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DTSTAMP:20240214T070247Z
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:Technical Papers\n\nCheng Zheng (MIT), Guangyuan Zhao (The Chi
 nese University of Hong Kong), and Peter So (MIT)\n\nWe introduce neural l
 ithography to address the ‘design-to-manufacturing’ gap in computational o
 ptics. Computational optics with large design degrees of freedom enable ad
 vanced functionalities and performance beyond traditional optics. However,
  the existing design approaches often overlook the numerical modeling of t
 he manufacturing process, which can result in significant performance devi
 ation between the design and the fabricated optics. To bridge this gap, we
 , for the first time, propose a fully differentiable design framework that
  integrates a pre-trained photolithography simulator into the model-based 
 optical design loop. Leveraging a blend of physics-informed modeling and d
 ata-driven training using experimentally collected datasets, our photolith
 ography simulator serves as a regularizer on fabrication feasibility durin
 g design, compensating for structure discrepancies introduced in the litho
 graphy process. We demonstrate the effectiveness of our approach through t
 wo 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 perfor
 mance on the task-specific metrics.\n\nRegistration Category: Full Access\
 n\nSession Chair: Haisen Zhao (Shandong University)
URL:https://asia.siggraph.org/2023/full-program?id=papers_995&sess=sess152
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