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Minimal memory differentiable FDTD for inverse design

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Abstract

We construct a reverse mode automatic differentiation FDTD that reduces the memory requirement, a typical bottleneck, by two orders of magnitude, and employ it to produce meta-atoms with specified phase responses and group delays.

© 2022 The Author(s)

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More Like This
Inverse Design of Nanophotonics Structures with Minimal Computation Using a Pruning Approach

Mohammad H Javani, Mohammadreza Zandehshahvar, Muliang Zhu, Tyler Brown, Yashar Kiarashi, and Ali Adibi
JW3B.132 CLEO: Applications and Technology (CLEO_AT) 2022

Acceleration of FDTD-based Inverse Design Using a Neural Network Approach

Keisuke Kojima, Bingnan Wang, Ulugbek Kamilov, Toshiaki Koike-Akino, and Kieran Parsons
ITu1A.4 Integrated Photonics Research, Silicon and Nanophotonics (IPRSN) 2017

Optimizing Metrological Devices with Memory-Efficient Automatic Differentiation

Michael H. Goerz, Sebastián C. Carrasco, and Vladimir S. Malinovsky
QW2A.12 Quantum 2.0 (QUANTUM) 2022

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