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Taming a Maxwell's demon for experimental stochastic resetting
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A diffusive process that is reset to its origin at random times, so-called stochastic resetting (SR), is an ubiquitous expedient in many natural systems . Yet, beyond its ability to improve the efficiency of target searching, SR is a true non-equilibrium thermodynamic process that brings forward new and challenging questions . Here, we show how the recent developments of experimental information thermodynamics renew the way to address SR and can lead, beyond a new understanding, to better control on the non-equilibrium nature of SR. This thermodynamically controlled SR is experimentally implemented within a time-dependent optical trapping potential. We show in particular that SR converts heat into work from a single bath continuously and without feedback. This implements a Maxwell's demon that constantly erases information. In our experiments, the erasure takes the form of a protocol that allows to evaluate the true energetic cost of SR. We show that using an appropriate measure of the available information, this cost can be reduced to a reversible minimum while being bounded by the Landauer limit. We finally reveal that the individual trajectories generated by the demon all break ergodicity and thus demonstrate the non-ergodic nature of the demon's modus operandi. Our results offer new approaches to processes, such as SR, where the informational framework provides key experimental tools for their non-equilibrium thermodynamic control.
Forward citations
Cited by 3 Pith papers
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Semi-Markovian switching in a fluctuating harmonic trap: An age-structured formulation
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Thermodynamic Cost of Recurrent Erasure
For recurrent resetting via finite-time harmonic trap stiffness changes, the authors derive the mean and variance of the work and an optimal finite-time protocol whose quasistatic cost falls below the equilibrium free...
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Experimental Realizations of Information Engines: Beyond Proof of Concept
The paper reviews experimental information engines and argues they have advanced beyond proof of concept into active, many-body, inertial, and optimally controlled regimes.
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