All-optical Edge Computing for Speckle Sensing Interrogation
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arXiv
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| Main Authors: | , , , , , |
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| Format: | Preprint |
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2026
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| _version_ | 1866914599432880128 |
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| author | Lopes, Tomás Teixeira, Joana M. Ferreira, Tiago D. Monteiro, Catarina S. Jorge, Pedro A. S. Silva, Nuno A. |
| author_facet | Lopes, Tomás Teixeira, Joana M. Ferreira, Tiago D. Monteiro, Catarina S. Jorge, Pedro A. S. Silva, Nuno A. |
| contents | Speckle-based sensing exploits the rich environmental information of its high-dimensional spatial intensity patterns. However, the requirement for camera-based acquisition and subsequent electronic digitization introduces significant latency and bandwidth bottlenecks that forbid real-time operation and higher temporal resolutions. Aiming to bypass this imaging processing pipeline, this manuscript presents an optically reconfigurable edge-computing platform for speckle-based sensors that performs task-specific computation directly in the optical domain. This is achieved by projecting output speckle patterns onto a digital micromirror device, using it as a programmable optical layer whose parameters are trained in situ using an evolutionary optimization strategy solely from detector feedback. We demonstrate the concept with a multi-point optical fiber sensing task, where multiple piezoelectric actuators simultaneously perturb the fiber, modifying the speckle pattern. Optimizing a set of masks to decouple these concurrent signals, the system successfully achieves real-time signal separation, achieving a target signal enhancement exceeding 4 dB while suppressing crosstalk leakage below -10 dB. Operating with bandwidths limited only by the photodetector, this approach paves the way for real-time and ultrafast optical sensing via an all-optical edge computing solution. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2605_25805 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | All-optical Edge Computing for Speckle Sensing Interrogation Lopes, Tomás Teixeira, Joana M. Ferreira, Tiago D. Monteiro, Catarina S. Jorge, Pedro A. S. Silva, Nuno A. Optics Speckle-based sensing exploits the rich environmental information of its high-dimensional spatial intensity patterns. However, the requirement for camera-based acquisition and subsequent electronic digitization introduces significant latency and bandwidth bottlenecks that forbid real-time operation and higher temporal resolutions. Aiming to bypass this imaging processing pipeline, this manuscript presents an optically reconfigurable edge-computing platform for speckle-based sensors that performs task-specific computation directly in the optical domain. This is achieved by projecting output speckle patterns onto a digital micromirror device, using it as a programmable optical layer whose parameters are trained in situ using an evolutionary optimization strategy solely from detector feedback. We demonstrate the concept with a multi-point optical fiber sensing task, where multiple piezoelectric actuators simultaneously perturb the fiber, modifying the speckle pattern. Optimizing a set of masks to decouple these concurrent signals, the system successfully achieves real-time signal separation, achieving a target signal enhancement exceeding 4 dB while suppressing crosstalk leakage below -10 dB. Operating with bandwidths limited only by the photodetector, this approach paves the way for real-time and ultrafast optical sensing via an all-optical edge computing solution. |
| title | All-optical Edge Computing for Speckle Sensing Interrogation |
| topic | Optics |
| url | https://arxiv.org/abs/2605.25805 |