Spectral methods are of fundamental importance in statistics and machine learning, because they underlie algorithms from classical principal components analysis to more recent approaches that exploit ...

This paper presents a new approach to spectral methods for initial boundary value problems. A filtered version of the partial differential equation and the initial and boundary conditions at an ...

Researchers have created a new method to extract the static and dynamic structure of complex chemical systems. In this context, 'structure' doesn't just mean the 3-D arrangement of atoms that make up ...

TSRS boosts the sensitivity of SRS to sub-mM level while maintaining the nature-linewidth-limit spectral lines. This method may find applications in high-density bio-orthogonal labeling, ...

DeePFAS, a novel deep-learning model, streamlines large-scale non-targeted screening of "forever chemicals" (PFAS) by ...