SKM 2023 – wissenschaftliches Programm

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DY: Fachverband Dynamik und Statistische Physik

DY 44: Poster: Statistical Physics

DY 44.16: Poster

Donnerstag, 30. März 2023, 13:00–16:00, P1

Theoretical design of Geometric Brownian Information Engine: Analysis of output work — •Syed Yunus Ali, Rafna Rafeek, and Debasish Mondal — IIT Tirupati, Yerpedu, Andhrapradesh, India

We design a geometric Brownian information engine by considering overdamped Brownian particles inside a 2-D monolobal confinement with irregular width along the transport direction. Under such conditions, particles experience an effective entropic potential. We employ a feedback control protocol as an outcome of error-free position measurement.The protocol comprises three stages: measurement, feedback, and relaxation. We show that the upper bound of the achievable work shows a cross-over from (5/3 − 2ln2)kB T to kBT/2 when the system changes from an entropy-dominated regime to energy dominated one. Next, we determine the benchmarks for utilizing the available information in an output work and the optimum operating requisites for best work extraction in asymmetric feedback protocol. Transverse bias force (G) tunes the entropic contribution in the effective potential and hence the equilibrium marginal probability distribution standard deviation(σ).We recognize that the amount of extracted work reaches a global maximum when xf = 2xm with xm=0.6σ, irrespective of the extent of the entropic limitation.


1. S. Y. Ali, R. Rafeek, and D. Mondal, J. Chem. Phys. 156, 014902 (2022).

2. R. Rafeek, S. Y. Ali, and D. Mondal (2022) (Under review).

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