activity
20242026
collaborators

5 papers

physics.chem-ph2026

Can DFT-trained neural network potentials reproduce structure, solvation, and water-exchange properties in aqueous magnesium solutions?

Sebastian Falkner, Pablo Montero de Hijes, Christoph Dellago +1

Magnesium ions play an essential role in many biological processes but remain challenging to model in biomolecular simulations. Despite considerable scientific effort, classical fo…

physics.comp-ph2026

An Always-Accepting Algorithm for Transition Path Sampling

Magdalena Häupl, Sebastian Falkner, Peter G. Bolhuis +2

We present a one-way shooting algorithm for transition path sampling that accepts every proposed trajectory, yet samples the correct transition path ensemble for systems with overd…

cond-mat.soft2025

Non-Markovian dynamics in ice nucleation

Pablo Montero de Hijes, Sebastian Falkner, Christoph Dellago

In simulation studies of crystallisation, the size of the largest crystalline nucleus is often used as a reaction coordinate to monitor the progress of the nucleation process. Here…

physics.comp-ph2025

Revisiting Shooting Point Monte Carlo Methods for Transition Path Sampling

Sebastian Falkner, Alessandro Coretti, Baron Peters +2

Rare event sampling algorithms are essential for understanding processes that occur infrequently on the molecular scale, yet they are important for the long-time dynamics of comple…

physics.comp-ph2024

Boltzmann Generators and the New Frontier of Computational Sampling in Many-Body Systems

Alessandro Coretti, Sebastian Falkner, Jan Weinreich +2

The paper by Noé et al. [F. Noé, S. Olsson, J. Köhler and H. Wu, Science, 365:6457 (2019)] introduced the concept of Boltzmann Generators (BGs), a deep generative model that can…