activity
20122026
most citedInformation-theoretic vs. thermodynamic entropy production in autonomous sensory networks

80 citations · 156 across the 16 of their papers we have counts for

collaborators

16 papers

cond-mat.stat-mech2026

Non-negative differential mobility of one-dimensional underdamped Langevin dynamics: Proof via mapping to a marginally stable oscillator

Udo Seifert

For an underdamped particle driven by a constant non-conservative force across a periodic potential in one spatial dimension at finite temperature, numerical studies have shown tha…

cond-mat.stat-mech2026

Generalizing the multidimensional thermodynamic uncertainty relation to combinations of arbitrary counting variables

Niklas Buschmann, Udo Seifert, Alexander M. Maier

Uncertainty relations provide lower bounds for otherwise hidden quantities of a partially accessible Markov network like the mean entropy production rate and the total dynamical ac…

cond-mat.stat-mech2026

Lower bounds on entropy production from dynamical correlation functions

Paul Raux, Alexander M. Maier, Udo Seifert

Entropy production is a key property in stochastic thermodynamics. For partially observed and coarse-grained systems, its inference is challenging and typically rests on proven low…

cond-mat.stat-mech2026

Waiting-time based entropy estimators in continuous space without Markovian events

Jonas H. Fritz, Udo Seifert

Estimating entropy production in continuous systems that can only be observed with a limited resolution remains an open problem in stochastic thermodynamics. Existing estimators ba…

cond-mat.stat-mech2025

Universal bounds on entropy production from fluctuating coarse-grained trajectories

Udo Seifert

Entropy production is arguably the most universally applicable measure of non-equilibrium behavior, particularly for systems coupled to a heat bath. This setting encompasses driven…

cond-mat.stat-mech2025★ 2 cited

Compensating random transition-detection blackouts in Markov networks

Alexander M. Maier, Benjamin Häsler, Udo Seifert

In Markov networks, measurement blackouts with unknown frequency compromise observations such that thermodynamic quantities can no longer be inferred reliably. In particular, the o…