2015
DOI: 10.1007/s10955-015-1283-0
|View full text |Cite
|
Sign up to set email alerts
|

A Formal View on Level 2.5 Large Deviations and Fluctuation Relations

Abstract: We obtain the rate function for the level 2.5 of large deviations for pure jump and diffusion processes. This result is proved by two methods: tilting, for which a tilted process with an appropriate typical behavior is considered, and a spectral method, for which the scaled cumulant generating function is used. We also briefly discuss fluctuation relations, pointing out their connection with large deviations at the level 2.5.

Help me understand this report
View preprint versions

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1

Citation Types

12
225
0

Year Published

2016
2016
2021
2021

Publication Types

Select...
8

Relationship

1
7

Authors

Journals

citations
Cited by 106 publications
(237 citation statements)
references
References 46 publications
12
225
0
Order By: Relevance
“…24. [30] Derive the expression of the tilted generator L k for SDEs in which the noise is multiplicative, that is, in which the noise matrix σ depends on x. In this case, you must specify the stochastic convention used for interpreting the product σ(x)dW t .…”
Section: Exercisesmentioning
confidence: 99%
“…24. [30] Derive the expression of the tilted generator L k for SDEs in which the noise is multiplicative, that is, in which the noise matrix σ depends on x. In this case, you must specify the stochastic convention used for interpreting the product σ(x)dW t .…”
Section: Exercisesmentioning
confidence: 99%
“…Eq. (19) follows from an exact expression for the "level 2.5" large deviation function I(J , p) for the joint distribution of the fluctuating current J and the fluctuating density p = (p i ) [16,17]. By using the contraction principle, the large deviation function for the currents can be expressed as I(J ) = min p I(J , p) = I(J , p * (J )).…”
Section: Introductionmentioning
confidence: 99%
“…In addition, the complete function ( ) J a characterizes the statistics of exponentially rare realizations a T that deviate substantially from á ñ a st . Recent applications of large deviation functions to describe rare events in statistical mechanics can be found in [8][9][10][11][12][13][14].Different Brownian functionals deriving from the same stochastic process ( ) x t have different large deviation functions. On the other hand, we may rewrite (1.1) as New J. Phys.…”
mentioning
confidence: 99%
“…, it was dubbed level 2.5 [14]. For the above contraction, however, no closed form for NESS is known.…”
mentioning
confidence: 99%
See 1 more Smart Citation