Regensburg 2022 – wissenschaftliches Programm

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DY: Fachverband Dynamik und Statistische Physik

DY 44: Poster Session: Statistical Physics and Critical Phenomena

DY 44.4: Poster

Donnerstag, 8. September 2022, 15:00–18:00, P2

Geometric Brownian Information Engine : Essentials of optimal work and performance. — •Rafna Rafeek, Syed Yunus Ali, and Debasish Mondal — Department of Chemistry and Center for Molecular and Optical Sciences & Technologies, Indian Institute of Technology Tirupati, Yerpedu 517619, Andhra Pradesh, India

We investigate a Geometric Brownian Information Engine (GBIE) in the presence of an error-free feedback controller that transforms the information gathered on the state of particles entrapped in mono-lobal geometric detention into extractable work. We determine the benchmarks for utilizing the available information in an output work and the optimum operating requisites for best performance. Apart from a reference measurement distance xm and feedback site xf , upshots of the information engine also depend on the transverse constant bias force(G). G tunes the entropic contribution in the effective potential and the standard deviation (σ) of the equilibrium marginal probability distribution.

We find that the upper bound of the achievable work shows a crossover from (5/3-2ln2)kBT to 1/2kBT when the system changes from entropy to an energy-dominated one.The higher loss of information during the relaxation process, accredits the lower value of work in entropic instances of GBIE. We recognize that the work extraction reaches a global maximum when xf=2xm with xm=0.6σ, irrespective of the extent of the entropic limitation. Also we explore the effect of entropic control on the unidirectional passage of the particle and efficacy of the GBIE.