Regensburg 2025 – wissenschaftliches Programm
Bereiche | Tage | Auswahl | Suche | Aktualisierungen | Downloads | Hilfe
DY: Fachverband Dynamik und Statistische Physik
DY 42: Stochastic Thermodynamics
DY 42.3: Vortrag
Freitag, 21. März 2025, 10:00–10:15, H43
Active Brownian information engine: Self-propulsion induced colossal performance — •Rafna Rafeek and Debasish Mondal — Department of Chemistry and Center for Molecular and Optical Sciences and Technologies, Indian Institute of Technology Tirupati, Yerpedu 517619, Andhra Pradesh, India
Many biological systems operating in athermal (active) environments, can be modeled as an information engine, with the key aspect of utilizing information on the fluctuation to extort work from the noisy environment. In this study, we propose a feedback-driven information engine operating in a Gaussian-correlated active reservoir with characteristic strength (Da) and correlation time (τa), which outperforms its thermal counterpart. We obtain the optimal functioning criteria for the enhanced performance of the active Brownian information engine (ABIE), reliant on the dispersion of the steady state, which is analogous to its passive analog. We notice that a weakly correlated active bath extracts colossal work due to the reduced relative loss of information in the relaxation process. In the limit of fractionally smaller correlation time ( ta / tr → 0,ta is thermal relaxation time), the upper bound on colossal work extraction is 0.202(D+ Da). The excess amount of extracted work reduces and converges to its passive counterpart in the higher limit of correlation time (ta / tr → high ). Interestingly, when correlation time is equivalent to relaxation time (ta / tr = 1 ), half the upper bound of excess work is achieved irrespective of activity strength. This study provides a new insight into understanding and designing the information-energy exchange of biological submicrometer motors.
Keywords: Brownian information engine; Non-equillibrium system; Active particle