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Andre C. Barato

Researcher at Max Planck Society

Publications -  64
Citations -  3450

Andre C. Barato is an academic researcher from Max Planck Society. The author has contributed to research in topics: Entropy production & Fluctuation theorem. The author has an hindex of 27, co-authored 64 publications receiving 2742 citations. Previous affiliations of Andre C. Barato include International Centre for Theoretical Physics & University of Houston.

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Rate of mutual information between coarse-grained non-Markovian variables

TL;DR: A numerical method to estimate the Shannon entropy rate of continuous time hidden-Markov processes from a single time series is developed and an analytical upper bound on the rate of mutual information is calculated for a class of Markov processes for which the transition rates have a bipartite character.
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Bounds on current fluctuations in periodically driven systems

TL;DR: In this article, the authors obtained a universal bound on current fluctuations for periodically driven systems, such as heat engines driven by periodic variation of the temperature and artificial molecular pumps driven by an external protocol.
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Current fluctuations in periodically driven systems

TL;DR: In this paper, the scaling cumulant generating function that characterizes current fluctuations is given by a maximal Floquet exponent, and it is shown that, with respect to large deviations, systems driven by a stochastic protocol with an infinitely large number of jumps are equivalent to deterministic protocols.
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Current fluctuations in periodically driven systems

TL;DR: In this article, the scaling cumulant generating function that characterizes current fluctuations is given by a maximal Floquet exponent, and it is shown that, with respect to large deviations, systems driven by a stochastic protocol with an infinitely large number of jumps are equivalent to deterministic protocols.
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Skewness and Kurtosis in Statistical Kinetics

TL;DR: Lower and upper bounds on the skewness and kurtosis associated with the cycle completion time of unicyclic enzymatic reaction schemes are obtained and it is demonstrated that evaluating these higher order moments with single molecule data can lead to information about the enzyme scheme that is not contained in the randomness parameter.