Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
86 tokens/sec
Gemini 2.5 Pro Premium
40 tokens/sec
GPT-5 Medium
27 tokens/sec
GPT-5 High Premium
32 tokens/sec
GPT-4o
94 tokens/sec
DeepSeek R1 via Azure Premium
94 tokens/sec
GPT OSS 120B via Groq Premium
469 tokens/sec
Kimi K2 via Groq Premium
198 tokens/sec
2000 character limit reached

Approximation of Random Evolution Equations of Parabolic type (2404.07660v2)

Published 11 Apr 2024 in math.FA, cs.NA, math.AP, math.NA, and math.PR

Abstract: In this paper, we present an abstract framework to obtain convergence rates for the approximation of random evolution equations corresponding to a random family of forms determined by finite-dimensional noise. The full discretization error in space, time, and randomness is considered, where polynomial chaos expansion (PCE) is used for the semi-discretization in randomness. The main result are regularity conditions on the random forms under which convergence of polynomial order in randomness is obtained depending on the smoothness of the coefficients and the Sobolev regularity of the initial value. In space and time, the same convergence rates as in the deterministic setting are achieved. To this end, we derive error estimates for vector-valued PCE as well as a quantified version of the Trotter--Kato theorem for form-induced semigroups. We apply the abstract framework to an anisotropic diffusion model with random diffusion coefficients.

Summary

We haven't generated a summary for this paper yet.

Dice Question Streamline Icon: https://streamlinehq.com

Follow-up Questions

We haven't generated follow-up questions for this paper yet.

Don't miss out on important new AI/ML research

See which papers are being discussed right now on X, Reddit, and more:

“Emergent Mind helps me see which AI papers have caught fire online.”

Philip

Philip

Creator, AI Explained on YouTube