1 citations · 1 across the 4 of their papers we have counts for
5 papers
Denoising Diffusion Monte Carlo Electron Densities with Physically Informed Variance Stabilization: From Fourier Filters to 3D UNETs
Kenneth O. Berard, Brenda Rubenstein, Jaron T. Krogel
Obtaining accurate electron densities is important for the fundamental description of molecular and condensed matter systems, as well as for the development of next-generation dens…
Identifying Band Inversions in Topological Materials Using Diffusion Monte Carlo
Annette Lopez, Cody A. Melton, Jeonghwan Ahn +2
Topological insulators are characterized by insulating bulk states and robust metallic surface states. Band inversion is a hallmark of topological insulators: at time-reversal inva…
Toward improved property prediction of 2D materials using many-body quantum Monte Carlo methods
Daniel Wines, Jeonghwan Ahn, Anouar Benali +10
The field of two-dimensional (2D) materials has grown dramatically in the last two decades. 2D materials can be utilized for a variety of next-generation optoelectronic, spintronic…
Atomistic Descriptor Optimization Using Complementary Euclidean and Geodesic Distance Information
Gopal R. Iyer, Brenda M. Rubenstein
Descriptors are physically-inspired schemes for representing atomistic systems that play a central role in the construction of models of potential energy surfaces. Although physica…
Force-free identification of minimum-energy pathways and transition states for stochastic electronic structure theories
Gopal R. Iyer, Noah Whelpley, Juha Tiihonen +3
Stochastic electronic structure theories, e.g., Quantum Monte Carlo methods, enable highly accurate total energy calculations which in principle can be used to construct highly acc…