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We uncover the gradient structure to investigate the convergence of solutions in nonlocal nonlinear dynamical systems. Mainly but not exclusively, we use the Lojasiewicz inequality to prove convergence results in various spaces with…

Analysis of PDEs · Mathematics 2022-05-20 Won Eui Hong

We consider a singular stochastic control problem, which is called the Monotone Follower Stochastic Control Problem and give sufficient conditions for the existence and uniqueness of a local-time type optimal control. To establish this…

Optimization and Control · Mathematics 2007-05-23 Erhan Bayraktar , Masahiko Egami

We introduce a stochastic version of Gubinelli's sewing lemma, providing a sufficient condition for the convergence in moments of some random Riemann sums. Compared with the deterministic sewing lemma, adaptiveness is required and the…

Probability · Mathematics 2021-10-12 Khoa Lê

This paper considers approximate smoothing for discretely observed non-linear stochastic differential equations. The problem is tackled by developing methods for linearising stochastic differential equations with respect to an arbitrary…

Methodology · Statistics 2019-01-21 Filip Tronarp , Simo Särkkä

This work aims to construct an efficient and highly accurate numerical method to address the time singularity at $t=0$ involved in a class of time-fractional parabolic integro-partial differential equations in one and two dimensions. The…

Numerical Analysis · Mathematics 2024-09-27 Sudarshan Santra , Ratikanta Behera

In the paper stochastic Volterra equations of nonscalar type in Hilbert space are studied. The aim of the paper is to provide some results on stochastic convolution and mild solutions to those Volterra equations. The motivation of the paper…

Probability · Mathematics 2007-05-23 Anna Karczewska

We study the one-dimensional isentropic compressible Euler equations with linear (frictional) damping, subject to multiplicative, white-in-time stochastic forcing. The system is posed on a bounded interval with $L^\infty$ initial data and…

Analysis of PDEs · Mathematics 2026-03-19 Rongyi Dai , Jeffrey Kuan , Krutika Tawri , Sunčica Čanić , Konstantina Trivisa

We analyse a Monte Carlo particle method for the simulation of the calibrated Heston-type local stochastic volatility (H-LSV) model. The common application of a kernel estimator for a conditional expectation in the calibration condition…

Computational Finance · Quantitative Finance 2025-04-22 Christoph Reisinger , Maria Olympia Tsianni

Molecular simulations of many particles which move rather according to a brownian than a newtonian type of dynamics, nevertheless, can be performed by means of a "velocity-Verlet-like" algorithm. The derivation of this algorithm requires…

Computational Physics · Physics 2009-06-11 Tobias Gleim

In this article integro-differential Volterra equations whose convolution kernel depends on the vector variable are considered and a connection of these equations with a class of semi-Markov processes is established. The variable order…

Probability · Mathematics 2018-07-19 Mladen Savov , Bruno Toaldo

We study the persistence in a class of continuous stochastic processes that are stationary only under integer shifts of time. We show that under certain conditions, the persistence of such a continuous process reduces to the persistence of…

Statistical Mechanics · Physics 2009-11-07 Satya N. Majumdar , Deepak Dhar

We investigate the statistics of the local time $\mathcal{T} = \int_0^T \delta(x(t)) dt$ that a run and tumble particle (RTP) $x(t)$ in one dimension spends at the origin, with or without an external drift. By relating the local time to the…

Statistical Mechanics · Physics 2024-08-13 Soheli Mukherjee , Pierre Le Doussal , Naftali R. Smith

We derive a generalised It\=o formula for stochastic processes which are constructed by a convolution of a deterministic kernel with a centred L\'evy process. This formula has a unifying character in the sense that it contains the classical…

Probability · Mathematics 2015-03-03 Christian Bender , Robert Knobloch , Philip Oberacker

We consider a stochastic Volterra integral equation with regular path-dependent coefficients and a Brownian motion as integrator in a multidimensional setting. Under an imposed absolute continuity condition, the unique solution is a…

Probability · Mathematics 2021-03-29 Alexander Kalinin

A particular type of random dynamical processes is considered, in which the stochasticity is introduced through randomly fluctuating parameters. A method of local multipliers is developed for treating the local stability of such dynamical…

Disordered Systems and Neural Networks · Physics 2015-06-25 V. I. Yukalov

In this article, we analyze three classes of time-reversal of a Markov process with Gaussian noise on a manifold. We first unveil a commutativity constraint for the most general of these time-reversals to be well defined. Then we give a…

Statistical Mechanics · Physics 2024-08-09 Jérémy O'Byrne , Michael E. Cates

The empirical measure flow of a McKean-Vlasov $n$-particle system with common noise is a measure-valued process whose law solves an associated martingale problem. We obtain a stability result for the sequence of martingale problems: all…

Probability · Mathematics 2025-09-01 Robert Alexander Crowell

This work considers the problem of finding a first-order stationary point of a non-convex function with potentially unbounded smoothness constant using a stochastic gradient oracle. We focus on the class of $(L_0,L_1)$-smooth functions…

Machine Learning · Statistics 2023-02-14 Matthew Faw , Litu Rout , Constantine Caramanis , Sanjay Shakkottai

We prove a weak error estimate for the approximation in space and time of a semilinear stochastic Volterra integro-differential equation driven by additive space-time Gaussian noise. We treat this equation in an abstract framework, in which…

Numerical Analysis · Mathematics 2016-03-15 Adam Andersson , Mihály Kovács , Stig Larsson

We study the regularity properties of integro-partial differential equations of Hamilton-Jocobi-Bellman type with terminal condition, which can be interpreted through a stochastic control system, composed of a forward and a backward…

Probability · Mathematics 2011-10-10 Shuai Jing