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Motivated by the recent contribution \cite{BB17} we study the scaling limit behavior of a class of one-dimensional stochastic differential equations which has a unique attracting point subject to a small additional repulsive perturbation.…

Mathematical Physics · Physics 2019-06-26 Martin Kolb , Matthias Liesenfeld

In this paper, we extend the dynamical low-rank approximation method to the space of finite signed measures. Under this framework, we derive stochastic low-rank dynamics for stochastic differential equations (SDEs) coming from classical…

Numerical Analysis · Mathematics 2018-07-05 Yu Cao , Jianfeng Lu

We investigate the profound relation between the equations of biological evolution and quantum mechanics by writing a biologically inspired equation for the stochastic dynamics of an ensemble of particles. Interesting behavior is observed…

Statistical Mechanics · Physics 2015-05-20 Ginestra Bianconi , Christoph Rahmede

The present paper is devoted to the study of the asymptotic behavior of the value functions of both finite and infinite horizon stochastic control problems and to the investigation of their relation with suitable stochastic ergodic control…

Probability · Mathematics 2018-04-06 Andrea Cosso , Giuseppina Guatteri , Gianmario Tessitore

In this work we construct a general class of exactly solvable non-relativistic bi-dimensional quantum systems with position-dependent masses (PDM). These systems are isospectral to a given system with constant mass. The case of a charged…

Quantum Physics · Physics 2017-07-14 A. de Souza Dutra , J. A. de Oliveira , R. A. C. Correa , W. de Paula

Likelihood inference for max-stable random fields is in general impossible because their finite-dimensional probability density functions are unknown or cannot be computed efficiently. The weighted composite likelihood approach that…

Statistics Theory · Mathematics 2025-03-11 Nicolas Chenavier , Christian Y. Robert

We investigate a system of Brownian particles weakly bound by attractive parity-symmetric potentials that grow at large distances as $V(x) \sim |x|^\alpha$, with $0 < \alpha < 1$. The probability density function $P(x,t)$ at long times…

Statistical Mechanics · Physics 2024-07-24 Lucianno Defaveri , Eli Barkai , David A. Kessler

In this work, we present a general Milstein-type scheme for McKean-Vlasov stochastic differential equations (SDEs) driven by Brownian motion and Poisson random measure and the associated system of interacting particles where drift,…

Probability · Mathematics 2025-01-08 Sani Biswas , Chaman Kumar , Christoph Reisinger , Verena Schwarz

Motivated by studies of stochastic systems describing non-equilibrium dynamics of (real-valued) spins of an infinite particle system in $\mathbb{R}^n$ we consider a row-finite system of stochastic differential equations with dissipative…

Functional Analysis · Mathematics 2021-08-09 Georgy Chargaziya

Numerical methods for stochastic partial differential equations typically estimate moments of the solution from sampled paths. Instead, we shall directly target the deterministic equations satisfied by the first and second moments, as well…

Numerical Analysis · Mathematics 2020-11-17 Kristin Kirchner

In this work, we present a novel approach for solving stochastic shape optimization problems. Our method is the extension of the classical stochastic gradient method to infinite-dimensional shape manifolds. We prove convergence of the…

Optimization and Control · Mathematics 2020-11-03 Caroline Geiersbach , Estefania Loayza-Romero , Kathrin Welker

We establish a non-explosion result for rough differential equations (RDEs) in which the noise and drift coefficients, together with their derivatives, may grow unboundedly at infinity. In addition, we prove the existence of a global…

Probability · Mathematics 2026-01-27 Xue-Mei Li , Kexing Ying

We consider random fields that can be represented as integrals of deterministic functions with respect to infinitely divisible random measures and show that these random fields are infinitely divisible.

Probability · Mathematics 2010-08-13 Wolfgang Karcher , Hans-Peter Scheffler , Evgeny Spodarev

This dissertation discusses solutions to the nonlinear Klein-Gordon equation with symmetric and asymmetric double-well potentials, focusing on the collapse and collision of bubbles and critical phenomena found therein. A new method is…

High Energy Physics - Phenomenology · Physics 2007-05-23 Ethan Honda

We study Backward Stochastic Differential Equations on a probability space equipped with a Brownian filtration. We assume that the terminal value and the generator at zero are merely integrable. Moreover, the generator is assumed to be…

Probability · Mathematics 2022-08-09 Tomasz Klimsiak , Maurycy Rzymowski

A strong quasi-invariance principle and a finite-dimensional integration by parts formula as in the Bismut approach to Malliavin calculus are obtained through a suitable application of Lie's symmetry theory to autonomous stochastic…

Probability · Mathematics 2023-07-12 Francesco C. De Vecchi , Paola Morando , Stefania Ugolini

Neural Stochastic Differential Equations (NSDEs) model the drift and diffusion functions of a stochastic process as neural networks. While NSDEs are known to make accurate predictions, their uncertainty quantification properties have been…

Machine Learning · Computer Science 2022-09-13 Andreas Look , Melih Kandemir , Barbara Rakitsch , Jan Peters

The quantum-mechanical problems of a nonrelativistic free particle, a harmonic oscillator and a Coulomb particle on Minkowski plane are discussed. The Schr\"odinger equations for eigenvalues are obtained using the Beltrami-Laplas operator…

Quantum Physics · Physics 2020-05-26 N. A. Gromov , I. V. Kostyakov , V. V. Kuratov

We study Hamilton Jacobi Bellman equations in an infinite dimensional Hilbert space, with Lipschitz coefficients, where the Hamiltonian has superquadratic growth with respect to the derivative of the value function, and the final condition…

Probability · Mathematics 2016-11-28 Federica Masiero , Adrien Richou

Stochastic partial differential equations driven by Poisson random measures (PRM) have been proposed as models for many different physical systems, where they are viewed as a refinement of a corresponding noiseless partial differential…

Probability · Mathematics 2012-09-25 Amarjit Budhiraja , Jiang Chen , Paul Dupuis
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