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Contents - Max-Planck-Institut für Physik komplexer Systeme

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p(W)<br />

0.1<br />

0.08<br />

0.06<br />

0.04<br />

0.02<br />

0<br />

0.01<br />

0.005<br />

0.001<br />

9900 ∆F<br />

W<br />

10000<br />

Figure 1: Distributions of the work performed during the direct<br />

process (solid lines) and extracted during the time-reversed process<br />

(dashed lines) for various values of the switching rate δλ.<br />

The parameter δλ, the switching rate, controls how<br />

far from equilibrium the system is driven. With fast<br />

switching (red curve on fig. 1), the system is driven further<br />

away from equilibrium than with slow switching<br />

(blue curve). The mean dissipated work is greater, as<br />

are the fluctuations of the work. The maximum work<br />

theorem implies that in the quasi-static limit δλ → 0,<br />

the distributions of the work for the direct and the timereversed<br />

processes both tend towards a Dirac distribution<br />

centered on ∆F .<br />

〈δW(t)〉/δλ<br />

10000<br />

9960<br />

9920<br />

9880<br />

10 −2<br />

5 · 10 −3<br />

10 −3<br />

9840<br />

0 0.2 0.4 0.6 0.8 1<br />

λ(t)<br />

Figure 2: Evolution of the mean work performed (solid lines) and<br />

extracted (dashed lines) 〈 δW<br />

〉 per time step along the direct and re-<br />

δλ<br />

verse processes for different switching rates δλ.<br />

The evolution of the quantity δW<br />

δλ during switching<br />

helps to understand how the distributions in fig. 1<br />

arise. Fig. 2 shows the evolution of its mean value 〈 δW<br />

δλ 〉<br />

along the process for different values of the switching<br />

rate δλ. Examples of the fluctuations of δW<br />

δλ around its<br />

mean value are shown on fig. 3. The mean value of δW<br />

δλ<br />

during the direct and the reverse process are very close<br />

to one another for a slow process and further apart for<br />

a fast one, implying an increase in the mean dissipated<br />

work as the switching rate increases. The amplitude of<br />

the fluctuations of δW<br />

δλ are not influenced by the switching<br />

rate. However, for slow switching (red curve on<br />

fig. 3), the system has more time to fluctuate and the<br />

fluctuations are partly averaged out when performing<br />

the integration (4).<br />

δW(t)−〈δW(t)〉<br />

δλ<br />

80<br />

40<br />

0<br />

-40<br />

-80<br />

10 −4<br />

10 −3<br />

0 0.2 0.4 0.6 0.8 1<br />

λ(t)<br />

Figure 3: Fluctuations of δW<br />

δλ<br />

along the process for two values of δλ.<br />

For Gaussian distributions of the dissipated work Wd<br />

one can easily verify that Crooks’ relation (1) implies<br />

that the mean value W d and variance σ 2 of the dissipated<br />

work for the direct and the time-reversed processes<br />

coincide. Crooks’ relation then reduces to a generalized<br />

fluctuation-dissipation relation [4]:<br />

σ 2 = 2kBT W d<br />

Fig. 4 shows the distribution of the quantity Wd =<br />

Wd/σ − σ/2kBT for the direct and the time-reversed<br />

process for various values of the switching rate. This<br />

quantity has a Gaussian distribution with zero mean<br />

and unit variance for all values of the switching rate,<br />

implying that the dissipated work Wd has a Gaussian<br />

distribution and satisfies (6) and therefore Crooks’ relation<br />

(1) as well.<br />

p( p( Wd ) p( Wd ) p( Wd ) p( Wd ) p( Wd ) p( Wd ) p( Wd ) p( Wd ) p( Wd ) p( Wd ) p( Wd ) p( Wd ) p( Wd ) p( Wd ) Wd )<br />

100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 10−1 10−1 10−1 10−1 10−1 10−1 10−1 10−1 10−1 10−1 10−1 10−1 10−1 10−1 10−1 10−2 10−2 10−2 10−2 10−2 10−2 10−2 10−2 10−2 10−2 10−2 10−2 10−2 10−2 10−2 10−3 10−3 10−3 10−3 10−3 10−3 10−3 10−3 10−3 10−3 10−3 10−3 10−3 10−3 10−3 10−4 10−4 10−4 10−4 10−4 10−4 10−4 10−4 10−4 10−4 10−4 10−4 10−4 10−4 10−4 10−5 10−5 10−5 10−5 10−5 10−5 10−5 10−5 10−5 10−5 10−5 10−5 10−5 10−5 10−5 10−6 10−6 10−6 10−6 10−6 10−6 10−6 10−6 10−6 10−6 10−6 10−6 10−6 10−6 10−6 -6 -4 -2 0 W W W W W W W W W W W W W W W d<br />

2 4 6<br />

Figure 4: Distribution of the quantity f Wd = Wd/σ −σ/2kBT for the<br />

direct and reverse process for various values of δλ.<br />

A more careful analysis of the fluctuations suggests<br />

that these are equilibrium heat bath fluctuations in<br />

which only the mean value depends of the protocol and<br />

hence reflects the distance from equilibrium. It is evident<br />

that this cannot hold for arbitrary situations, in<br />

particular not in cases where the driving force creates<br />

dynamical instabilities. The details are still awaiting<br />

further investigation. This issue is relevant for macroscopic<br />

fluctuations in non-equilibrium systems that are<br />

close to the thermodynamic limit, for which pure heat<br />

bath fluctuations should become invisible.<br />

[1] H. B. Callen, THERMODYNAMICS AND AN INTRODUCTION TO<br />

THERMOSTATISTICS, John Wiley & sons (1985).<br />

[2] G. E. Crooks, J. of Stat. Phys. 90 (1998) 1481.<br />

[3] R. Adhikari et al, Europys. Lett. 71 (2005) 473; B. Dünweg,<br />

U. D. Schiller and A. J. C. Ladd, Phys. Rev. E 76 (2007) 036704.<br />

[4] L. Granger, M. Niemann and H. Kantz, J. Stat. Mech.: Th. and<br />

Exp. (2010) P06029<br />

2.14. Work Dissipation Along a Non Quasi-Static Process 69<br />

(6)

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