469 research outputs found
Inverse design and implementation of a wavelength demultiplexing grating coupler
Nanophotonics has emerged as a powerful tool for manipulating light on chips.
Almost all of today's devices, however, have been designed using slow and
ineffective brute-force search methods, leading in many cases to limited device
performance. In this article, we provide a complete demonstration of our
recently proposed inverse design technique, wherein the user specifies design
constraints in the form of target fields rather than a dielectric constant
profile, and in particular we use this method to demonstrate a new
demultiplexing grating. The novel grating, which has not been developed using
conventional techniques, accepts a vertical-incident Gaussian beam from a
free-space and separates O-band and C-band
light into separate waveguides. This inverse design concept
is simple and extendable to a broad class of highly compact devices including
frequency splitters, mode converters, and spatial mode multiplexers.Comment: 17 pages, 4 figures, 1 table. A supplementary section describing the
inverse-design algorithm in detail has been added, in addition to minor
corrections and updated reference
Leveraging Continuous Material Averaging for Inverse Electromagnetic Design
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.Comment: 20 pages, 9 figure
Automatic differentiation accelerated shape optimization approaches to photonic inverse design on rectilinear simulation grids
Shape optimization approaches to inverse design offer low-dimensional,
physically-guided parameterizations of structures by representing them as
combinations of shape primitives. However, on discretized rectilinear
simulation grids, computing the gradient of a user objective via the adjoint
variables method requires a sum reduction of the forward/adjoint field
solutions and the Jacobian of the simulation material distribution with respect
to the structural shape parameters. These shape parameters often perturb large
or global parts of the simulation grid resulting in many non-zero Jacobian
entries, which are typically computed by finite-difference in practice.
Consequently, the gradient calculation can be non-trivial. In this work we
propose to accelerate the gradient calculation by invoking automatic
differentiation (AutoDiff) in instantiations of structural material
distributions. In doing so, we develop extensible differentiable mappings from
shape parameters to shape primitives and differentiable effective logic
operations (denoted AutoDiffGeo). These AutoDiffGeo definitions may introduce
some additional discretization error into the field solutions because they
relax notions of sub-pixel smoothing along shape boundaries. However, we show
that some mappings (e.g. simple cuboids) can achieve zero error with respect to
volumetric averaging strategies. We demonstrate AutoDiff enhanced shape
optimization using three integrated photonic examples: a multi-etch blazed
grating coupler, a non-adiabatic waveguide transition taper, and a
polarization-splitting grating coupler. We find accelerations of the gradient
calculation by AutoDiff relative to finite-difference often exceed 50x,
resulting in total wall time accelerations of 4x or more on the same hardware
with little or no compromise to final device performance. Our code is available
open source at https://github.com/smhooten/emoptComment: 29 pages, 15 figure
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