138 citations · 213 across the 8 of their papers we have counts for
9 papers
Correlation-Free Transition Path Sampling through Shooting Point Generation Guided by Committor Learning
Maximilian Negedly, Sebastian Falkner, Alessandro Coretti +1
Studying the dynamical behavior of a system often depends on characterizing how it transitions between long-lived states. Because such transitions are rare, observing them usually…
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…
Nonadiabatic Forward-Flux Sampling of Rare Molecular Gas-Phase Ammonia Photodissociation
Madlen Maria Reiner, Johannes C. B. Dietschreit, Leticia González +1
Simulating rare events in photochemistry by brute-force surface hopping is computationally prohibitive: most propagated trajectories either remain nonreactive or follow dominant re…
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…
NATPS: Nonadiabatic Transition Path Sampling Using Time-Reversible MASH Dynamics
Xiran Yang, Madlen Maria Reiner, Brigitta Bachmair +3
Rare nonadiabatic events play a central role in photochemistry but remain difficult to simulate because excited-state dynamics is computationally demanding and often stochastic. He…
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…
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 pr…
Autonomous artificial intelligence discovers mechanisms of molecular self-organization in virtual experiments
Hendrik Jung, Roberto Covino, A Arjun +2
Molecular self-organization driven by concerted many-body interactions produces the ordered structures that define both inanimate and living matter. Understanding the physical mech…
Escape dynamics of active particles in multistable potentials
Andrei Militaru, Max Innerbichler, Martin Frimmer +3
Rare transitions between long-lived metastable states underlie a great variety of physical, chemical and biological processes. Our quantitative understanding of reactive mechanisms…