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We introduce the notion of descriptor embedding for nonlinear systems and use it for the data-driven design of stabilizing controllers. Specifically, we provide sufficient data-dependent LMI conditions which, if feasible, return a…

Optimization and Control · Mathematics 2025-11-04 Mohammad Alsalti , Claudio De Persis , Victor G. Lopez , Matthias A. Müller

We develop a linear-algebraic framework for dimensional analysis in systems with constraints, particularly when variables are numerous or related by implicit relations so that direct elimination is impractical. By expressing both…

Mathematical Physics · Physics 2026-03-31 Umpei Miyamoto

A computational tool for coarse-graining nonlinear systems of ordinary differential equations in time is discussed. Three illustrative model examples are worked out that demonstrate the range of capability of the method. This includes the…

Numerical Analysis · Mathematics 2017-11-23 Sabyasachi Chatterjee , Amit Acharya , Zvi Artstein

Fast, gradient-based structural optimization has long been limited to a highly restricted subset of problems -- namely, density-based compliance minimization -- for which gradients can be analytically derived. For other objective functions,…

Computational Engineering, Finance, and Science · Computer Science 2024-09-17 Keith J. Lee , Yijiang Huang , Caitlin T. Mueller

We present an energy-stable scheme for numerically approximating the governing equations for incompressible two-phase flows with different densities and dynamic viscosities for the two fluids. The proposed scheme employs a scalar-valued…

Computational Physics · Physics 2019-06-26 Z. Yang , S. Dong

Frequently encountered in nature, internal solitary waves in stratified fluids are well-observed and well-studied from the experimental, the theoretical, and the numerical perspective. From the mathematical point of view, these waves are…

Analysis of PDEs · Mathematics 2014-11-03 Andreas Klaiber

Irregular sampling intervals and missing values in real-world time series data present challenges for conventional methods that assume consistent intervals and complete data. Neural Ordinary Differential Equations (Neural ODEs) offer an…

Machine Learning · Computer Science 2025-01-28 YongKyung Oh , Dong-Young Lim , Sungil Kim

We extend the definition of algebraic entropy to a class of differential-delay equations. The vanishing of the entropy, as a structural property of an equation, signals its integrability. We suggest a simple way to produce…

Exactly Solvable and Integrable Systems · Physics 2014-08-27 Claude M. Viallet

This paper investigates the two-dimensional stochastic steady-state Navier-Stokes(NS) equations with additive random noise. We introduce an innovative splitting method that decomposes the stochastic NS equations into a deterministic NS…

Numerical Analysis · Mathematics 2025-04-23 Jie Zhu , Yujun Zhu , Ju Ming , Max D. Gunzburger

Pseudo-differential operator equations with parameter are studied. Uniform separability properties and resolvent estimates are obtained in terms of fractional derivatives. Moreover, maximal regularity properties of the pseudo-differential…

Analysis of PDEs · Mathematics 2017-06-06 Veli Shakhmurov

The behavior of IAD_0 scheme, a fully conservative SPH scheme based on a tensor formulation, is analyzed in connection with several astrophysical scenarios, and compared to the same simulations carried out with the standard SPH technique.…

Instrumentation and Methods for Astrophysics · Physics 2015-06-05 Ruben M. Cabezon , Domingo Garcia-Senz , Jose Antonio Escartin

High index differential algebraic equations (DAEs) are ordinary differential equations (ODEs) with constraints and arise frequently from many mathematical models of physical phenomenons and engineering fields. In this paper, we generalize…

Symbolic Computation · Computer Science 2015-04-21 Xiaolin Qin , Lu Yang , Yong Feng , Bernhard Bachmann , Peter Fritzson

Probabilistic sensitivity analysis identifies the influential uncertain input to guide decision-making. We propose a general sensitivity framework with respect to the input distribution parameters that unifies a wide range of sensitivity…

Methodology · Statistics 2023-02-10 Jiannan Yang

We present a structure-preserving Eulerian algorithm for solving $L^2$-gradient flows and a structure-preserving Lagrangian algorithm for solving generalized diffusions. Both algorithms employ neural networks as tools for spatial…

Numerical Analysis · Mathematics 2024-04-16 Ziqing Hu , Chun Liu , Yiwei Wang , Zhiliang Xu

We present a new temporal discretization paradigm for developing energy-production-rate preserving numerical approximations to thermodynamically consistent partial differential equation systems, called the supplementary variable method. The…

Numerical Analysis · Mathematics 2020-06-09 Yuezheng Gong , Qi Hong , Qi Wang

We propose two different strategies to find eigenvalues and eigenvectors of a given, not necessarily Hermitian, matrix $A$. Our methods apply also to the case of complex eigenvalues, making the strategies interesting for applications to…

Mathematical Physics · Physics 2020-06-24 Fabio Bagarello , Francesco Gargano

The discrete element method (DEM) is providing a new modeling approach for describing sea ice dynamics. It exploits particle-based methods to characterize the physical quantities of each sea ice floe along its trajectory under Lagrangian…

Numerical Analysis · Mathematics 2022-03-09 Nan Chen , Quanling Deng , Samuel N. Stechmann

We construct stable periodic solutions for a simple form nonlinear delay differential equation (DDE) with a periodic coefficient. The equation involves one underlying nonlinearity with the multiplicative periodic coefficient. The well-known…

Dynamical Systems · Mathematics 2024-02-14 Anatoli Ivanov , Sergiy Shelyag

Navier-Stokes equations establish the hydrodynamical problem by definition. The importance of these equations is quite natural to understand if we focus on the role they assume in a large spectrum of dynamical problems which involve…

Mathematical Physics · Physics 2010-07-30 Michele Romeo

We have developed a parallel, simple, and fast hydrodynamics code for multi-dimensional, self-gravitating, adiabatic flows. Our primary motivation is the study of the non-linear evolution of white dwarf oscillations excited via tidal…

Astrophysics · Physics 2009-11-10 Avery E. Broderick , Yasser Rathore