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Found 4 papers, 1 papers with code
A neural operator-based surrogate solver for free-form electromagnetic inverse design
Neural operators have emerged as a powerful tool for solving partial differential equations in the context of scientific machine learning.
On enhanced sensing of chiral molecules in optical cavities
The differential response of chiral molecules to incident left- and right- handed circularly polarized light is used for sensing the handedness of molecules.
Optics Chemical Physics
Bayesian optimization with improved scalability and derivative information for efficient design of nanophotonic structures
We propose the combination of forward shape derivatives and the use of an iterative inversion scheme for Bayesian optimization to find optimal designs of nanophotonic devices.
Benchmarking five global optimization approaches for nano-optical shape optimization and parameter reconstruction
Numerical optimization is an important tool in the field of computational physics in general and in nano-optics in specific.
