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19992026
most citedHypocoercivity for Kolmogorov backward evolution equations and applications

41 citations · 257 across the 53 of their papers we have counts for

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Showing 2021 · math.PRShow all

7 papers · 2 filters

math.PR2021★ 1 cited

Stochastic analysis for vector-valued generalized grey Brownian motion

Wolfgang Bock, Martin Grothaus, Karlo Orge

In this article, we show that the standard vector-valued generalization of a generalized grey Brownian motion (ggBm) has independent components if and only if it is a fractional Br…

math.PR2021

Dirichlet form analysis of the Jacobi process

Martin Grothaus, Max Sauerbrey

We construct and analyze the Jacobi process - in mathematical biology referred to as Wright-Fisher diffusion - using a Dirichlet form. The corresponding Dirichlet space takes the f…

math.PR2021

Convergence Rate for Degenerate Partial and Stochastic Differential Equations via weak Poincaré Inequalities

Alexander Bertram, Martin Grothaus

We employ weak hypocoercivity methods to study the long-term behavior of operator semigroups generated by degenerate Kolmogorov operators with variable second-order coefficients, w…

math.PR2021★ 4 cited

An improved characterisation of regular generalised functions of white noise and an application to singular SPDEs

Martin Grothaus, Jan Müller, Andreas Nonnenmacher

A characterisation of the spaces and introduced in Grothaus et al. (Methods Funct Anal Topol 3(2):46-64, 1997) and Potthoff and Timpel (Potential A…

math.PR2021★ 1 cited

Hypocoercivity for non-linear infinite-dimensional degenerate stochastic differential equations

Benedikt Eisenhuth, Martin Grothaus

The aim of this article is to construct solutions to second order in time stochastic partial differential equations and to show hypocoercivity of the corresponding transition semig…

math.PR2021

A White Noise Approach to Stochastic Currents of Brownian Motion

Martin Grothaus, Herry Pribawanto Suryawan, José Luís da Silva

In this paper we study stochastic currents of Brownian motion , , by using white noise analysis. For and for $x=0\in\m…