Inverse Design of Optical Switch Based on Bilevel Optimization Inspired by Meta-Learning

Abstract

We introduce the concept of meta-learning into the design of active optical switches. An optical switch consists of both tunable and nontunable elements. It has been difficult to apply conventional inverse design methods to optical switches, since the optimal choice of the tunable elements depends on the design of the nontunable elements. Here we show that a bilevel optimization scheme, closely related to the concept of meta-learning, can be used for the design of active optical switches. In this scheme, the inner and outer loops correspond to the optimization of the tunable and nontunable elements, respectively. We illustrate this scheme with two designs of optical switches based on different tuning mechanisms. This approach is generally applicable for the design of optical switches as well as other active and tunable optical devices.

Free-Space Beam Steering with Twisted Bilayer Photonic Crystal Slabs

“…One could also extend the method to more general light routing functions beyond single-channel ones. We anticipate the use of bilevel optimizations , for achieving such more general light routing functions.…”

DataSheet1.docx

“…The precision control of optical beams is of paramount importance for numerous emerging applications, encompassing light detection and ranging [1][2][3], free space optical communications (FSO) [4][5][6][7], optical multiple-input multiple-output (MIMO) [8,9], optical switches [10][11][12], structured light [13,14] and beyond. Emerging technologies now demand more versatile beam steering techniques beyond merely controlling the propagation direction of individual beams.…”