Time-dependent study of bit reset

Chiuchiù, Davide

doi:10.1209/0295-5075/109/30002

Cited by 10 publications

(12 citation statements)

References 14 publications

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“…In the results reported in this paper, we simultaneously measure both the work required and the heat transferred to the bath in protocols that erase a one-bit memory. Simultaneous work and heat estimates have been compared and analysed in theoretical studies [52,53], but not in experiments [18,51,[54][55][56][57][58]. Here, we compare distributions of these stochastic quantities for an erasure experiment and consider the relative merits and limitations of each type of measurement.…”

Section: Experimental Test Of the Landauer Principlementioning

confidence: 99%

“…In one dimension, the potential is parametrized to control the height of the barrier E b and tilt A independently [16,22,52,53]:…”

Section: (A) Virtual Double-well Potentialmentioning

confidence: 99%

“…We have adapted the feedback trap described above to study memory erasure in a double-well potential. In one dimension, the potential is parametrized to control the height of the barrier E b and tilt A independently [16,22,52,53]:…”

Section: (A) Virtual Double-well Potentialmentioning

confidence: 99%

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Feedback traps for virtual potentials

Gavrilov

Bechhoefer

2017

Phil. Trans. R. Soc. A.

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Feedback traps are tools for trapping and manipulating single charged objects, such as molecules in solution. An alternative to optical tweezers and other single-molecule techniques, they use feedback to counteract the Brownian motion of a molecule of interest. The trap first acquires information about a molecule's position and then applies an electric feedback force to move the molecule. Since electric forces are stronger than optical forces at small scales, feedback traps are the best way to trap single molecules without ‘touching’ them (e.g. by putting them in a small box or attaching them to a tether). Feedback traps can do more than trap molecules: they can also subject a target object to forces that are calculated to be the gradient of a desired potential functionU(x). If the feedback loop is fast enough, it creates avirtual potentialwhose dynamics will be very close to those of a particle in an actual potentialU(x). But because the dynamics are entirely a result of the feedback loop—absent the feedback, there is only an object diffusing in a fluid—we are free to specify and then manipulate in time an arbitrary potentialU(x,t). Here, we review recent applications of feedback traps to studies on the fundamental connections between information and thermodynamics, a topic where feedback plays an even more fundamental role. We discuss how recursive maximum-likelihood techniques allow continuous calibration, to compensate for drifts in experiments that last for days. We consider ways to estimate work and heat, using them to measure fluctuating energies to a precision of ±0.03kTover these long experiments. Finally, we compare work and heat measurements of the costs of information erasure, theLandauer limitofkTln 2 per bit of information erased. We argue that, when you want to know the average heat transferred to a bath in a long protocol, you should measure instead the average work and then infer the heat using the first law of thermodynamics.This article is part of the themed issue ‘Horizons of cybernetical physics’.

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Section: Experimental Test Of the Landauer Principlementioning

confidence: 99%

“…In one dimension, the potential is parametrized to control the height of the barrier E b and tilt A independently [16,22,52,53]:…”

Section: (A) Virtual Double-well Potentialmentioning

confidence: 99%

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Feedback traps for virtual potentials

Gavrilov

Bechhoefer

2017

Phil. Trans. R. Soc. A.

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“…Stochastic thermodynamics is a branch of nonequilibrium statistical physics that deals with the thermodynamic properties of small physical systems in fluctuating environments [1]. Its main applications are in nanotechnology and in biophysics, where it's respectively used to study the physical limits of a computing device [2][3][4][5][6][7][8], and to study chemical reaction networks and proteins functionality [9][10][11][12]. One of the most important quantity in stochastic thermodynamics is the heat exchanged by the systems with a thermal reservoir.…”

Section: Introductionmentioning

confidence: 99%

How to measure heat in stochastic systems

Chiuchiù

2017

Preprint

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Heat is a complex quantity to measure in stochastic systems because it requires extremely small sampling timesteps. Unfortunately this is not always possible in real experiments, mainly because experimental setups have technical limits. To overcome this difficulty a Simpson-like quadrature scheme was suggested in [Phil. Trans. R. Soc. A 2017 375 ] as a tool to compute the heat in stochastic systems. In this paper we study this new quadrature scheme. In particular, we first give a qualitative proof of the Simpson-like quadrature with the help of Riemann-Stieltjes integrals and we then perform supplementary numerical simulations to confirm our observations. Our main finding is that the Simpson-like quadrature yields errors that are much smaller than the ones obtained with the Stratonovich quadrature. This opens the possibility to design extremely sensitive experiments on stochastic systems without state-of-the-art sampling techniques.

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“…If we assume that t R ≪ τ k , the system dynamics is practically confined within one well. Here it can be approximately described by the dynamics of an harmonic oscillator, characterised by a Gaussian probability density function [18].…”

mentioning

confidence: 99%

Cost of remembering a bit of information

et al. 2018

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In 1961, Rolf Landauer pointed out that resetting a binary memory requires a minimum energy of k B T ln(2). However, once written, any memory is doomed to loose its content if no action is taken. To avoid memory losses, a refresh procedure is periodically performed. In this paper we present a theoretical model and an experiment on a micro-electro-mechanical system to evaluate the minimum energy required to preserve one bit of information over time. Two main conclusions are drawn: i) in principle the energetic cost to preserve information for a fixed time duration with a given error probability can be arbitrarily reduced if the refresh procedure is performed often enough; ii) the Heisenberg uncertainty principle sets an upper bound on the memory lifetime.

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Time-dependent study of bit reset

Cited by 10 publications

References 14 publications

Feedback traps for virtual potentials

Feedback traps for virtual potentials

How to measure heat in stochastic systems

Cost of remembering a bit of information

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