15 citations · 15 across the 1 of their papers we have counts for
3 papers
Anticipating Decoherence for Enhancing Coherence in Quantum Systems
Pranshu Maan, Yuheng Chen, Sean Borneman +6
Large-scale quantum systems require optical coherence between distant quantum devices, necessitating spectral indistinguishability. Scalable solid-state platforms offer promising r…
Machine-Learning-Assisted Photonic Device Development: A Multiscale Approach from Theory to Characterization
Yuheng Chen, Alexander Montes McNeil, Taehyuk Park +16
Photonic device development (PDD) has achieved remarkable success in designing and implementing new devices for controlling light across various wavelengths, scales, and applicatio…
PearSAN: A Machine Learning Method for Inverse Design using Pearson Correlated Surrogate Annealing
Michael Bezick, Blake A. Wilson, Vaishnavi Iyer +6
PearSAN is a machine learning-assisted optimization algorithm applicable to inverse design problems with large design spaces, where traditional optimizers struggle. The algorithm l…