Nanophotonic structures have versatile applications including solar cells, antireflective coatings, electromagnetic interference shielding, optical filters, and light emitting diodes. To design and understand these nanophotonic structures, electrodynamic simulations are essential. These simulations enable us to model electromagnetic fields over time and calculate optical properties. In this work, we introduce frameworks and benchmarks to evaluate nanophotonic structures in the context of parametric structure design problems. The benchmarks are instrumental in assessing the performance of optimization algorithms and identifying an optimal structure based on target optical properties. Moreover, we explore the impact of varying grid sizes in electrodynamic simulations, shedding light on how evaluation fidelity can be strategically leveraged in enhancing structure designs.
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This content will become publicly available on January 1, 2025
Multi-BOWS: multi-fidelity multi-objective Bayesian optimization with warm starts for nanophotonic structure design
The design of optical devices is a complex and time-consuming process. To simplify this process, we
present a novel framework of multi-fidelity multi-objective Bayesian optimization with warm starts,
called Multi-BOWS. This approach automatically discovers new nanophotonic structures by managing
multiple competing objectives and utilizing multi-fidelity evaluations during the design process. We
employ our Multi-BOWS method to design an optical device specifically for transparent electromagnetic
shielding, a challenge that demands balancing visible light transparency and effective protection against
electromagnetic waves. Our approach leverages the understanding that simulations with a coarser mesh
grid are faster, albeit less accurate than those using a denser mesh grid. Unlike the earlier multi-fidelity
multi-objective method, Multi-BOWS begins with faster, less accurate evaluations, which we refer to as
“warm-starting,” before shifting to a dense mesh grid to increase accuracy. As a result, Multi-BOWS
demonstrates 3.2–89.9% larger normalized area under the Pareto frontier, which measures a balance
between transparency and shielding effectiveness, than low-fidelity only and high-fidelity only
techniques for the nanophotonic structures studied in this work. Moreover, our method outperforms an
existing multi-fidelity method by obtaining 0.5–10.3% larger normalized area under the Pareto frontier
for the structures of interest.
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- Award ID(s):
- 2239527
- NSF-PAR ID:
- 10490622
- Publisher / Repository:
- Royal Society of Chemistry
- Date Published:
- Journal Name:
- Digital Discovery
- ISSN:
- 2635-098X
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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