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Juan M. R. Parrondo

Researcher at Complutense University of Madrid

Publications -  151
Citations -  7427

Juan M. R. Parrondo is an academic researcher from Complutense University of Madrid. The author has contributed to research in topics: Entropy production & Ratchet. The author has an hindex of 41, co-authored 148 publications receiving 6411 citations. Previous affiliations of Juan M. R. Parrondo include Max Planck Society & University of California, San Diego.

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Thermodynamics of information

TL;DR: In this article, the authors present a theoretical framework for the thermodynamics of information based on stochastic thermodynamics and fluctuation theorems, review some recent experimental results, and present an overview of the state of the art in the field.
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Dissipation: The Phase-Space Perspective

TL;DR: It is shown that the average dissipation, upon perturbing a Hamiltonian system arbitrarily far out of equilibrium in a transition between two canonical equilibrium states, is exactly given by =W-DeltaF=kTD(rho||rho[ over ])=kT, where rho and rho[over ] are the phase-space density of the system measured at the same intermediate but otherwise arbitrary point in time, for the forward and backward process.
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Brownian Carnot engine

TL;DR: This work reports an experimental realization of a Carnot engine with a single optically trapped Brownian particle as the working substance and analyses the fluctuations of the finite-time efficiency, showing that the Carnot bound can be surpassed for a small number of non-equilibrium cycles.
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Noise-induced nonequilibrium phase transition.

TL;DR: In this article, a simple model of a spatially distributed system subject to multiplicative noise, white in space and time, can undergo a nonequilibrium phase transition to a symmetry-breaking state, while no such transition exists in the absence of the noise term.
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New paradoxical games based on brownian ratchets

TL;DR: New games where all the rules depend only on the history of the game and not on the capital are presented, which significantly increases the parameter space for which the effect operates.