A simple framework to justify linear response theory

Martin Hairer, Andrew J. Majda

Research output: Contribution to journalArticle

Abstract

The use of linear response theory for forced dissipative stochastic dynamical systems through the fluctuation dissipation theorem is an attractive way to study climate change systematically among other applications. Here, a mathematically rigorous justification of linear response theory for forced dissipative stochastic dynamical systems is developed. The main results are formulated in an abstract setting and apply to suitable systems, in finite and infinite dimensions, that are of interest in climate change science and other applications.

Original languageEnglish (US)
Pages (from-to)909-922
Number of pages14
JournalNonlinearity
Volume23
Issue number4
DOIs
StatePublished - 2010

Fingerprint

Dissipative Dynamical System
Stochastic Dynamical Systems
Linear Response
Climate Change
climate change
Climate change
dynamical systems
Justify
Dynamical systems
Fluctuation-dissipation Theorem
Infinite Dimensions
Justification
dissipation
theorems
Framework

ASJC Scopus subject areas

  • Applied Mathematics
  • Physics and Astronomy(all)
  • Statistical and Nonlinear Physics
  • Mathematical Physics

Cite this

A simple framework to justify linear response theory. / Hairer, Martin; Majda, Andrew J.

In: Nonlinearity, Vol. 23, No. 4, 2010, p. 909-922.

Research output: Contribution to journalArticle

Hairer, Martin ; Majda, Andrew J. / A simple framework to justify linear response theory. In: Nonlinearity. 2010 ; Vol. 23, No. 4. pp. 909-922.
@article{e4b479659b3247aca8c202c6f6f26245,
title = "A simple framework to justify linear response theory",
abstract = "The use of linear response theory for forced dissipative stochastic dynamical systems through the fluctuation dissipation theorem is an attractive way to study climate change systematically among other applications. Here, a mathematically rigorous justification of linear response theory for forced dissipative stochastic dynamical systems is developed. The main results are formulated in an abstract setting and apply to suitable systems, in finite and infinite dimensions, that are of interest in climate change science and other applications.",
author = "Martin Hairer and Majda, {Andrew J.}",
year = "2010",
doi = "10.1088/0951-7715/23/4/008",
language = "English (US)",
volume = "23",
pages = "909--922",
journal = "Nonlinearity",
issn = "0951-7715",
publisher = "IOP Publishing Ltd.",
number = "4",

}

TY - JOUR

T1 - A simple framework to justify linear response theory

AU - Hairer, Martin

AU - Majda, Andrew J.

PY - 2010

Y1 - 2010

N2 - The use of linear response theory for forced dissipative stochastic dynamical systems through the fluctuation dissipation theorem is an attractive way to study climate change systematically among other applications. Here, a mathematically rigorous justification of linear response theory for forced dissipative stochastic dynamical systems is developed. The main results are formulated in an abstract setting and apply to suitable systems, in finite and infinite dimensions, that are of interest in climate change science and other applications.

AB - The use of linear response theory for forced dissipative stochastic dynamical systems through the fluctuation dissipation theorem is an attractive way to study climate change systematically among other applications. Here, a mathematically rigorous justification of linear response theory for forced dissipative stochastic dynamical systems is developed. The main results are formulated in an abstract setting and apply to suitable systems, in finite and infinite dimensions, that are of interest in climate change science and other applications.

UR - http://www.scopus.com/inward/record.url?scp=77949684421&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=77949684421&partnerID=8YFLogxK

U2 - 10.1088/0951-7715/23/4/008

DO - 10.1088/0951-7715/23/4/008

M3 - Article

VL - 23

SP - 909

EP - 922

JO - Nonlinearity

JF - Nonlinearity

SN - 0951-7715

IS - 4

ER -