Controlling light: Methods for inverse design of nonlinear nanophotonic waveguides on chip
Doktorsavhandling, 2025

The nonlinear response of optical materials is in general very weak. In order to make use of these nonlinear interactions for optical processes in integrated optical devices, such as optical parametric amplifiers, we often need very long waveguides to achieve appreciable efficiency. These waveguides can have lengths of the order of metres and need to fulfil multiple requirements over a range of wavelengths.

Modern advances in manufacturing and nanophotonics have made possible a high degree of tailoring of waveguide geometries for near-field light enhancement to meet these requirements. However, simulating and designing these nonlinear integrated optical devices is challenging.

In this thesis, I will present methods for simulating periodic optical waveguide structures with nontrivial unit cells, and how we can use knowledge of the physics to tailor the mesh adaptation in finite-element simulations to electrodynamic problems. I will also present how we can combine machine learning and physics for scattering problems and how we can use inverse design to suggest waveguide cross sections that fulfil multiple design requirements on dispersion characteristics.

FEM

machine learning

FWM

Inverse design

metamaterials

OPA

four wave mixing

Nanophotonics

waveguide

nonlinear optics

parametric amplifiers

PSA

AI

PJ-salen, byggnad Fysik Origo, Fysikgården 1, Göteborg
Opponent: Prof. Peter Wiecha, National Centre for Scientific Research (CNRS), Frankrike

Författare

Albin Jonasson Svärdsby

Chalmers, Fysik, Kondenserad materie- och materialteori

Adaptive meshing strategies for nanophotonics using a posteriori error estimation

Optics Express,;Vol. 32(2024)p. 24592-24602

Artikel i vetenskaplig tidskrift

Viktor A. Lilja, Albin J. Svärdsby, Timo Gahlmann, and Philippe Tassin. A general framework for knowledge integration in machine learning for electromagnetic scattering using quasinormal modes

Albin J. Svärdsby and Philippe Tassin. Determining the dispersion and nonlinear characteristics of 3D periodic waveguides using finite-element eigenmode simulations

Albin J. Svärdsby et. al . Inverse design of optical waveguides for phase-sensitive amplifiers using machine learning

Towards achieving Goldilocks designs for optics
Fascinating physics can occur in materials. If you shine rays of light with different colours into a
material and the conditions are just right, quantum effects can produce another ray of light with a
different colour. If the conditions are just right...

In order for these conditions to be just right, we need to manufacture our devices with nanometre-
level precision so that the features of the structure are smaller than the wavelength of the light. This
poses considerable manufacturing challenges, but modern advances in manufacturing have now en-
abled us to be this precise. However, before we build it we need to know what is just right...

To achieve this, we use simulations to predict the behaviour of our devices. These simulations can
take a long time and be computationally expensive and this poses a challenge for us when we want to
create good designs that are just right...

In this thesis I will present work that decreases the computational cost associated with the simulation
of devices that guide light and how we can use AI to assist us in predicting device designs that control
light in a desired way, so that the conditions become just right.

Utveckling av nya fotoniska metaytor med hjälp av artificiell intelligens

Vetenskapsrådet (VR) (2020-05284), 2020-12-01 -- 2024-11-30.

Ämneskategorier (SSIF 2025)

Atom- och molekylfysik och optik

Annan fysik

Infrastruktur

Chalmers e-Commons (inkl. C3SE, 2020-)

DOI

10.63959/chalmers.dt/5813

ISBN

978-91-8103-356-4

Doktorsavhandlingar vid Chalmers tekniska högskola. Ny serie: 5813

Utgivare

Chalmers

PJ-salen, byggnad Fysik Origo, Fysikgården 1, Göteborg

Opponent: Prof. Peter Wiecha, National Centre for Scientific Research (CNRS), Frankrike

Mer information

Senast uppdaterat

2026-02-03