Evaluation of free energy landscapes from manipulation experiments

A fluctuation relation, which is an extended form of the Jarzynski equality, is introduced and discussed. We show how to apply this relation in order to evaluate the free energy landscape of simple systems. These systems are manipulated by varying the external field coupled with a systems' internal characteristic variable. Two different manipulation protocols are here considered: in the first case the external field is a linear function of time, in the second case it is a periodic function of time. While for simple mean field systems both the linear protocol and the oscillatory protocol provide a reliable estimate of the free energy landscape, for a simple model ofhomopolymer the oscillatory protocol turns out to be not reliable for this purpose. We then discuss the possibility of application of the method here presented to evaluate the free energy landscape of real systems, and the practical limitations that one can face in the realization of an experimental set-up

Work probability distribution in systems driven out of equilibrium

We derive the differential equation describing the time evolution of the work probability distribution function of a stochastic system which is driven out of equilibrium by the manipulation of a parameter. We consider both systems described by their microscopic state or by a collective variable which identifies a quasiequilibrium state. We show that the work probability distribution can be represented by a path integral, which is dominated by ``classical'' paths in the large system size limit. We compare these results with simulated manipulation of mean-field systems. We discuss the range of applicability of the Jarzynski equality for evaluating the system free energy using these out-of-equilibrium manipulations. Large fluctuations in the work and the shape of the work distribution tails are also discussed

The distribution function of entropy flow in stochastic systems

We obtain a simple direct derivation of the differential equation governing the entropy flow probability distribution function of a stochastic system first obtained by Lebowitz and Spohn. Its solution agrees well with the experimental results of Tietz et al [2006 {\it Phys. Rev. Lett.} {\bf 97} 050602]. A trajectory-sampling algorithm allowing to evaluate the entropy flow distribution function is introduced and discussed. This algorithm turns out to be effective at finite times and in the case of time-dependent transition rates, and is successfully applied to an asymmetric simple exclusion process

Efficiency of molecular machines with continuous phase space

We consider a molecular machine described as a Brownian particle diffusing in a tilted periodic potential. We evaluate the absorbed and released power of the machine as a function of the applied molecular and chemical forces, by using the fact that the times for completing a cycle in the forward and the backward direction have the same distribution, and that the ratio of the corresponding splitting probabilities can be simply expressed as a function of the applied force. We explicitly evaluate the efficiency at maximum power for a simple sawtooth potential. We also obtain the efficiency at maximum power for a broad class of 2-D models of a Brownian machine and find that loosely coupled machines operate with a smaller efficiency at maximum power than their strongly coupled counterparts.Comment: To appear in EP

Fluctuation relations for a driven Brownian particle

We consider a driven Brownian particle, subject to both conservative and non-conservative applied forces, whose probability evolves according to the Kramers equation. We derive a general fluctuation relation, expressing the ratio of the probability of a given Brownian path in phase space with that of the time-reversed path, in terms of the entropy flux to the heat reservoir. This fluctuation relation implies those of Seifert, Jarzynski and Gallavotti-Cohen in different special cases

Heat flow in chains driven by thermal noise

We consider the large deviation function for a classical harmonic chain composed of N particles driven at the end points by heat reservoirs, first derived in the quantum regime by Saito and Dhar and in the classical regime by Saito and Dhar and Kundu et al. Within a Langevin description we perform this calculation on the basis of a standard path integral calculation in Fourier space. The cumulant generating function yielding the large deviation function is given in terms of a transmission Green's function and is consistent with the fluctuation theorem. We find a simple expression for the tails of the heat distribution which turn out to decay exponentially. We, moreover, consider an extension of a single particle model suggested by Derrida and Brunet and discuss the two-particle case. We also discuss the limit for large N and present a closed expression for the cumulant generating function. Finally, we present a derivation of the fluctuation theorem on the basis of a Fokker-Planck description. This result is not restricted to the harmonic case but is valid for a general interaction potential between the particles.Comment: Latex: 26 pages and 9 figures, appeared in J. Stat. Mech. P04005 (2012

Work distribution in manipulated single biomolecules

We consider the relation between the microscopic and effective descriptions of the unfolding experiment on a model polypeptide. We evaluate the probability distribution function of the performed work by Monte Carlo simulations and compare it with that obtained by evaluating the work distribution generating function on an effective Brownian motion model tailored to reproduce exactly the equilibrium properties. The agreement is satisfactory for fast protocols, but deteriorates for slower ones, hinting at the existence of processes on several time scales even in such a simple system.Comment: To appear in Physical Biology, Special issue: Polymer physics of the cel

Work distribution and path integrals in general mean-field systems

We consider a mean-field system described by a general collective variable $M$, driven out of equilibrium by the manipulation of a parameter $\mu$. Given a general dynamics compatible with its equilibrium distribution, we derive the evolution equation for the joint probability distribution function of $M$ and the work $W$ done on the system. We solve this equation by path integrals. We show how the Jarzynski equality holds identically at the path integral level and for the classical paths which dominate the expression in the thermodynamic limit. We discuss some implications of our results.Comment: 4 pages, 2 figures; accepted for publication in Europhys. Let

Work and heat probability distribution of an optically driven Brownian particle: Theory and experiments

We analyze the equations governing the evolution of distributions of the work and the heat exchanged with the environment by a manipulated stochastic system, by means of a compact and general derivation. We obtain explicit solutions for these equations for the case of a dragged Brownian particle in a harmonic potential. We successfully compare the resulting predictions with the outcomes of experiments, consisting in dragging a micron-sized colloidal particle through water with a laser trap