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In this article, we establish integration by parts formulas for the solutions of McKean-Vlasov stochastic differential equations with jumps under elliptic coefficients. The derived formulas accommodate both derivatives with respect to…

Probability · Mathematics 2026-05-21 Yao Chen , Jiagang Ren , Hua Zhang

Using arithmetic jet spaces, we attach perfectoid spaces to smooth schemes and to $\delta$-morphisms of smooth schemes. We also study perfectoid spaces attached to arithmetic differential equations defined by some of the remarkable…

Number Theory · Mathematics 2019-11-04 Alexandru Buium , Lance Edward Miller

We formulate a new class of stochastic partial differential equations (SPDEs), named high-order vector backward SPDEs (B-SPDEs) with jumps, which allow the high-order integral-partial differential operators into both drift and diffusion…

Probability · Mathematics 2011-05-05 Wanyang Dai

Many important features of a field theory, {\it e.g.}, conserved currents, symplectic structures, energy-momentum tensors, {\it etc.}, arise as tensors locally constructed from the fields and their derivatives. Such tensors are naturally…

General Relativity and Quantum Cosmology · Physics 2007-05-23 C. G. Torre

We study stochastic delay differential equations (SDDE) where the coefficients depend on the moving averages of the state process. As a first contribution, we provide sufficient conditions under which a linear path functional of the…

Probability · Mathematics 2013-10-17 Salvatore Federico , Peter Tankov

Stochastic differential equations (SDEs) provide a flexible framework for modeling temporal dynamics in partially observed systems. A central task is to calibrate such models from data, which requires inferring latent trajectories and…

Machine Learning · Statistics 2026-05-08 Yu Wang , Arnab Ganguly

Symmetry methods are by now recognized as one of the main tools to attack deterministic differential equations (both ODEs and PDEs); the situation is quite different for what concerns stochastic differential equations: here, symmetry…

Mathematical Physics · Physics 2007-05-23 Giuseppe Gaeta

This paper contributes to the theory of singularities of meromorphic linear ODEs in traceless $2\times2$ cases, focusing on their deformations and confluences. It is divided into two parts: The first part addresses individual singularities…

Classical Analysis and ODEs · Mathematics 2024-12-05 Martin Klimeš

The goal of this study is to provide a method for computing the following: Given a network of curves in 3d (satisfying a condition at the intersection points), compute efficiently a smooth surface such that the curves are geodesics on it.…

Computational Geometry · Computer Science 2024-06-04 Tom Gilat

We study stochastic differential equations (SDEs) with multiplicative Stratonovich-type noise of the form $ dX_t = b(X_t) dt + \sigma(X_t)\circ d W_t, X_0=x_0\in\mathbb{R}^d, t\geq0,$ with a possibly singular drift $b\in…

Probability · Mathematics 2021-09-28 Chengcheng Ling , Sebastian Riedel , Michael Scheutzow

We consider the problem of optimally stopping a general one-dimensional stochastic differential equation (SDE) with generalised drift over an infinite time horizon. First, we derive a complete characterisation of the solution to this…

Probability · Mathematics 2019-09-26 Mihail Zervos , Neofytos Rodosthenous , Pui Chan Lon , Thomas Bernhardt

We deal with a class of semilinear parabolic PDEs on the space of continuous functions that arise, for example, as Kolmogorov equations associated to the infinite-dimensional lifting of path-dependent SDEs. We investigate existence of…

Probability · Mathematics 2019-10-14 Federica Masiero , Carlo Orrieri , Gianmario Tessitore , Giovanni Zanco

Multiscale stochastic dynamical systems have been widely adopted to a variety of scientific and engineering problems due to their capability of depicting complex phenomena in many real world applications. This work is devoted to…

Machine Learning · Statistics 2024-01-02 Lingyu Feng , Ting Gao , Min Dai , Jinqiao Duan

Non-relativistic particles that are effectively confined to two dimensions can in general move on curved surfaces, allowing dynamical phenomena beyond what can be described with scalar potentials or even vector gauge fields. Here we…

Quantum Physics · Physics 2022-11-15 James R. Anglin , Etienne Wamba

Partial differential equations (PDEs) with spatially-varying coefficients arise throughout science and engineering, modeling rich heterogeneous material behavior. Yet conventional PDE solvers struggle with the immense complexity found in…

Graphics · Computer Science 2022-02-01 Rohan Sawhney , Dario Seyb , Wojciech Jarosz , Keenan Crane

These are course notes on the application of SDEs to options pricing. The author was partially supported by NSF grant DMS-0739195.

Mathematical Finance · Quantitative Finance 2019-01-03 Andrew Papanicolaou

The machine learning methods for data-driven identification of partial differential equations (PDEs) are typically defined for a given number of spatial dimensions and a choice of coordinates the data have been collected in. This dependence…

Machine Learning · Computer Science 2025-10-07 Trung V. Phan , George A. Kevrekidis , Soledad Villar , Yannis G. Kevrekidis , Juan M. Bello-Rivas

The paper deals with the numerical solution of the nonlinear Ito stochastic differential equations (SDEs) appearing in the unravelling of quantum master equations. We first develop an exponential scheme of weak order 1 for general globally…

Probability · Mathematics 2007-05-23 Carlos M. Mora

Consider a manifold $M$ endowed locally with a pair of complementary distributions $\Delta^H \oplus \Delta^V=TM$ and let $\text{Diff}(\Delta^H, M)$ and $\text{Diff}(\Delta^V, M)$ be the corresponding Lie subgroups generated by vector fields…

Dynamical Systems · Mathematics 2015-11-05 Alison M. Melo , Leandro Morgado , Paulo R. Ruffino

Numerical methods for stochastic differential equations with non-globally Lipschitz coefficients are currently studied intensively. This article gives an overview of our work for the case that the drift coefficient is potentially…

Numerical Analysis · Mathematics 2021-04-26 Michaela Szölgyenyi