Measurement and feedback allows for 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 the information that is acquired via the measurement, a result that manifests the close relation between information theory and stochastic thermodynamics. In this paper, we show how to reversibly confine a Brownian particle in an optical tweezer potential and then extract the corresponding increase of the free energy as work. By repeatedly tracking the position of the particle and modifying the potential accordingly, we can extract work optimally, even with a high degree of inaccuracy in the measureme...
In the standard framework of thermodynamics work is a random variable whose average is bounded by th...
A suitable way of quantifying work for microscopic quantum systems has been constantly debated in th...
We use Monte Carlo and genetic algorithms to train neural-network feedback-control protocols for sim...
A Brownian information engine can induce directed motion of a Brownian particle in a single heat bat...
We investigate a Geometric Brownian Information Engine (GBIE) in the presence of an error-free feedb...
We present an experimental realization of an information-driven Brownian motor by periodically cooli...
In the last thirty years, experimental and theoretical advancements allowed the investigation of the...
Brownian information engines can extract work from thermal fluctuations by utilizing information. So...
We determine the maximum amount of work extractable in finite time by a demon performing continuous ...
Brownian information engines can extract work from thermal fluctuations by utilizing information. To...
Our goal in this article is to elucidate the rapport of work and information in the context of a min...
Recent advances in nanotechnology and the accompanying development oftechniques that operate and man...
Abstract Although the equivalence of heat and work has been unveiled since Joule’s ingenious experim...
We report on a lossless information engine that converts nearly all available information from an er...
In the derivation of fluctuation relations, and in stochastic thermodynamics in general, it is tacit...
In the standard framework of thermodynamics work is a random variable whose average is bounded by th...
A suitable way of quantifying work for microscopic quantum systems has been constantly debated in th...
We use Monte Carlo and genetic algorithms to train neural-network feedback-control protocols for sim...
A Brownian information engine can induce directed motion of a Brownian particle in a single heat bat...
We investigate a Geometric Brownian Information Engine (GBIE) in the presence of an error-free feedb...
We present an experimental realization of an information-driven Brownian motor by periodically cooli...
In the last thirty years, experimental and theoretical advancements allowed the investigation of the...
Brownian information engines can extract work from thermal fluctuations by utilizing information. So...
We determine the maximum amount of work extractable in finite time by a demon performing continuous ...
Brownian information engines can extract work from thermal fluctuations by utilizing information. To...
Our goal in this article is to elucidate the rapport of work and information in the context of a min...
Recent advances in nanotechnology and the accompanying development oftechniques that operate and man...
Abstract Although the equivalence of heat and work has been unveiled since Joule’s ingenious experim...
We report on a lossless information engine that converts nearly all available information from an er...
In the derivation of fluctuation relations, and in stochastic thermodynamics in general, it is tacit...
In the standard framework of thermodynamics work is a random variable whose average is bounded by th...
A suitable way of quantifying work for microscopic quantum systems has been constantly debated in th...
We use Monte Carlo and genetic algorithms to train neural-network feedback-control protocols for sim...