Searcharxiv⌕ Search

arXiv subjects

Rafael de la Fuente Herrezuelo

Publications and source records attributed to Rafael de la Fuente Herrezuelo.

2 recordsLinked to original sources

Physics-Informed Neural Networks for Optimal Beam Shaping in Flat Optics

We introduce a physics-informed neural network (PINN) approach for designing phase profiles in flat optics that reshape an incident beam into a prescribed target intensity distribution. The method solves Monge--Ampère beam-shaping equations associated with energy-conserving ray mappings generated by a phase-only optical element. We treat both finite-distance and far-field targets using a generalized-Snell-law formulation. The learned phase profiles are validated by scalar diffraction simulations and compared with conventional phase-retrieval methods such as Gerchberg--Saxton. To our knowledge, this is the first time a PINN has been used for beam shaping problems in flat optics.

physics.optics↗

Experimental demonstration of a beam shaping non-imaging metasurface

Light emitting diodes have superior performance over most other light sources, but the need for secondary optics to shape their illumination for specific applications yield bulky lighting products. Here, we present an approach to shaping light from incoherent sources, such as light emitting diodes, using non-imaging metasurfaces. We present a theoretical framework and a numerical tool for designing the metasurface phase, and use it to construct a proof-of-principle beam shaping metasurface. We demonstrate the optical performance of the fabricated sample, and perform numerical experiments to investigate the quality of the metasurface design. Our approach bridges the fields of non-imaging optics and metaoptics, and may enable metasurface applications for shaping coherent and incoherent light.

physics.optics↗