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cond-mat.str-el2026
Neural network backflow for ab-initio solid calculations
An-Jun Liu, Bryan K. Clark
Accurately simulating extended periodic systems is a central challenge in condensed matter physics. Neural quantum states (NQS) offer expressive wavefunctions for this task but fac…
cond-mat.str-el2025
Enhancing Neural Network Backflow
Kieran Loehr, Bryan K. Clark
Accurately describing the ground state of strongly correlated systems is essential for understanding their emergent properties. Neural Network Backflow (NNBF) is a powerful variati…