Optical Computation-in-Communication enables low-latency, high-fidelity perception in telesurgery

• URL: http://arxiv.org/abs/2510.14058v1
• Date: Wed, 15 Oct 2025 19:54:11 GMT
• Title: Optical Computation-in-Communication enables low-latency, high-fidelity perception in telesurgery
• Authors: Rui Yang, Jiaming Hu, Jian-Qing Zheng, Yue-Zhen Lu, Jian-Wei Cui, Qun Ren, Yi-Jie Yu, John Edward Wu, Zhao-Yu Wang, Xiao-Li Lin, Dandan Zhang, Mingchu Tang, Christos Masouros, Huiyun Liu, Chin-Pang Liu,
• Abstract summary: Optical Computation-in-Communication (OCiC) framework reduces end-to-end latency significantly by performing AI inference concurrently with optical communication.<n>OCiC integrates Optical Remote Computing Units directly into the optical communication pathway, with each ORCU experimentally achieving up to 69 tera-operations per second per channel.<n>When scaled globally, OCiC transforms long-haul fibre infrastructure into a distributed photonic AI fabric with exascale potential.
• Score: 31.415400862116204
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Artificial intelligence (AI) holds significant promise for enhancing intraoperative perception and decision-making in telesurgery, where physical separation impairs sensory feedback and control. Despite advances in medical AI and surgical robotics, conventional electronic AI architectures remain fundamentally constrained by the compounded latency from serial processing of inference and communication. This limitation is especially critical in latency-sensitive procedures such as endovascular interventions, where delays over 200 ms can compromise real-time AI reliability and patient safety. Here, we introduce an Optical Computation-in-Communication (OCiC) framework that reduces end-to-end latency significantly by performing AI inference concurrently with optical communication. OCiC integrates Optical Remote Computing Units (ORCUs) directly into the optical communication pathway, with each ORCU experimentally achieving up to 69 tera-operations per second per channel through spectrally efficient two-dimensional photonic convolution. The system maintains ultrahigh inference fidelity within 0.1% of CPU/GPU baselines on classification and coronary angiography segmentation, while intrinsically mitigating cumulative error propagation, a longstanding barrier to deep optical network scalability. We validated the robustness of OCiC through outdoor dark fibre deployments, confirming consistent and stable performance across varying environmental conditions. When scaled globally, OCiC transforms long-haul fibre infrastructure into a distributed photonic AI fabric with exascale potential, enabling reliable, low-latency telesurgery across distances up to 10,000 km and opening a new optical frontier for distributed medical intelligence.

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