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20222026
most citedAccurate Memory Kernel Extraction from Discretized Time Series Data

17 citations · 17 across the 8 of their papers we have counts for

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physics.bio-ph2026

Memory-resolved prediction of ligand residence times on the minutes timescale

Hossein Batebi, Lucas Tepper, Roland R. Netz

AI-enabled computational drug discovery is advancing rapidly in predicting molecular structures, binding poses and affinities, but ligand dissociation kinetics remain harder to acc…

cond-mat.soft2026

Position-dependent friction in protein folding from a GLE derived with a non-stationary localized projection distribution

Salma Salem, Lucas Tepper, Benjamin J. A. Héry +3

The Generalized Langevin Equation (GLE) is an integro-differential equation of motion for a general observable of a many-body system and is rigorously derived using the projection…

physics.bio-ph2026

Reaction-Coordinate-Dependent Non-Markovian Friction Governs Protein-Folding Dynamics

Lucas Tepper, Benjamin J. A. Héry, Cihan Ayaz +4

It is common to project the full atomic-resolution representation of a protein onto a one-dimensionalreaction coordinate (RC) to capture the protein-folding kinetics. As a direct c…

cond-mat.stat-mech2026

Comparison of different exact generalized Langevin equations with a non-linear potential of mean force and an observable-dependent mass and friction

Benjamin J. A. Héry, Lucas Tepper, Roland R. Netz

The Mori-Zwanzig projection formalism constitutes a powerful and robust framework for deriving equations of motion in terms of generalized Langevin equations (GLEs) for an arbitrar…

cond-mat.stat-mech2026

Non-equilibrium generalized Langevin equation for multi-dimensional observables

Benjamin J. A. Héry, Lucas Tepper, Andrea Guljas +4

The Mori-Zwanzig formalism is a powerful theoretical framework for deriving equations of motion for coarse-grained observables in the form of generalized Langevin equations (GLEs)…