activity
20192026
collaborators

7 papers

math.PR2026

Intermittency of geometric Brownian motion on

Sefika Kuzgun, Felix Otto, Christian Wagner

This short note is motivated by a recently discovered connection between a drift-diffusion process in -dimensional Euclidean space with a divergence-free drift sampled from a st…

math.PR2024

Time-dependent averages of a critical long-range stochastic heat equation

Sefika Kuzgun, Ran Tao

We study the time-dependent spatial averages of a critical stochastic partial differential equation, namely the stochastic heat equation in dimension with noise white in…

math.PR2023

On the radius of self-repellent fractional Brownian motion

Le Chen, Sefika Kuzgun, Carl Mueller +1

We study the radius of a self-repellent fractional Brownian motion taking values in . Our sharpest result is for , whe…

math.PR2022

Convergence of densities of spatial averages of the parabolic Anderson model driven by colored noise

Sefika Kuzgun, David Nualart

In this paper, we present a rate of convergence in the uniform norm for the densities of spatial averages of the solution to the d-dimensional parabolic Anderson model driven by a…

math.PR2021

Convergence of Densities of Spatial Averages of Stochastic Heat Equation

Sefika Kuzgun, David Nualart

In this paper, we consider the one-dimensional stochastic heat equation driven by a space time white noise. In two different scenarios: {\it (i)} initial condition and gene…

math.PR2020

Feynman-Kac formula for iterated derivatives of the parabolic Anderson model

Sefika Kuzgun, David Nualart

The purpose of this paper is to establish a Feynman-Kac formula for the moments of the iterated Malliavin derivatives of the solution to the parabolic Anderson model in terms of pi…

math.PR2019

Rate of Convergence in the Breuer-Major Theorem via Chaos Expansions

Sefika Kuzgun, David Nualart

We show new estimates for the total variation and Wasserstein distances in the framework of the Breuer-Major theorem. The results are based on the combination of Stein's method for…