activity
19992023
most citedThe spectral weight of the Hubbard model through cluster perturbation theory

403 citations · 957 across the 25 of their papers we have counts for

collaborators
Showing 2020Show all

6 papers · 1 filter

cs.DC2020★ 4 cited

Rapid Exploration of Optimization Strategies on Advanced Architectures using TestSNAP and LAMMPS

Rahulkumar Gayatri, Stan Moore, Evan Weinberg +5

The exascale race is at an end with the announcement of the Aurora and Frontier machines. This next generation of supercomputers utilize diverse hardware architectures to achieve t…

cs.DC2020

Resource allocation for task-level speculative scientific applications: a proof of concept using Parallel Trajectory Splicing

Andrew Garmon, Vinay Ramakrishnaiah, Danny Perez

The constant increase in parallelism available on large-scale distributed computers poses major scalability challenges to many scientific applications. A common strategy to improve…

cond-mat.stat-mech2020

Arbitrarily accurate representation of atomistic dynamics via Markov Renewal Processes

Animesh Agarwal, Sandrasegaram Gnanakaran, Nicholas Hengartner +2

Atomistic simulations with methods such as molecular dynamics are extremely powerful tools to understand nanoscale dynamical behavior. The resulting trajectories, by the virtue of…

cond-mat.mtrl-sci2020★ 3 cited

Statistical mechanics of kinks on a gliding screw dislocation

M. Boleininger, M. Gallauer, S. L. Dudarev +3

The ability of a body-centered cubic metal to deform plastically is limited by the thermally activated glide motion of screw dislocations, which are line defects with a mobility ex…

physics.comp-ph2020

Automated calculation and convergence of defect transport tensors

Thomas D Swinburne, Danny Perez

Defect transport is a key process in materials science and catalysis, but as migration mechanisms are often too complex to enumerate a priori, calculation of transport tensors typi…

physics.comp-ph2020

An Entropy-Maximization Approach to Automated Training Set Generation for Interatomic Potentials

Mariia Karabin, Danny Perez

Machine learning (ML)-based interatomic potentials are currently garnering a lot of attention as they strive to achieve the accuracy of electronic structure methods at the computat…