Autonomous multifunctional image processing via programmable multimode lasing
Abstract
Optical image processing offers a promising pathway to overcome the latency and energy limitations of conventional electronic image processors. However, existing approaches based on passive photonic devices are often constrained by signal attenuation, lack of nonlinearity, fixed functionality, and heavy training overhead. Here, we introduce a programmable image processor based on a highly multimode degenerate cavity laser (DCL), shifting the computational framework from passive extracavity transformation to active intracavity evolution. By manipulating the intracavity loss distribution and exploiting the nonlinear lasing dynamics, we map computational tasks to the spontaneous mode selection within the DCL, realizing image processing directly at the source. We experimentally demonstrate that by simply altering the encoding scheme of input images, the platform can be flexibly reconfigured for multifunctional tasks, including high-fidelity edge detection and robust image denoising. The computation proceeds autonomously without dataset training, featuring an intrinsically low latency (∼90 μs) with 𝒪(1) complexity. Furthermore, the high intensity sustained within the resonator enables intracavity nonlinear upconversion of the processed image. This work extends the frontiers of laser applications, providing a compelling candidate for next-generation optical processors.
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BibTeX
@misc{wu2026autonomous,
title = {{Autonomous multifunctional image processing via programmable multimode lasing}},
author = {Jiawei Wu and Yue Yin and Jianqi Hu and Hao Wang and Xing Fu and Qiang Liu},
howpublished = {arXiv},
year = {2026},
month = sep,
doi = {10.48550/arxiv.2609.12534},
eprint = {2609.12534},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2609.12534},
}
RIS
TY - UNPB
TI - Autonomous multifunctional image processing via programmable multimode lasing
AU - Jiawei Wu
AU - Yue Yin
AU - Jianqi Hu
AU - Hao Wang
AU - Xing Fu
AU - Qiang Liu
PY - 2026
DA - 2026/09/11
PB - arXiv
DO - 10.48550/arxiv.2609.12534
UR - https://arxiv.org/abs/2609.12534
AB - Optical image processing offers a promising pathway to overcome the latency and energy limitations of conventional electronic image processors. However, existing approaches based on passive photonic devices are often constrained by signal attenuation, lack of nonlinearity, fixed functionality, and heavy training overhead. Here, we introduce a programmable image processor based on a highly multimode degenerate cavity laser (DCL), shifting the computational framework from passive extracavity transformation to active intracavity evolution. By manipulating the intracavity loss distribution and exploiting the nonlinear lasing dynamics, we map computational tasks to the spontaneous mode selection within the DCL, realizing image processing directly at the source. We experimentally demonstrate that by simply altering the encoding scheme of input images, the platform can be flexibly reconfigured for multifunctional tasks, including high-fidelity edge detection and robust image denoising. The computation proceeds autonomously without dataset training, featuring an intrinsically low latency (∼90 μs) with 𝒪(1) complexity. Furthermore, the high intensity sustained within the resonator enables intracavity nonlinear upconversion of the processed image. This work extends the frontiers of laser applications, providing a compelling candidate for next-generation optical processors.
ER -