Strong local nondeterminism for stochastic time-fractional slow and fast diffusion equations

TL;DR

This paper establishes sharp conditions and properties for solutions to stochastic time-fractional diffusion equations driven by Gaussian noise, including local nondeterminism, regularity, and small ball probability bounds.

Contribution

It introduces new sharp Dalang-type conditions for existence and analyzes local nondeterminism and regularity properties of solutions across a broad parameter range.

Findings

Sharp variance bounds for increments

Strong local nondeterminism in time and space

Exact moduli of continuity and small ball probability estimates

Abstract

We study a class of stochastic time-fractional equations on $\mathbb{R}^d$ driven by a centered Gaussian noise, involving a Caputo time derivative of order $\beta>0$, a fractional (power) Laplacian of order $\alpha>0$, and a Riemann-Liouville time integral of order $\gamma\ge0$ acting on the noise. The noise is fractional in time (index $H$) and Riesz-type in space (index $\ell$). We derive sharp Dalang-type necessary and sufficient conditions for the existence of a random field solution across almost full parameter range $(\alpha,\beta,\gamma;H,\ell)$. Under the Dalang-type conditions, we prove sharp variance bounds for temporal and spatial increments, as well as strong local nondeterminism in time in several regimes (two-sided version for $\beta=1$ and for parts of the case $\beta=2$; one-sided version for $0<\beta<2$) and strong local nondeterminism in space for the whole range of parameters. As applications, we derive exact uniform and local moduli of continuity, Chung-type laws of the iterated logarithm, and quantitative bounds on small ball probabilities. Along the way, we obtain sharp asymptotics for the fundamental solution kernels at $0$ and $\infty$, which may be of independent interest.