2 papers
cond-mat.mtrl-sci2026
Comparative study of ensemble-based uncertainty quantification methods for neural network interatomic potentials
Yonatan Kurniawan, Mingjian Wen, Ellad B. Tadmor +1
Machine learning interatomic potentials (MLIPs) enable atomistic simulations with near first-principles accuracy at substantially reduced computational cost, making them powerful t…
nucl-th2026
One-Body and Two-Body Density Matrix Elements in a Symplectic Many-Body Basis
Jakub Herko, Mark A. Caprio
The symplectic no-core configuration interaction (SpNCCI) framework is an ab initio many-body method for nuclear structure which makes use of the approximate symplectic symmetry of…