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A numerical approach to large deviations in continuous time

Vivien Lecomte1,2 and Julien Tailleur3

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We present an algorithm to evaluate large deviation functions associated to history-dependent observables. Instead of relying on a time discretization procedure to approximate the dynamics, we provide a direct continuous-time algorithm valuable for systems with multiple timescales, thus extending the work of Giardinà, Kurchan and Peliti (2006 Phys. Rev. Lett. 96 120603).

The procedure is supplemented with a thermodynamic-integration scheme which improves its efficiency. We also show how the method can be used to probe large deviation functions in systems with a dynamical phase transition—revealed in our context through the appearance of a non-analyticity in the large deviation functions.


Keywords

stochastic processes (theory)

current fluctuations

fluctuations (theory)

other numerical approaches

PACS

05.70.Fh Phase transitions: general studies

02.50.Ga Markov processes

MSC

60J27 Markov chains with continuous parameter

82C26 Dynamic and nonequilibrium phase transitions (general)

Subjects

Computational physics

Statistical physics and nonlinear systems

Dates

Issue 03 (March 2007)

Received 9 January 2007, accepted for publication 5 February 2007

Published 2 March 2007



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