Long-Time Asymptotics for Subordinated Fractional Diffusion Equations

Fuente: arXiv
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Main Authors: Majdoub, Mohamed, Mliki, Ezzedine
Format: Preprint
Published: 2025
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author Majdoub, Mohamed
Mliki, Ezzedine
author_facet Majdoub, Mohamed
Mliki, Ezzedine
contents We study the long-time behavior of solutions to a class of evolution equations arising from random-time changes driven by subordinators. Our focus is on fractional diffusion equations involving mixed local and nonlocal operators. By combining techniques from probability theory, asymptotic analysis, and partial differential equations (PDEs), we characterize the dynamics of the subordinated solutions. This approach extends classical fractional dynamics and establishes a deeper connection between stochastic processes and deterministic PDEs.
format Preprint
id arxiv_https___arxiv_org_abs_2509_10203
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Long-Time Asymptotics for Subordinated Fractional Diffusion Equations
Majdoub, Mohamed
Mliki, Ezzedine
Analysis of PDEs
Probability
We study the long-time behavior of solutions to a class of evolution equations arising from random-time changes driven by subordinators. Our focus is on fractional diffusion equations involving mixed local and nonlocal operators. By combining techniques from probability theory, asymptotic analysis, and partial differential equations (PDEs), we characterize the dynamics of the subordinated solutions. This approach extends classical fractional dynamics and establishes a deeper connection between stochastic processes and deterministic PDEs.
title Long-Time Asymptotics for Subordinated Fractional Diffusion Equations
topic Analysis of PDEs
Probability
url https://arxiv.org/abs/2509.10203