Markovian Embedding of Nonlinear Memory via Spectral Representation

Fuente: arXiv
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Autori principali: Jaganathan, Divya, Valani, Rahil N.
Natura: Preprint
Pubblicazione: 2023
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author Jaganathan, Divya
Valani, Rahil N.
author_facet Jaganathan, Divya
Valani, Rahil N.
contents Differential equations containing memory terms that depend nonlinearly on past states model a variety of non-Markovian processes. In this study, we present a Markovian embedding procedure for such equations with distributed delay by utilising an exact spectral representation of the nonlinear memory function. This allows us to transform the nonlocal system to an equivalent local-in-time system in an abstract extended space. We demonstrate our embedding procedure for two one-dimensional physical models: (i) the walking droplet and (ii) the single-phase Stefan problem. In addition to providing an alternative representation of the underlying physical system, the local representation finds applications in designing efficient time-integrators with time-independent computational costs for memory-dependent systems which typically suffer from growing-in-time costs.
format Preprint
id arxiv_https___arxiv_org_abs_2402_00009
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Markovian Embedding of Nonlinear Memory via Spectral Representation
Jaganathan, Divya
Valani, Rahil N.
Numerical Analysis
Computational Physics
Fluid Dynamics
Differential equations containing memory terms that depend nonlinearly on past states model a variety of non-Markovian processes. In this study, we present a Markovian embedding procedure for such equations with distributed delay by utilising an exact spectral representation of the nonlinear memory function. This allows us to transform the nonlocal system to an equivalent local-in-time system in an abstract extended space. We demonstrate our embedding procedure for two one-dimensional physical models: (i) the walking droplet and (ii) the single-phase Stefan problem. In addition to providing an alternative representation of the underlying physical system, the local representation finds applications in designing efficient time-integrators with time-independent computational costs for memory-dependent systems which typically suffer from growing-in-time costs.
title Markovian Embedding of Nonlinear Memory via Spectral Representation
topic Numerical Analysis
Computational Physics
Fluid Dynamics
url https://arxiv.org/abs/2402.00009