2 citations · 2 across the 6 of their papers we have counts for
6 papers
RepNN: Tackling spectral bias in deep neural networks for regression and PDE problems via parameter reparameterization
Yong Wang, Tao Zhou, Xuhui Meng
Deep neural networks (DNNs) have achieved remarkable success in scientific computing, yet they often suffer from spectral bias in capturing oscillatory and multiscale behaviors. In…
Dynamical Steering and Unambiguous Signature of Majorana Corner Modes in Altermagnetic Josephson Junctions
Yu-Xuan Li, Tao Zhou
Dynamical manipulation of Majorana zero modes and their unambiguous distinction from topologically trivial states remain paramount challenges in topological quantum computation. He…
DONUT: Physics-aware Machine Learning for Real-time X-ray Nanodiffraction Analysis
Aileen Luo, Tao Zhou, Ming Du +3
Coherent X-ray scattering techniques are critical for investigating the fundamental structural properties of materials at the nanoscale. While advancements have made these experime…
Homomorphic data compression for real time photon correlation analysis
Sebastian Strempfer, Zichao Wendy Di, Kazutomo Yoshii +8
The construction of highly coherent x-ray sources has enabled new research opportunities across the scientific landscape. The maximum raw data rate per beamline now exceeds 40 GB/s…
Deep Learning of Structural Morphology Imaged by Scanning X-ray Diffraction Microscopy
Aileen Luo, Tao Zhou, Martin V. Holt +2
Scanning X-ray nanodiffraction microscopy is a powerful technique for spatially resolving nanoscale structural morphologies by diffraction contrast. One of the critical challenges…
Data-driven discovery of dynamics from time-resolved coherent scattering
Nina Andrejevic, Tao Zhou, Qingteng Zhang +3
Coherent X-ray scattering (CXS) techniques are capable of interrogating dynamics of nano- to mesoscale materials systems at time scales spanning several orders of magnitude. Howeve…