Dimension Reduction for Systems with Slow Relaxation: In Memory of Leo P. Kadanoff

Shankar C. Venkataramani, Raman C. Venkataramani, Juan M. Restrepo

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

We develop reduced, stochastic models for high dimensional, dissipative dynamical systems that relax very slowly to equilibrium and can encode long term memory. We present a variety of empirical and first principles approaches for model reduction, and build a mathematical framework for analyzing the reduced models. We introduce the notions of universal and asymptotic filters to characterize ‘optimal’ model reductions for sloppy linear models. We illustrate our methods by applying them to the practically important problem of modeling evaporation in oil spills.

Original languageEnglish
Pages (from-to)892-933
Number of pages42
JournalJournal of Statistical Physics
Volume167
Issue number3-4
DOIs
StatePublished - May 1 2017
Externally publishedYes

Funding

FundersFunder number
National Science Foundation1524241

    Keywords

    • Aging
    • Dimension reduction
    • Glassy systems
    • Mori–Zwanzig projection
    • Multi-scale
    • Oil spills
    • Sloppy models
    • Slow relaxation
    • Weathering

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