Distributed simulation and optimization of large-area metasurfaces
Abstract/Contents
- Abstract
- Emerging technologies such as augmented reality, lidar, and mobile imaging have opened a large market for complex, compact, and mass-producible optical systems. Metasurfaces are a promising building block for such next-generation systems. These flat optical elements can use subwavelength scatterers to control light, and can be mass-produced in the same advanced semiconductor foundries that have enabled successful scaling of consumer electronics. However, although metasurface functionality can be experimentally demonstrated, simulating metasurfaces is a central challenge in metasurface design. This simulation challenge arises because metasurfaces typically span thousands of wavelengths in linear dimension, rendering traditional electromagnetic simulation techniques (e.g. Finite-Difference and Finite-Element methods) intractable. Here, we present a metasurface simulation distribution strategy that can preserve the simulation accuracy while allowing scalability to arbitrarily-large areas. Using this distribution strategy with a GPU-based implementation of the Transition-matrix (T-matrix) method, we show a record-size 3-dimensional metasurface simulation (over 600 lambda by 600 lambda) that accurately accounts for scatterer-scatterer interactions significantly beyond the commonly-used locally periodic approximation. We then demonstrate gradient-based optimization of single and multilayer metasurfaces using our distributed T-matrix method. Finally, we discuss using the distribution strategy with Finite-Difference Time-Domain solvers to handle arbitrary scatterer geometries.
Description
| Type of resource | text |
|---|---|
| Form | electronic resource; remote; computer; online resource |
| Extent | 1 online resource. |
| Place | California |
| Place | [Stanford, California] |
| Publisher | [Stanford University] |
| Copyright date | 2022; ©2022 |
| Publication date | 2022; 2022 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Author | Skarda, Jinhie Lee |
|---|---|
| Degree supervisor | Vuckovic, Jelena |
| Thesis advisor | Vuckovic, Jelena |
| Thesis advisor | Fan, Jonathan Albert |
| Thesis advisor | Miller, D. A. B |
| Degree committee member | Fan, Jonathan Albert |
| Degree committee member | Miller, D. A. B |
| Associated with | Stanford University, Department of Electrical Engineering |
Subjects
| Genre | Theses |
|---|---|
| Genre | Text |
Bibliographic information
| Statement of responsibility | Jinhie Skarda. |
|---|---|
| Note | Submitted to the Department of Electrical Engineering. |
| Thesis | Thesis Ph.D. Stanford University 2022. |
| Location | https://purl.stanford.edu/zk069ch7237 |
Access conditions
- Copyright
- © 2022 by Jinhie Lee Skarda
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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