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The McLachlan "minimum-distance" principle for optimizing approximate solutions of the time-dependent Schrodinger equation is revisited, with a focus on the local-in-time error accompanying the variational solutions. Simple, exact…

Quantum Physics · Physics 2020-04-22 Rocco Martinazzo , Irene Burghardt

The classical Ray-Knight theorems for Brownian motion determine the law of its local time process either at the first hitting time of a given value a by the local time at the origin, or at the first hitting time of a given position b by…

Probability · Mathematics 2020-12-04 Elie Aïdékon , Yueyun Hu , Zhan Shi

In this article we consider likelihood-based estimation of static parameters for a class of partially observed McKean-Vlasov (POMV) diffusion process with discrete-time observations over a fixed time interval. In particular, using the…

Methodology · Statistics 2024-11-12 Ajay Jasra , Mohamed Maama , Raul Tempone

We consider the fully-coupled McKean-Vlasov equation with multi-time-scale potentials, and all the coefficients depend on the distributions of both the slow component and the fast motion. By studying the smoothness of the solution of the…

Probability · Mathematics 2022-04-28 Yun Li , Fuke Wu , Longjie Xie

Statistical fluctuations of local tensorial fields beyond the mean are relevant to predict localized failure or overall behavior of the inelastic composites. The expression for second moments of the local fields can be established using the…

Classical Physics · Physics 2025-02-06 Tarkes Dora Pallicity , Maximillian Krause , Thomas Böhlke

We study the optimal stopping problem of McKean-Vlasov diffusions when the criterion is a function of the law of the stopped process. A remarkable new feature in this setting is that the stopping time also impacts the dynamics of the…

Probability · Mathematics 2023-01-18 Mehdi Talbi , Nizar Touzi , Jianfeng Zhang

We propose two numerical methods for the optimal control of McKean-Vlasov dynamics in finite time horizon. Both methods are based on the introduction of a suitable loss function defined over the parameters of a neural network. This allows…

Optimization and Control · Mathematics 2021-03-31 René Carmona , Mathieu Laurière

From a logic point of view this is the third in the series to solve the problem of absence of detailed balance. This paper will be denoted as SDS III. The existence of a dynamical potential with both local and global meanings in general…

Quantitative Methods · Quantitative Biology 2016-09-08 P. Ao

Our work deals with the systematic study of the coupling between the nonlocal Stokes system and the Vlasov equation. The coupling is due to a drag force generated by the fluid-particles interaction. We establish the existence of global weak…

Analysis of PDEs · Mathematics 2014-07-30 Gabriel Nguetseng , Celestin Wafo Soh , Jean Louis Woukeng

We study a time--space nonlocal diffusion equation driven by additive time--space white noise, where the time derivative is the Caputo derivative of order $\alpha\in(0,2)$. The model couples local diffusion with a nonlocal convolution…

Analysis of PDEs · Mathematics 2026-01-22 M. Alwohaibi , D. Alsaleh , M. El-Beltagy , M. Majdoub , E. Mliki

The Donsker-Varadhan rate function for occupation-time fluctuations has been seen numerically to exhibit monotone return to stationary nonequilibrium [Phys. Rev. Lett. 107, 010601 (2011)]. That rate function is related to dynamical activity…

Mathematical Physics · Physics 2015-05-07 Christian Maes , Karel Netocny , Bram Wynants

In this paper, we set the mathematical foundations of the Dynamical Low-Rank Approximation (DLRA) method for stochastic differential equations (SDEs). DLRA aims at approximating the solution as a linear combination of a small number of…

Numerical Analysis · Mathematics 2024-08-23 Yoshihito Kazashi , Fabio Nobile , Fabio Zoccolan

In this paper we introduce and analyze a class of diffusion type equations related to certain non-Markovian stochastic processes. We start from the forward drift equation which is made non-local in time by the introduction of a suitable…

Mathematical Physics · Physics 2009-11-13 Antonio Mura , Murad S. Taqqu , Francesco Mainardi

We study the time-dependent Navier-Stokes equations in the context of stochastic finite element discretizations. Specifically, we assume that the viscosity is a random field given in the form of a generalized polynomial chaos expansion, and…

Numerical Analysis · Mathematics 2026-01-14 Bedřich Sousedík , Randy Price

For finite size Markov chains, the Donsker-Varadhan theory fully describes the large deviations of the time averaged empirical measure. We are interested in the extension of the Donsker-Varadhan theory for a large size non-equilibrium…

Probability · Mathematics 2024-05-06 Thierry Bodineau , Benoit Dagallier

We introduce a local non-determinism condition for Volterra It\^{o} processes that captures smoothing properties of possibly degenerate noise. By combining the stochastic sewing lemma with one-step Euler approximations, we first prove the…

Probability · Mathematics 2026-03-26 Martin Friesen

Spatial differentiability of solutions of stochastic differential equations (SDEs) is a classical question in stochastic analysis. The case of coefficients with globally Lipschitz continuous derivatives is well understood in the literature.…

Probability · Mathematics 2022-04-27 Anselm Hudde , Martin Hutzenthaler , Sara Mazzonetto

We provide a new version of the Tikhonov theorem for both two-scale forward systems and also two-scale forward-backward systems of stochastic differential equations, which also covers the McKean-Vlasov case. Differently from what is usually…

Probability · Mathematics 2024-03-26 Matteo Burzoni , Alekos Cecchin , Andrea Cosso

We derive an annealed large deviation principle for the normalised local times of a continuous-time random walk among random conductances in a finite domain in $\Z^d$ in the spirit of Donsker-Varadhan \cite{DV75}. We work in the interesting…

Probability · Mathematics 2011-04-11 Wolfgang König , Michele Salvi , Tilman Wolff

Stochastic resetting is a rapidly developing topic in the field of stochastic processes and their applications. It denotes the occasional reset of a diffusing particle to its starting point and effects, inter alia, optimal first-passage…

Statistical Mechanics · Physics 2023-05-25 C. Di Bello , A. V. Chechkin , A. K. Hartmann , Z. Palmowski , R. Metzler