PRISM: Photonics-Informed Inverse Lithography for Manufacturable Inverse-Designed Photonic Integrated Circuits
2026-02-17 • Emerging Technologies
Emerging Technologies
AI summaryⓘ
The authors address a challenge in making advanced photonic devices that are sensitive to tiny manufacturing errors, which usually lowers their performance in real-world production. They introduce PRISM, a new method that improves how masks for photonic components are optimized by using smart calibration patterns and physics-based models. This approach helps create designs that work better after fabrication, reduce the time and data needed for calibration, and improve manufacturing yield. Their work makes it easier and more reliable to produce complex photonic hardware at scale.
photonic inverse designphotonic integrated circuits (PICs)mask optimizationfabrication variationselectron-beam lithographydeep ultraviolet photolithographycalibration patternsdifferentiable fabrication modelmanufacturabilityyield
Authors
Hongjian Zhou, Haoyu Yang, Nicholas Gangi, Tianle Xu, Rena Huang, Jiaqi Gu
Abstract
Recent advances in photonic inverse design have demonstrated the ability to automatically synthesize compact, high-performance photonic components that surpass conventional, hand-designed structures, offering a promising path toward scalable and functionality-rich photonic hardware. However, the practical deployment of inverse-designed PICs is bottlenecked by manufacturability: their irregular, subwavelength geometries are highly sensitive to fabrication variations, leading to large performance degradation, low yield, and a persistent gap between simulated optimality and fabricated performance. Unlike electronics, photonics lacks a systematic, flexible mask optimization flow. Fabrication deviations in photonic components cause large optical response drift and compounding error in cascaded circuits, while calibrating fabrication models remains costly and expertise-heavy, often requiring repeated fabrication cycles that are inaccessible to most designers. To bridge this gap, we introduce PRISM, a photonics-informed inverse lithography workflow that makes photonic mask optimization data-efficient, reliable, and optics-informed. PRISM (i) synthesizes compact, informative calibration patterns to minimize required fabrication data, (ii) trains a physics-grounded differentiable fabrication model, enabling gradient-based optimization, and (iii) performs photonics-informed inverse mask optimization that prioritizes performance-critical features beyond geometry matching. Across multiple inverse-designed components with both electron-beam lithography and deep ultra-violet photolithography processes, PRISM significantly boosts post-fabrication performance and yield while reducing calibration area and turnaround time, enabling and democratizing manufacturable and high-yield inverse-designed photonic hardware at scale.