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Disordered topological graphs enhancing nonlinear phenomena
Complex networks play a fundamental role in understanding phenomena from the collective behavior of spins, neural networks, and power grids to the spread of diseases. Topological phenomena in such networks have recently been exploited to preserve the response of systems in the presence of disorder....
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Association for the Advancement of Science
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10075993/ https://www.ncbi.nlm.nih.gov/pubmed/37018406 http://dx.doi.org/10.1126/sciadv.adf9330 |
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author | Jia, Zhetao Seclì, Matteo Avdoshkin, Alexander Redjem, Walid Dresselhaus, Elizabeth Moore, Joel Kanté, Boubacar |
author_facet | Jia, Zhetao Seclì, Matteo Avdoshkin, Alexander Redjem, Walid Dresselhaus, Elizabeth Moore, Joel Kanté, Boubacar |
author_sort | Jia, Zhetao |
collection | PubMed |
description | Complex networks play a fundamental role in understanding phenomena from the collective behavior of spins, neural networks, and power grids to the spread of diseases. Topological phenomena in such networks have recently been exploited to preserve the response of systems in the presence of disorder. We propose and demonstrate topological structurally disordered systems with a modal structure that enhances nonlinear phenomena in the topological channels by inhibiting the ultrafast leakage of energy from edge modes to bulk modes. We present the construction of the graph and show that its dynamics enhances the topologically protected photon pair generation rate by an order of magnitude. Disordered nonlinear topological graphs will enable advanced quantum interconnects, efficient nonlinear sources, and light-based information processing for artificial intelligence. |
format | Online Article Text |
id | pubmed-10075993 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | American Association for the Advancement of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-100759932023-04-06 Disordered topological graphs enhancing nonlinear phenomena Jia, Zhetao Seclì, Matteo Avdoshkin, Alexander Redjem, Walid Dresselhaus, Elizabeth Moore, Joel Kanté, Boubacar Sci Adv Physical and Materials Sciences Complex networks play a fundamental role in understanding phenomena from the collective behavior of spins, neural networks, and power grids to the spread of diseases. Topological phenomena in such networks have recently been exploited to preserve the response of systems in the presence of disorder. We propose and demonstrate topological structurally disordered systems with a modal structure that enhances nonlinear phenomena in the topological channels by inhibiting the ultrafast leakage of energy from edge modes to bulk modes. We present the construction of the graph and show that its dynamics enhances the topologically protected photon pair generation rate by an order of magnitude. Disordered nonlinear topological graphs will enable advanced quantum interconnects, efficient nonlinear sources, and light-based information processing for artificial intelligence. American Association for the Advancement of Science 2023-04-05 /pmc/articles/PMC10075993/ /pubmed/37018406 http://dx.doi.org/10.1126/sciadv.adf9330 Text en Copyright © 2023 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC). https://creativecommons.org/licenses/by-nc/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial license (https://creativecommons.org/licenses/by-nc/4.0/) , which permits use, distribution, and reproduction in any medium, so long as the resultant use is not for commercial advantage and provided the original work is properly cited. |
spellingShingle | Physical and Materials Sciences Jia, Zhetao Seclì, Matteo Avdoshkin, Alexander Redjem, Walid Dresselhaus, Elizabeth Moore, Joel Kanté, Boubacar Disordered topological graphs enhancing nonlinear phenomena |
title | Disordered topological graphs enhancing nonlinear phenomena |
title_full | Disordered topological graphs enhancing nonlinear phenomena |
title_fullStr | Disordered topological graphs enhancing nonlinear phenomena |
title_full_unstemmed | Disordered topological graphs enhancing nonlinear phenomena |
title_short | Disordered topological graphs enhancing nonlinear phenomena |
title_sort | disordered topological graphs enhancing nonlinear phenomena |
topic | Physical and Materials Sciences |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10075993/ https://www.ncbi.nlm.nih.gov/pubmed/37018406 http://dx.doi.org/10.1126/sciadv.adf9330 |
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