108 citations · 110 across the 3 of their papers we have counts for
8 papers
Lightshow: a Python package for generating computational x-ray absorption spectroscopy input files
Matthew R. Carbone, Fanchen Meng, Christian Vorwerk +7
First-principles computational spectroscopy is a critical tool for interpreting experiment, performing structure refinement, and developing new physical understanding. Systematical…
When not to use machine learning: a perspective on potential and limitations
M. R. Carbone
The unparalleled success of artificial intelligence (AI) in the technology sector has catalyzed an enormous amount of research in the scientific community. It has proven to be a po…
Numerically Exact Generalized Green's Function Cluster Expansions for Electron-Phonon Problems
Matthew R. Carbone, David R. Reichman, John Sous
We generalize the family of approximate momentum average methods to formulate a numerically exact, convergent hierarchy of equations whose solution provides an efficient algorithm…
Predicting impurity spectral functions using machine learning
Erica J. Sturm, Matthew R. Carbone, Deyu Lu +2
The Anderson Impurity Model (AIM) is a canonical model of quantum many-body physics. Here we investigate whether machine learning models, both neural networks (NN) and kernel ridge…
Microscopic model of the doping dependence of line widths in monolayer transition metal dichalcogenides
Matthew R. Carbone, Matthew Z. Mayers, David R. Reichman
A fully microscopic model of the doping-dependent exciton and trion line widths in the absorption spectra of monolayer transition metal dichalcogenides in the low temperature and l…
Effective Trap-like Activated Dynamics in a Continuous Landscape
Matthew R. Carbone, Valerio Astuti, Marco Baity-Jesi
We use a simple model to extend network models for activated dynamics to a continuous landscape with a well-defined notion of distance and a direct connection to many-body systems.…