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Non-autonomous differential equations are crucial for modeling systems influenced by external signals, yet fitting these models to data becomes particularly challenging when the signals change abruptly. To address this problem, we propose a…

Machine Learning · Computer Science 2025-07-10 Hyeontae Jo , Krešimir Josić , Jae Kyoung Kim

In this paper we develop a novel method to solve problems involving quantum optical systems coupled to coherent quantum feedback loops featuring time delays. Our method is based on exact mappings of such non-Markovian problems to equivalent…

Quantum Physics · Physics 2023-11-14 Kseniia Vodenkova , Hannes Pichler

A system of inhomogeneous second-order difference equations with linear parts given by noncommutative matrix coefficients are considered. Closed form of its solution is derived by means of newly defined delayed matrix sine/cosine using the…

Dynamical Systems · Mathematics 2025-02-28 Nazim I. Mahmudov

Non-linear state estimation and some related topics, like parametric estimation, fault diagnosis, and perturbation attenuation, are tackled here via a new methodology in numerical differentiation. The corresponding basic system theoretic…

Computational Engineering, Finance, and Science · Computer Science 2008-11-06 Michel Fliess , Cédric Join , Hebertt Sira-Ramirez

We present a computational method for studying transverse homoclinic orbits for periodic solutions of delay differential equations, a phenomenon that we refer to as the \emph{Poincar\'{e} scenario}. The strategy is geometric in nature, and…

Dynamical Systems · Mathematics 2023-10-17 Olivier Hénot , Jean-Philippe Lessard , Jason D. Mireles James

In this paper we consider a linearized variable-time-step two-step backward differentiation formula (BDF2) scheme for solving nonlinear parabolic equations. The scheme is constructed by using the variable time-step BDF2 for the linear term…

Numerical Analysis · Mathematics 2025-08-29 Chengchao Zhao , Nan Liu , Yuheng Ma , Jiwei Zhang

Solving complex optimization problems in engineering and the physical sciences requires repetitive computation of multi-dimensional function derivatives. Commonly, this requires computationally-demanding numerical differentiation such as…

Numerical Analysis · Mathematics 2021-05-12 Danny Smyl , Tyler N. Tallman , Dong Liu , Andreas Hauptmann

This paper addresses the challenging numerical simulation of nonlinear hybrid stochastic functional differential equations with infinite delays. We first propose an explicit scheme using space and time truncation, requiring only finite…

Numerical Analysis · Mathematics 2025-12-23 Guozhen Li , Xiaoyue Li , Xuerong Mao

Dynamic systems described by differential equations often involve feedback among system components. When there are time delays for components to sense and respond to feedback, delay differential equation (DDE) models are commonly used. This…

Methodology · Statistics 2024-06-24 Yuxuan Zhao , Samuel W. K. Wong

We provide sufficient conditions for the existence of invariant probability measures for generic stochastic differential equations with finite time delay. This is achieved by means of the Krylov-Bogoliubov method. Furthermore, we focus on…

Dynamical Systems · Mathematics 2026-05-15 Mark van den Bosch , Onno van Gaans , Sjoerd Verduyn Lunel

This paper studies the second moment boundedness of solutions of linear stochastic delay differential equations. First, we give a framework, for general $\mathrm{N}$-dimensional linear stochastic differential equations with a single…

Statistics Theory · Mathematics 2012-10-11 Zhen Wang , Xiong Li , Jinzhi Lei

A stochastic differential equation with coefficients defined in a scale of Hilbert spaces is considered. The existence and uniqueness of finite time solutions is proved by an extension of the Ovsyannikov method. This result is applied to a…

Functional Analysis · Mathematics 2018-05-15 Alexei Daletskii

The numerical solution of differential equations can be formulated as an inference problem to which formal statistical approaches can be applied. However, nonlinear partial differential equations (PDEs) pose substantial challenges from an…

Numerical Analysis · Mathematics 2021-08-26 Junyang Wang , Jon Cockayne , Oksana Chkrebtii , T. J. Sullivan , Chris. J. Oates

A linearized numerical scheme is proposed to solve the nonlinear time fractional parabolic problems with time delay. The scheme is based on the standard Galerkin finite element method in the spatial direction, the fractional Crank-Nicolson…

Numerical Analysis · Mathematics 2021-09-10 Lili Li , Mianfu She , Yuanling Niu

We study a particular class of autonomous Differential-Algebraic Equations that are equivalent to Ordinary Differential Equations on manifolds. Under appropriate assumptions we determine an easy-to-use straightforward formula for the…

Classical Analysis and ODEs · Mathematics 2009-08-14 Marco Spadini

This paper studies the problem of stability of a parameterized delay differential equations (DDE see equation (0.1)). After discretizing the DDE (0.1), we show that the problem can be equivalently casted into a semi-definite programming…

Optimization and Control · Mathematics 2017-01-03 Dongcai Su

The fundamental matrix and the delay Lyapunov matrix of linear delay difference equations are introduced. Some properties of the Lyapunov matrix, and the jump discontinuities of its derivative are proven, leading to its construction in the…

Dynamical Systems · Mathematics 2016-12-15 Emanuel Rocha , Sabine Mondié , Michael Di Loreto

Coefficient inverse problems related to identifying the right-hand side of an equation with use of additional information is of interest among inverse problems for partial differential equations. When considering non-stationary problems,…

Numerical Analysis · Computer Science 2016-04-18 Petr N. Vabishchevich

Non-Markovian dynamics is ubiquitous in both quantum and classical systems, but the numerical computation of the time-delay dynamics is demanding. In this work, we propose an efficient quantum algorithm for solving linear distributed delay…

Quantum Physics · Physics 2026-03-19 Wataru Setoyama , Keisuke Fujii

We propose a machine learning framework to accelerate numerical computations of time-dependent ODEs and PDEs. Our method is based on recasting (generalizations of) existing numerical methods as artificial neural networks, with a set of…

Numerical Analysis · Mathematics 2019-03-08 Siddhartha Mishra
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