Title: Leveraging Continuous Material Averaging for Inverse Electromagnetic Design,
Abstract: Inverse electromagnetic design has emerged as a way of efficiently designing
active and passive electromagnetic devices. This maturing strategy involves
optimizing the shape or topology of a device in order to improve a figure of
merit--a process which is typically performed using some form of steepest
descent algorithm. Naturally, this requires that we compute the gradient of a
figure of merit which describes device performance, potentially with respect to
many design variables. In this paper, we introduce a new strategy based on
smoothing abrupt material interfaces which enables us to efficiently compute
these gradients with high accuracy irrespective of the resolution of the
underlying simulation. This has advantages over previous approaches to shape
and topology optimization in nanophotonics which are either prone to gradient
errors or place important constraints on the shape of the device. As a
demonstration of this new strategy, we optimize a non-adiabatic waveguide taper
between a narrow and wide waveguide. This optimization leads to a non-intuitive
design with a very low insertion loss of only 0.041 dB at 1550 nm.