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An LLM-based Agentic Framework For Photonic IC Design Automation (U. of Toronto, Max Planck, MIT Et Al.)

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A new technical paper titled “AI Agents for Photonic Integrated Circuit Design Automation” was published by researchers at the University of Toronto, Max Planck Institute of Microstructure Physics, GDSFactory, MIT and Axiomatic_AI Inc.

Abstract
“We present Photonics Intelligent Design and Optimization (PhIDO), a multi-agent framework that converts natural-language photonic integrated circuit (PIC) design requests into layout mask files. We compare 7 reasoning large language models for PhIDO using a testbench of 102 design descriptions that ranged from single devices to 112-component PICs. The success rate for single-device designs was up to 91%. For design queries with less than or equal to 15 components, o1, Gemini-2.5-pro, and Claude Opus 4 achieved the highest end-to-end pass@5 success rates of approximately 57%, with Gemini-2.5-pro requiring the fewest output tokens and lowest cost. The next steps toward autonomous PIC development include standardized knowledge representations, expanded datasets, extended verification, and robotic automation.”

Find the technical paper here. August 2025.

Sharma, Ankita, YuQi Fu, Vahid Ansari, Rishabh Iyer, Fiona Kuang, Kashish Mistry, Raisa Islam Aishy et al. “AI Agents for Photonic Integrated Circuit Design Automation.” arXiv preprint arXiv:2508.14123 (2025).



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