Fully Parallel Multi-Agent Photonic Optimizer
Fuente:
arXiv
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| Autori principali: | , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| Soggetti: | |
| Accesso online: | |
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| _version_ | 1866909830842679296 |
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| author | Syed, Ghazi Sarwat Schmidt, Philipp Brückerhoff-Plückelmann, Frank Dijkstra, Jelle Pernice, Wolfram H. P Sebastian, Abu |
| author_facet | Syed, Ghazi Sarwat Schmidt, Philipp Brückerhoff-Plückelmann, Frank Dijkstra, Jelle Pernice, Wolfram H. P Sebastian, Abu |
| contents | Optimization problems are central to many important cross-disciplinary applications.In their conventional implementations, the sequential nature of operations imposes strict limitations on the computational efficiency. Here, we discuss how analog optical computing can overcome this fundamental bottleneck. We propose a photonic optimizer unit, together with supporting algorithms that uses in memory computation within a nature inspired, multi agent cooperative framework. The system performs a sequence of reconfigurable parallel matrix vector operations, enabled by the high bandwidth and multiplexing capabilities inherent to photonic circuits. This approach provides a pathway toward fast paced and high quality solutions for difficult optimization and search problems. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2510_06424 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Fully Parallel Multi-Agent Photonic Optimizer Syed, Ghazi Sarwat Schmidt, Philipp Brückerhoff-Plückelmann, Frank Dijkstra, Jelle Pernice, Wolfram H. P Sebastian, Abu Disordered Systems and Neural Networks Optimization problems are central to many important cross-disciplinary applications.In their conventional implementations, the sequential nature of operations imposes strict limitations on the computational efficiency. Here, we discuss how analog optical computing can overcome this fundamental bottleneck. We propose a photonic optimizer unit, together with supporting algorithms that uses in memory computation within a nature inspired, multi agent cooperative framework. The system performs a sequence of reconfigurable parallel matrix vector operations, enabled by the high bandwidth and multiplexing capabilities inherent to photonic circuits. This approach provides a pathway toward fast paced and high quality solutions for difficult optimization and search problems. |
| title | Fully Parallel Multi-Agent Photonic Optimizer |
| topic | Disordered Systems and Neural Networks |
| url | https://arxiv.org/abs/2510.06424 |