activity
20232026
collaborators

6 papers

cond-mat.stat-mech2026

Optimal parameterization of nonequilibrium generalized master equations from discrete-time experimental data

Chih-Wei Joshua Liu, Jérémie Klinger, Grant M. Rotskoff

Kinetic analyses of experiments often require coarse-grained descriptions, but complex systems rarely conform to the widely used modeling assumptions of Markovianity and thermodyna…

cond-mat.stat-mech2025

Minimally dissipative multi-bit logical operations

Jérémie Klinger, Grant M. Rotskoff

Modern computing architectures are vastly more energy-dissipative than fundamental thermodynamic limits suggest, motivating the search for principled approaches to low-dissipation…

cond-mat.stat-mech2025

Large volume statistics of first-passage observables of -dimensional Jump Processes

Jérémie Klinger, Olivier Bénichou, Raphaël Voituriez

First-passage observables (FPO) are central to understanding stochastic processes in confined domains, with applications spanning chemical reaction kinetics, foraging behavior, and…

cond-mat.stat-mech2024

Computing Nonequilibrium Responses with Score-shifted Stochastic Differential Equations

Jérémie Klinger, Grant M. Rotskoff

Using equilibrium fluctuations to understand the response of a physical system to an externally imposed perturbation is the basis for linear response theory, which is widely used t…

cond-mat.stat-mech2024

Universal energy-speed-accuracy trade-offs in driven nonequilibrium systems

Jérémie Klinger, Grant M. Rotskoff

Physical systems driven away from equilibrium by an external controller dissipate heat to the environment; the excess entropy production in the thermal reservoir can be interpreted…

cond-mat.stat-mech2023

Extreme Value Statistics of Jump Processes

Jérémie Klinger, Raphaël Voituriez, Olivier Bénichou

We investigate extreme value statistics (EVS) of general discrete time and continuous space symmetric jump processes. We first show that for unbounded jump processes, the semi-infi…