Time-Resolved Statistics of Snippets as General Framework for Model-Free Entropy Estimators

Degünther, Julius; Seifert, Udo

doi:10.1103/physrevlett.130.257101

Cited by 17 publications

(8 citation statements)

References 48 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A transition I + and I − ends if endpoints B and A, respectively, are reached. Crucially, the state of the system is fully characterized each time a transition is finished, because reaching a milestone A or B is a Markovian event [17]. In contrast to transitions between discrete states, the continuous ones possess a finite duration, which ends when the milestone is reached.…”

Section: Modelmentioning

confidence: 99%

“…for the example shown in figure 3(b). Since the sums equal the waiting-times in ( 14), the path weight (17) becomes…”

Section: Entropy Estimatormentioning

confidence: 99%

“…Surprisingly, these estimators recover the full entropy production rate in a uni-cyclic system with a single observed transition. More generally, the waiting-time approach can be applied to any observations of Markovian events [17], not only to transitions.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Entropy production from waiting-time distributions for overdamped Langevin dynamics

Meyberg,

Degünther,

Seifert

2024

J. Phys. A: Math. Theor.

View full text Add to dashboard Cite

For a Markovian dynamics on discrete states, the logarithmic ratio of waiting-time distributions between two successive, instantaneous transitions in forward and backward direction is a measure of time-irreversibility. It thus serves as an entropy estimator, which is exact in the case of a uni-cyclic network. We adopt this framework to overdamped Langevin dynamics, where such transitions have finite duration. By introducing milestones based on the observation of a particle at at least two milestones and an additional third event, we identify an entropy estimator that becomes exact for driven motion along a one-dimensional potential.

show abstract

Section: Modelmentioning

confidence: 99%

“…for the example shown in figure 3(b). Since the sums equal the waiting-times in ( 14), the path weight (17) becomes…”

Section: Entropy Estimatormentioning

confidence: 99%

See 1 more Smart Citation

Entropy production from waiting-time distributions for overdamped Langevin dynamics

Meyberg,

Degünther,

Seifert

2024

J. Phys. A: Math. Theor.

View full text Add to dashboard Cite

show abstract

“…Indeed, in order to have a lower bound one should consider the entropy production of the non-Markovian coarsegrained process. Here, instead, we consider an approximate Markovian process and, as it is shown in [13], its entropy production could also be larger than the entropy production of the microscopic system. Let us now consider in more detail the expected…”

Section: Empirical Estimate Of the Entropy Productionmentioning

confidence: 99%

“…Among the interesting issues which deserve investigation, one should include the design of efficient methods to characterise the 'degree of irreversibility', something also called 'distance from equilibrium' [7], which typically requires a proper modelling with a suitable mathematical description of the system [8][9][10][11][12][13]. In this paper we discuss the role of Gaussian or non-Gaussian statistics for discriminating the degree of irreversibility of a system.…”

Section: Introductionmentioning

confidence: 99%

Statistical features of systems driven by non-Gaussian processes: theory & practice

Lucente,

Puglisi,

Viale

et al. 2023

J. Stat. Mech.

View full text Add to dashboard Cite

Nowadays many tools, e.g. fluctuation relations, are available to characterize the statistical properties of non-equilibrium systems. However, most of these tools rely on the assumption that the driving noise is normally distributed. Here we consider a class of Markov processes described by Langevin equations driven by a mixture of Gaussian and Poissonian noises, focusing on their non-equilibrium properties. In particular, we prove that detailed balance does not hold even when correlation functions are symmetric under time reversal. In such cases, a breakdown of the time reversal symmetry can be highlighted by considering higher order correlation functions. Furthermore, the entropy production may be different from zero even for vanishing currents. We provide analytical expressions for the average entropy production rate in several cases. We also introduce a scale dependent estimate for entropy production, suitable for inference from experimental signals. The empirical entropy production allows us to discuss the role of spatial and temporal resolutions in characterizing non-equilibrium features. Finally, we revisit the Brownian gyrator introducing an additional Poissonian noise showing that it behaves as a two dimensional linear ratchet. It has also the property that when Onsager relations are satisfied its entropy production is positive although it is minimal. We conclude discussing estimates of entropy production for partially accessible systems, comparing our results with the lower bound provided by the thermodynamic uncertainty relations.

show abstract

Stochastic thermodynamics for biological functions

Cao,

Liang

2024

Quant. Biol.

View full text Add to dashboard Cite

Living systems operate within physical constraints imposed by nonequilibrium thermodynamics. This review explores recent advancements in applying these principles to understand the fundamental limits of biological functions. We introduce the framework of stochastic thermodynamics and its recent developments, followed by its application to various biological systems. We emphasize the interconnectedness of kinetics and energetics within this framework, focusing on how network topology, kinetics, and energetics influence functions in thermodynamically consistent models. We discuss examples in the areas of molecular machine, error correction, biological sensing, and collective behaviors. This review aims to bridge physics and biology by fostering a quantitative understanding of biological functions.

show abstract

Time-Resolved Statistics of Snippets as General Framework for Model-Free Entropy Estimators

Cited by 17 publications

References 48 publications

Entropy production from waiting-time distributions for overdamped Langevin dynamics

Entropy production from waiting-time distributions for overdamped Langevin dynamics

Statistical features of systems driven by non-Gaussian processes: theory & practice

Stochastic thermodynamics for biological functions

Contact Info

Product

Resources

About