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We developed a novel approach to identification and model testing in linear structural equation models (SEMs) based on auxiliary variables (AVs), which generalizes a widely-used family of methods known as instrumental variables. The…

Methodology · Statistics 2019-10-09 Bryant Chen , Daniel Kumor , Elias Bareinboim

We consider families of systems of two-dimensional ordinary differential equations with the origin $0$ as a non-hyperbolic equilibrium. For any number $s \in (-\infty, +\infty)$ we show that it is possible to choose a parameter in these…

Dynamical Systems · Mathematics 2022-08-30 Alexander Lohse

We derive a hydrodynamical description of the eigenvalues of the chiral Dirac spectrum in the vacuum and in the large $N$ (volume) limit. The linearized hydrodynamics supports sound waves. The stochastic relaxation of the eigenvalues is…

High Energy Physics - Phenomenology · Physics 2015-12-23 Yizhuang Liu , Piotr Warchol , Ismail Zahed

The reliability is of the most importance when employing a numerical method to solve the eigenvalue integral equations. In this paper, we present one type of particular singularities (pseudosingularities) existing in eigenvalue integral…

Computational Physics · Physics 2016-04-19 Jiao-Kai Chen

A new Bayesian approach to linear system identification has been proposed in a series of recent papers. The main idea is to frame linear system identification as predictor estimation in an infinite dimensional space, with the aid of…

Machine Learning · Statistics 2015-07-03 Diego Romeres , Gianluigi Pillonetto , Alessandro Chiuso

We propose a new class of finite element approximations to ideal compressible magnetohydrodynamic equations in smooth regime. Following variational approximations developed for fluid models in the last decade, our discretizations are built…

Numerical Analysis · Mathematics 2024-02-29 Valentin Carlier , Martin Campos-Pinto

Many complex systems can be reduced to their key components through spectrally decomposing matrices that capture their dynamics. These matrices can in turn be constructed from data, often by least-squares fitting: examples of algorithms to…

Numerical Analysis · Mathematics 2026-05-18 Caroline Wormell

Structural parameter identifiability is a property of a differential model with parameters that allows for the parameters to be determined from the model equations in the absence of noise. One of the standard approaches to assessing this…

Algebraic Geometry · Mathematics 2020-12-29 Alexey Ovchinnikov , Gleb Pogudin , Peter Thompson

Second-order superintegrable systems in dimensions two and three are essentially classified. With increasing dimension, however, the non-linear partial differential equations employed in current methods become unmanageable. Here we propose…

Differential Geometry · Mathematics 2025-05-09 Jonathan Kress , Konrad Schöbel , Andreas Vollmer

In the hyperbolic community, discontinuous Galerkin approaches are mainly applied when finite element methods are considered. As the name suggested, the DG framework allows a discontinuity at the element interfaces, which seems for many…

Numerical Analysis · Mathematics 2021-04-20 Rémi Abgrall , Jan Nordström , Philipp Öffner , Svetlana Tokareva

We present the derivation of hydrodynamical equations for a perfect fluid in General Relativity, within the 3+1 decomposition of spacetime framework, using only primitive variables. Primitive variables are opposed to conserved variables, as…

General Relativity and Quantum Cosmology · Physics 2023-04-17 Gaël Servignat , Jerome Novak , Isabel Cordero-Carrión

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

Certain neural network architectures, in the infinite-layer limit, lead to systems of nonlinear differential equations. Motivated by this idea, we develop a framework for analyzing time signals based on non-autonomous dynamical equations.…

Machine Learning · Statistics 2022-04-19 Ryeongkyung Yoon , Harish S. Bhat , Braxton Osting

Conservation laws are an inherent feature in many systems modeling real world phenomena, in particular, those modeling biological and chemical systems. If the form of the underlying dynamical system is known, linear algebra and algebraic…

Numerical Analysis · Mathematics 2024-03-11 Tracey Oellerich , Maria Emelianenko

The Self-Organized Hydrodynamics model of collective behavior is studied on an annular domain. A modal analysis of the linearized model around a perfectly polarized steady-state is conducted. It shows that the model has only pure imaginary…

Mathematical Physics · Physics 2014-07-01 Pierre Degond , Hui Yu

We present a numerical method to solve the equations of general relativistic hydrodynamics in a given external gravitational field. The method is based on a generalization of Roe's approximate Riemann solver for the non relativistic Euler…

Astrophysics · Physics 2007-05-23 Frits Eulderink , Garrelt Mellema

In this article we discuss the numerical analysis for the finite difference scheme of the one-dimensional nonlinear wave equations with dynamic boundary conditions. From the viewpoint of the discrete variational derivative method we propose…

Numerical Analysis · Mathematics 2021-12-14 Akihiro Umeda , Yuta Wakasugi , Shuji Yoshikawa

Von Neumann established that discretized algebraic equations must be consistent with the differential equations, and must be stable in order to obtain convergent numerical solutions for the given differential equations. The "stability" is…

Numerical Analysis · Mathematics 2012-05-31 Lun-Shin Yao

We investigate differentially private estimators for individual parameters within larger parametric models. While generic private estimators exist, the estimators we provide repose on new local notions of estimand stability, and these…

Machine Learning · Computer Science 2025-03-24 Hilal Asi , John C. Duchi , Kunal Talwar

For a parameter-unknown linear descriptor system, this paper proposes data-driven methods to testify the system's type and controllability and then to stabilize it. First, a data-based condition is developed to identify whether this unknown…

Systems and Control · Electrical Eng. & Systems 2022-01-03 Jiabao He , Xuan Zhang , Feng Xu , Junbo Tan , Xueqian Wang
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