5 citations · 5 across the 4 of their papers we have counts for
5 papers
Generative Nested Sampling of Atomistic Thermodynamic Landscapes
Alessandro Coretti, Nico Unglert, Sebastian Falkner +2
Nested sampling (NS) resolves the thermodynamics of an atomistic system from a single simulation, but its practical reach is limited by the Markov-chain updates needed to decorrela…
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…
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…
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…
Neural-Network Force Field Backed Nested Sampling: Study of the Silicon p-T Phase Diagram
N. Unglert, J. Carrete, L. B. Pártay +1
Nested sampling is a promising method for calculating phase diagrams of materials, however, the computational cost limits its applicability if ab-initio accuracy is required. In th…