2021/02/28 by Sreekanth K Manikandan, Subhrokoli Ghosh, Avijit Kundu +5
Chemistry · Engineering · Mathematics · Physics and Astronomy · #Advanced Thermodynamics and Statistical Mechanics #Applied mathematics #Benchmark (surveying) #Computer science #Entropy (arrow of time) #Entropy production #Experimental data #Field (mathematics) #Mathematical optimization #Mathematics #Phase Equilibria and Thermodynamics #Physics #Statistical physics #Statistics #Thermodynamics #Trajectory #cond-mat.mes-hall #cond-mat.soft #thermodynamics and calorimetric analyses
paper · pdf · doi:10.1038/s42005-021-00766-2
published as Communications Physics volume 4, Article number: 258 (2021) · 19 pages, 14 figures, Revised version including comparison with SFI technique introduced in [Phys. Rev. X 10, 021009]
arxiv created 2021/10/01 · openalex publication_date 2021/12/02 · arxiv updated 2021/12/03 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
Abstract Estimating entropy production directly from experimental trajectories is of great current interest but often requires a large amount of data or knowledge of the underlying dynamics. In this paper, we propose a minimal strategy using the short-time Thermodynamic Uncertainty Relation (TUR) by means of which we can simultaneously and quantitatively infer the thermodynamic force field acting on the system and the (potentially exact) rate of entropy production from experimental short-time trajectory data. We benchmark this scheme first for an experimental study of a colloidal particle system where exact analytical results are known, prior to studying the case of a colloidal particle in a hydrodynamical flow field, where neither analytical nor numerical results are available. In the latter case, we build an effective model of the system based on our results. In both cases, we also demonstrate that our results match with those obtained from another recently introduced scheme.