3 papers
cond-mat.mtrl-sci2026
Composable and adaptive design of machine learning interatomic potentials guided by Fisher-information analysis
Weishi Wang, Mark K. Transtrum, Vincenzo Lordi +2
An adaptive physics-inspired model design strategy for machine-learning interatomic potentials (MLIPs) is proposed. This strategy relies on iterative reconfigurations of composite…
quant-ph2026
Putting fermions onto a digital quantum computer
Riley W. Chien, Mitchell L. Chiew, Brent Harrison +8
Quantum computers are expected to become a powerful tool for studying physical quantum systems. Consequently, a number of quantum algorithms for studying the physical properties of…
physics.chem-ph2025
Encoding electronic ground-state information with variational even-tempered basis sets
Weishi Wang, Casey Dowdle, James D. Whitfield
We propose a system-oriented basis-set design based on even-tempered basis functions to variationally encode electronic ground-state information into molecular orbitals. First, we…