3 papers
cond-mat.mtrl-sci2025
Active learning potentials for first-principles phase diagrams using replica-exchange nested sampling
Nico Unglert, Michael Ketter, Georg K. H. Madsen
Accurate prediction of materials phase diagrams from first principles remains a central challenge in computational materials science. Machine-learning interatomic potentials can pr…
physics.comp-ph2025
msmJAX: Fast and Differentiable Electrostatics on the GPU in Python
Florian Buchner, Johannes Schörghuber, Nico Unglert +2
We present msmJAX, a Python package implementing the multilevel summation method with B-spline interpolation, a linear-scaling algorithm for efficiently evaluating electrostatic an…
cond-mat.stat-mech2025
Replica exchange nested sampling
Nico Unglert, Livia Bartók Pártay, Georg K. H. Madsen
Nested sampling (NS) has emerged as a powerful tool for exploring thermodynamic properties in materials science. However, its efficiency is often hindered by the limitations of Mar…