Spontaneous Symmetry Breaking in Diffraction

We demonstrate spontaneous symmetry breaking in the diffraction of a laser-driven grating with memory in its nonlinear response. We observe, experimentally and theoretically, asymmetric diffraction even when the grating and illumination are symmetric. Our analysis reveals how diffracted waves can spontaneously acquire momentum parallel to the lattice vector in quantities unconstrained by the grating period. Our findings point to numerous opportunities for imaging, sensing, and information processing with nonlinear periodic systems, which can leverage a much richer diffractive response than their linear counterparts.

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Publication Details

Journal
Physical Review Letters
Published
2024-09-27
DOI
https://doi.org/10.1103/physrevlett.133.133803
Citations
1
Primary Topic
Neural Networks and Reservoir Computing
Type
article
Field-Weighted Citation Impact
0.35

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Spontaneous Symmetry Breaking in Diffraction

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Spontaneous Symmetry Breaking in Diffraction

Z. Geng, Francisco José García-Vidal, Antonio I. Fernández‐Domínguez, G. Keijsers, S. R. K. Rodríguez, Jaime Abad-Arredondo, Falco Bijloo
article en
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Abstract

We demonstrate spontaneous symmetry breaking in the diffraction of a laser-driven grating with memory in its nonlinear response. We observe, experimentally and theoretically, asymmetric diffraction even when the grating and illumination are symmetric. Our analysis reveals how diffracted waves can spontaneously acquire momentum parallel to the lattice vector in quantities unconstrained by the grating period. Our findings point to numerous opportunities for imaging, sensing, and information processing with nonlinear periodic systems, which can leverage a much richer diffractive response than their linear counterparts.

Physical Review LettersVol. 133(13)
Institute for Atomic and Molecular Physics (NL), Institute of High Performance Computing (SG), Universidad Autónoma de Madrid (ES)
Ministerio de Ciencia, Innovación y Universidades, Nederlandse Organisatie voor Wetenschappelijk Onderzoek, Horizon 2020 Framework Programme, H2020 European Research Council
Reduced inequalities
Openalex Percentile: Top 33%
Neural Networks and Reservoir Computing
0.35
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