Photonic Self-Learning in Ultrafast Laser-Induced Complexity

Fuente: arXiv
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Autores principales: Banna, Fayad Ali, Brandao, Eduardo, Nakhoul, Anthony, Emonet, Rémi, Sebban, Marc, Colombier, Jean-Philippe
Formato: Preprint
Publicado: 2025
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author Banna, Fayad Ali
Brandao, Eduardo
Nakhoul, Anthony
Emonet, Rémi
Sebban, Marc
Colombier, Jean-Philippe
author_facet Banna, Fayad Ali
Brandao, Eduardo
Nakhoul, Anthony
Emonet, Rémi
Sebban, Marc
Colombier, Jean-Philippe
contents How can one design complex systems capable of learning for a given functionality? In the context of ultrafast laser-surface interaction, we unravel the nature of learning schemes tied to the emergence of complexity in dissipative structures. The progressive development of learning mechanisms, from direct information storage to the development of smart surfaces, originates from the network of curvatures formed in the unstable fluid under thermoconvective instability, which is subsequently quenched and resolidified. Under pulsed laser irradiation, non-equilibrium dynamics generate intricate nanoscale patterns, unveiling adaptive process mechanisms. We demonstrate that the imprints left by light act as a form of structural memory, encoding not only local effects directed by laser field polarization but also a cooperative strategy of reliefs that dynamically adjust surface morphology to optimize light capture. By investigating how apparent complexity and optical response are intricately intertwined, shaping one another, we establish a framework that draws parallels between material adaptation and learning dynamics observed in biological systems.
format Preprint
id arxiv_https___arxiv_org_abs_2507_08825
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Photonic Self-Learning in Ultrafast Laser-Induced Complexity
Banna, Fayad Ali
Brandao, Eduardo
Nakhoul, Anthony
Emonet, Rémi
Sebban, Marc
Colombier, Jean-Philippe
Optics
How can one design complex systems capable of learning for a given functionality? In the context of ultrafast laser-surface interaction, we unravel the nature of learning schemes tied to the emergence of complexity in dissipative structures. The progressive development of learning mechanisms, from direct information storage to the development of smart surfaces, originates from the network of curvatures formed in the unstable fluid under thermoconvective instability, which is subsequently quenched and resolidified. Under pulsed laser irradiation, non-equilibrium dynamics generate intricate nanoscale patterns, unveiling adaptive process mechanisms. We demonstrate that the imprints left by light act as a form of structural memory, encoding not only local effects directed by laser field polarization but also a cooperative strategy of reliefs that dynamically adjust surface morphology to optimize light capture. By investigating how apparent complexity and optical response are intricately intertwined, shaping one another, we establish a framework that draws parallels between material adaptation and learning dynamics observed in biological systems.
title Photonic Self-Learning in Ultrafast Laser-Induced Complexity
topic Optics
url https://arxiv.org/abs/2507.08825