Most Probable Flows for Kunita SDEs

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Standard

Most Probable Flows for Kunita SDEs. / Grong, Erlend; Sommer, Stefan.

I: Applied Mathematics and Optimization, Bind 89, Nr. 2, 44, 2024.

Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt

Harvard

Grong, E & Sommer, S 2024, 'Most Probable Flows for Kunita SDEs', Applied Mathematics and Optimization, bind 89, nr. 2, 44. https://doi.org/10.1007/s00245-024-10110-z

APA

Grong, E., & Sommer, S. (2024). Most Probable Flows for Kunita SDEs. Applied Mathematics and Optimization, 89(2), [44]. https://doi.org/10.1007/s00245-024-10110-z

Vancouver

Grong E, Sommer S. Most Probable Flows for Kunita SDEs. Applied Mathematics and Optimization. 2024;89(2). 44. https://doi.org/10.1007/s00245-024-10110-z

Author

Grong, Erlend ; Sommer, Stefan. / Most Probable Flows for Kunita SDEs. I: Applied Mathematics and Optimization. 2024 ; Bind 89, Nr. 2.

Bibtex

@article{e49e78e3b0a6483a8303bda272aa914a,
title = "Most Probable Flows for Kunita SDEs",
abstract = "We identify most probable flows for Kunita Brownian motions, i.e. stochastic flows with Eulerian noise and deterministic drifts. Such stochastic processes appear for example in fluid dynamics and shape analysis modelling coarse scale deterministic dynamics together with fine-grained noise. We treat this infinite dimensional problem by equipping the underlying domain with a Riemannian metric originating from the noise. The resulting most probable flows are compared with the non-perturbed deterministic flow, both analytically and experimentally by integrating the equations with various choice of noise structures.",
author = "Erlend Grong and Stefan Sommer",
year = "2024",
doi = "10.1007/s00245-024-10110-z",
language = "English",
volume = "89",
journal = "Applied Mathematics and Optimization",
issn = "0095-4616",
publisher = "Springer",
number = "2",

}

RIS

TY - JOUR

T1 - Most Probable Flows for Kunita SDEs

AU - Grong, Erlend

AU - Sommer, Stefan

PY - 2024

Y1 - 2024

N2 - We identify most probable flows for Kunita Brownian motions, i.e. stochastic flows with Eulerian noise and deterministic drifts. Such stochastic processes appear for example in fluid dynamics and shape analysis modelling coarse scale deterministic dynamics together with fine-grained noise. We treat this infinite dimensional problem by equipping the underlying domain with a Riemannian metric originating from the noise. The resulting most probable flows are compared with the non-perturbed deterministic flow, both analytically and experimentally by integrating the equations with various choice of noise structures.

AB - We identify most probable flows for Kunita Brownian motions, i.e. stochastic flows with Eulerian noise and deterministic drifts. Such stochastic processes appear for example in fluid dynamics and shape analysis modelling coarse scale deterministic dynamics together with fine-grained noise. We treat this infinite dimensional problem by equipping the underlying domain with a Riemannian metric originating from the noise. The resulting most probable flows are compared with the non-perturbed deterministic flow, both analytically and experimentally by integrating the equations with various choice of noise structures.

U2 - 10.1007/s00245-024-10110-z

DO - 10.1007/s00245-024-10110-z

M3 - Journal article

VL - 89

JO - Applied Mathematics and Optimization

JF - Applied Mathematics and Optimization

SN - 0095-4616

IS - 2

M1 - 44

ER -

ID: 383890930