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DTSTAMP:20260114T163645Z
LOCATION:Meeting Room C4.9+C4.10\, Level 4 (Convention Centre)
DTSTART;TZID=Australia/Melbourne:20231214T111000
DTEND;TZID=Australia/Melbourne:20231214T112000
UID:siggraphasia_SIGGRAPH Asia 2023_sess152_papers_995@linklings.com
SUMMARY:Close the Design-to-Manufacturing Gap in Computational Optics with
  a ’Real2Sim’ Learned Two-Photon Neural Lithography Simulator
DESCRIPTION:Cheng Zheng (MIT), Guangyuan Zhao (The Chinese University of H
 ong Kong), and Peter So (MIT)\n\nWe introduce neural lithography to addres
 s the ‘design-to-manufacturing’ gap in computational optics. Computational
  optics with large design degrees of freedom enable advanced functionaliti
 es and performance beyond traditional optics. However, the existing design
  approaches often overlook the numerical modeling of the manufacturing pro
 cess, which can result in significant performance deviation between the de
 sign and the fabricated optics. To bridge this gap, we, for the first time
 , propose a fully differentiable design framework that integrates a pre-tr
 ained photolithography simulator into the model-based optical design loop.
  Leveraging a blend of physics-informed modeling and data-driven training 
 using experimentally collected datasets, our photolithography simulator se
 rves as a regularizer on fabrication feasibility during design, compensati
 ng for structure discrepancies introduced in the lithography process. We d
 emonstrate the effectiveness of our approach through two typical tasks in 
 computational optics, where we design and fabricate a holographic optical 
 element (HOE) and a multi-level diffractive lens (MDL) using a two-photon 
 lithography system, showcasing improved optical performance on the task-sp
 ecific metrics.\n\nRegistration Category: Full Access\n\nSession Chair: Ha
 isen Zhao (Shandong University)\n\n
URL:https://asia.siggraph.org/2023/full-program?id=papers_995&sess=sess152
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