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Related papers: Speeding up the Euler scheme for killed diffusions

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In this paper, we study the large--time behavior of a numerical scheme discretizing drift-- diffusion systems for semiconductors. The numerical method is finite volume in space, implicit in time, and the numerical fluxes are a…

Numerical Analysis · Mathematics 2019-04-22 Marianne Bessemoulin-Chatard , Claire Chainais-Hillairet

The implicit Euler method integrates systems of ordinary differential equations $$\frac{d x}{d t}=G(t,x(t))$$ with differentiable right-hand side $G : {\mathbb R} \times {\mathbb R}^n \rightarrow {\mathbb R}^n$ from an initial state $x=x(0)…

Numerical Analysis · Mathematics 2024-09-19 Uwe Naumann

We extend some results on the convergence of one-dimensional diffusions killed at the boundary, conditioned on extended survival, to the case of general killing on the interior. We show, under fairly general conditions, that a diffusion…

Probability · Mathematics 2007-05-23 David Steinsaltz , Steven N. Evans

This paper focuses on mean-square approximations of a generalized A\"it-Sahalia interest rate model with Poisson jumps. The main challenge in the construction and analysis of time-discrete numerical schemes is caused by a drift that blows…

Numerical Analysis · Mathematics 2025-07-01 Yingsong Jiang , Ruishu Liu , Minhong Xu

In this work, we consider the numerical recovery of a spatially dependent diffusion coefficient in a subdiffusion model from distributed observations. The subdiffusion model involves a Caputo fractional derivative of order $\alpha\in(0,1)$…

Numerical Analysis · Mathematics 2021-01-12 Bangti Jin , Zhi Zhou

We derive optimal $L^2$-error estimates for semilinear time-fractional subdiffusion problems involving Caputo derivatives in time of order $\alpha\in (0,1)$, for cases with smooth and nonsmooth initial data. A general framework is…

Numerical Analysis · Mathematics 2020-04-28 Samir Karaa

In this paper, a backward Euler method combined with finite element discretization in spatial direction is discussed for the equations of motion arising in the $2D$ Oldroyd model of viscoelastic fluids of order one with the forcing term…

Numerical Analysis · Mathematics 2026-04-16 Bikram Bir , Deepjyoti Goswami , Amiya K. Pani

This paper develops a quantized Q-learning algorithm for the optimal control of controlled diffusion processes on $\mathbb{R}^d$ under both discounted and ergodic (average) cost criteria. We first establish near-optimality of finite-state…

Optimization and Control · Mathematics 2026-03-16 Erhan Bayraktar , Ali D. Kara , Somnath Pradhan , Serdar Yuksel

This article presents a finite element scheme with Newton's method for solving the time-fractional nonlinear diffusion equation. For time discretization, we use the fractional Crank-Nicolson scheme based on backward Euler convolution…

Analysis of PDEs · Mathematics 2018-11-26 Dileep Kumar , Sudhakar Chaudhary , V. V. K Srinivas Kumar

Explicit discretizations of stochastic differential equations often encounter instability when the coefficients are not globally Lipschitz. The truncated schemes and tamed schemes have been proposed to handle this difficulty, but truncated…

Numerical Analysis · Mathematics 2025-07-15 Zichang Ju , Lei Li , Yuliang Wang

In this paper, we propose a linear and monolithic finite element method for the approximation of an incompressible viscous fluid interacting with an elastic and deforming plate. We use the arbitrary Lagrangian-Eulerian (ALE) approach that…

Numerical Analysis · Mathematics 2023-01-13 Sebastian Schwarzacher , Bangwei She , Karel Tuma

In this paper, we analyze the drift-implicit (or backward) Euler numerical scheme for a class of stochastic differential equations with unbounded drift driven by an arbitrary $\lambda$-H\"older continuous process, $\lambda\in(0,1)$. We…

Probability · Mathematics 2022-04-20 Giulia Di Nunno , Yuliya Mishura , Anton Yurchenko-Tytarenko

In order to describe or estimate different quantities related to a specific random variable, it is of prime interest to numerically generate such a variate. In specific situations, the exact generation of random variables might be either…

Probability · Mathematics 2020-04-07 Samuel Herrmann , Cristina Zucca

In this paper, we investigate the problem of strong approximation of the solutions of stochastic differential equations (SDEs) when the drift coefficient is given in integral form. We investigate its upper error bounds, in terms of the…

Numerical Analysis · Mathematics 2025-11-20 Paweł Przybyłowicz , Michał Sobieraj

We consider the empirical process G_t of a one-dimensional diffusion with finite speed measure, indexed by a collection of functions F. By the central limit theorem for diffusions, the finite-dimensional distributions of G_t converge weakly…

Probability · Mathematics 2007-05-23 Aad van der Vaart , Harry van Zanten

Viewing optimization methods as numerical integrators for ordinary differential equations (ODEs) provides a thought-provoking modern framework for studying accelerated first-order optimizers. In this literature, acceleration is often…

Optimization and Control · Mathematics 2021-02-24 Peiyuan Zhang , Antonio Orvieto , Hadi Daneshmand , Thomas Hofmann , Roy Smith

Diffusion models, which convert noise into new data instances by learning to reverse a diffusion process, have become a cornerstone in contemporary generative modeling. In this work, we develop non-asymptotic convergence theory for a…

Machine Learning · Computer Science 2024-08-06 Gen Li , Yuting Wei , Yuejie Chi , Yuxin Chen

In this paper we discuss the local discontinuous Galerkin methods coupled with two specific explicit-implicit-null time discretizations for solving one-dimensional nonlinear diffusion problems $U_t=(a(U)U_x)_x$. The basic idea is to add and…

Numerical Analysis · Mathematics 2019-03-29 Haijin Wang , Qiang Zhang , Shiping Wang , Chi-Wang Shu

We review some recent results of quantitative long-time convergence for the law of a killed Markov process conditioned to survival toward a quasi-stationary distribution, and on the analogous question for the particle systems used in…

Probability · Mathematics 2023-05-26 Bertrand Cloez , Lucas Journel , Pierre Monmarché , Boris Nectoux , Mouad Ramil

This paper deals with the backward Euler method applied to semilinear parabolic stochastic partial differential equations (SPDEs) driven by additive noise. The SPDE is discretized in space by the finite element method and in time by the…

Numerical Analysis · Mathematics 2020-01-01 Jean Daniel Mukam , Antoine Tambue
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