A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.
This work introduces benchmarks for evaluating nanophotonic structures in design simulations.
Bayesian optimization improved for nanophotonic device design.
Deep learning simplifies nanophotonic device physics.
We apply numerical methods in combination with finite-difference-time-domain (FDTD) simulations to optimize transmission properties of plasmonic mirror color filters using a multi-objective figure of merit over a five-dimensional parameter space by utilizing novel multi-fidelity Gaussian processes approach. We compare …
Designs chiral photonic structures using machine learning for efficient optical properties.