158 citations · 298 across the 10 of their papers we have counts for
12 papers
Surface Phase Diagrams from Nested Sampling
Mingrui Yang, Livia B. Pártay, Robert B. Wexler
Studies in atomic-scale modeling of surface phase equilibria often focus on temperatures near zero Kelvin due to the challenges in calculating the free energy of surfaces at finite…
A general-purpose machine learning Pt interatomic potential for an accurate description of bulk, surfaces and nanoparticles
Jan Kloppenburg, Livia B. Pártay, Hannes Jónsson +1
A Gaussian approximation machine learning interatomic potential for platinum is presented. It has been trained on DFT data computed for bulk, surfaces and nanostructured platinum,…
Carbon phase diagram with empirical and machine learned interatomic potentials
George Marchant, Bora Karasulu, Livia B. Partay
In the present work we detail how the many-body potential energy landscape of interatomic potentials for carbon can be explored by utilising the nested sampling algorithm, allowing…
Nested sampling for physical scientists
Greg Ashton, Noam Bernstein, Johannes Buchner +20
We review Skilling's nested sampling (NS) algorithm for Bayesian inference and more broadly multi-dimensional integration. After recapitulating the principles of NS, we survey deve…
Machine-learned Interatomic Potentials for Alloys and Alloy Phase Diagrams
Conrad W. Rosenbrock, Konstantin Gubaev, Alexander V. Shapeev +4
We introduce machine-learned potentials for Ag-Pd to describe the energy of alloy configurations over a wide range of compositions. We compare two different approaches. Moment tens…
Direct computation of the quantum partition function by path-integral nested sampling
Bela Szekeres, Livia B. Partay, Edit Matyus
In the present work we introduce a computational approach to the absolute rovibrational quantum partition function using the path-integral formalism of quantum mechanics in combina…