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We consider a Geometric Brownian Information Engine to explore the effects of finite cycle time $(\tau)$ on the extractable work, power, and efficiency. We incorporate an error-free feedback controller that converts the information obtained…

Statistical Mechanics · Physics 2025-06-23 Syed Yunus Ali , Rafna Rafeek , Debasish Mondal

Brownian Information engine (BIE) harnesses the energy from a fluctuating environment by utilizing the associated information change in the presence of a single heat bath. The engine operates in a space-dependent confining potential and…

Soft Condensed Matter · Physics 2025-04-15 Rafna Rafeek , Debasish Mondal

The information engine extracts work from a single heat bath using mutual information obtained during the operation cycle. This study investigates the influence of the potential shaping in a Brownian information engine (BIE) in harnessing…

Soft Condensed Matter · Physics 2025-04-15 Rafna Rafeek , Debasish Mondal

An information engine harnesses energy from a single heat bath, utilising the gathered information. This study explores the best control strategy of a Brownian information engine (BIE), confined in a potential energy surface (PES) of…

Soft Condensed Matter · Physics 2025-05-26 Rafna Rafeek , Debasish Mondal

A Brownian information engine is a device extracting a mechanical work from a single heat bath by exploiting the information on the state of a Brownian particle immersed in the bath. As for engines, it is important to find the optimal…

Statistical Mechanics · Physics 2016-04-06 J. -M. Park , J. S. Lee , J. D. Noh

We describe an experiment on an underdamped mechanical oscillator used as an information engine. The system is equivalent to an inertial Brownian particle confined in a harmonic potential whose center is controlled by a feedback protocol…

Statistical Mechanics · Physics 2025-01-23 Aubin Archambault , Caroline Crauste-Thibierge , Sergio Ciliberto , Ludovic Bellon

A Brownian information machine extracts work from a heat bath through a feedback process that exploits the information acquired in a measurement. For the paradigmatic case of a particle trapped in a harmonic potential, we determine how…

Statistical Mechanics · Physics 2012-04-09 Michael Bauer , David Abreu , Udo Seifert

We report on a lossless information engine that converts nearly all available information from an error-free feedback protocol into mechanical work. Combining high-precision detection at resolution of 1 nm with ultrafast feedback control,…

Statistical Mechanics · Physics 2018-02-07 Govind Paneru , Dong Yun Lee , Tsvi Tlusty , Hyuk Kyu Pak

We have experimentally realized an information engine consisting of an optically trapped, heavy bead in water. The device raises the trap center after a favorable "up" thermal fluctuation, thereby increasing the bead's average gravitational…

Statistical Mechanics · Physics 2023-04-11 Tushar K. Saha , Joseph N. E. Lucero , Jannik Ehrich , David A. Sivak , John Bechhoefer

A Brownian particle moving in a staircase-like potential with feedback control offers a way to implement Maxwell's demon. An experimental demonstration of such a system using sinusoidal periodic potential carried out by Toyabe et al. has…

Statistical Mechanics · Physics 2023-12-29 Kiran V , Toby Joseph

We study the optimal performance of an information engine consisting of an overdamped Brownian bead confined in a controllable, $d$-dimensional harmonic trap and additionally subjected to gravity. The trap's center is updated dynamically…

Statistical Mechanics · Physics 2026-02-18 Antonio Patrón Castro , John Bechhoefer , David A. Sivak

A finite cycle time information engine based on a two-level system in contact with a thermal reservoir is studied analytically. The model for the engine incorporates an error in measuring the system's state and time delay between the…

Statistical Mechanics · Physics 2024-05-13 Kiran V , Toby Joseph

Bayesian optimal experimental design is a principled framework for conducting experiments that leverages Bayesian inference to quantify how much information one can expect to gain from selecting a certain design. However, accurate Bayesian…

Machine Learning · Statistics 2025-11-12 Yasir Zubayr Barlas , Sabina J. Sloman , Samuel Kaski

Brownian information engines can extract work from thermal fluctuations by utilizing information. So far, the studies on Brownian information engines consider the system in a thermal bath; however, many processes in nature occur in a…

Statistical Mechanics · Physics 2022-07-26 Govind Paneru , Sandipan Dutta , Hyuk Kyu Pak

Computing expected information gain (EIG) from prior to posterior (equivalently, mutual information between candidate observations and model parameters or other quantities of interest) is a fundamental challenge in Bayesian optimal…

Methodology · Statistics 2026-01-30 Fengyi Li , Ricardo Baptista , Youssef Marzouk

We review recent studies of a colloidal information engine that consists of a bead in water and held by an optical trap. The bead is ratcheted upward without any apparent external work, by taking advantage of favorable thermal fluctuations.…

Statistical Mechanics · Physics 2024-12-30 Johan du Buisson , David A. Sivak , John Bechhoefer

Experimental design is crucial for inference where limitations in the data collection procedure are present due to cost or other restrictions. Optimal experimental designs determine parameters that in some appropriate sense make the data…

Machine Learning · Statistics 2016-03-11 Panagiotis Tsilifis , Roger G. Ghanem , Paris Hajali

Work can be extracted from a single heat bath if additional information is available. For the paradigmatic case of a Brownian particle in a harmonic potential, whose position has been measured with finite precision, we determine the optimal…

Statistical Mechanics · Physics 2011-03-24 D. Abreu , U. Seifert

Measurement and feedback allows an external agent to extract work from a system in contact with a single thermal bath. The maximum amount of work that can be extracted in a single measurement and the corresponding feedback loop is given by…

Statistical Mechanics · Physics 2024-01-19 L. Dinis , J. M. R. Parrondo

The geometric Brownian motion (GBM) is widely employed for modeling stochastic processes, yet its solutions are characterized by the log-normal distribution. This comprises predictive capabilities of GBM mainly in terms of forecasting…

Data Analysis, Statistics and Probability · Physics 2024-03-19 Rishabh Gupta , Ewa A. Drzazga-Szczȩśniak , Sabre Kais , Dominik Szczȩśniak
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