| Issue |
EPJ Web Conf.
Volume 335, 2025
EOS Annual Meeting (EOSAM 2025)
|
|
|---|---|---|
| Article Number | 01010 | |
| Number of page(s) | 2 | |
| Section | Face2Phase (F2P) | |
| DOI | https://doi.org/10.1051/epjconf/202533501010 | |
| Published online | 22 September 2025 | |
https://doi.org/10.1051/epjconf/202533501010
Instant reconstruction of the longitudinal component in tightly focused fields using polarimetric data and deep neural networks
Departament de Física Aplicada, Universitat de Barcelona, Martí i Franquès 1, Barcelona, 08028
* e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
Published online: 22 September 2025
Abstract
This work presents a data-driven approach for reconstructing the longitudinal component of tightly focused optical fields using only experimentally accessible polarimetric intensity images. A custom-designed deep neural network is trained on simulated polarimetric mappings generated from aberrated wavefronts through a high-NA objective. The model successfully reconstructs the complex amplitude of the longitudinal field with high fidelity, offering a practical and instant method for indirect measurement of longitudinal components in tightly focused beams.
© The Authors, published by EDP Sciences, 2025
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