinas "Scattering on the cloud: scaling-up wave physics computations", Proc. SPIE 12903, AI and Optical Data Sciences V, 129030O (13 March 2024); https://doi.org/10.1117/12.3002884
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Light scattering

Scattering

Machine learning

Physics

Photonics

Physical coherence

Neural networks

Back to Top