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We present a novel, generally applicable Monte Carlo algorithm for the simulation of fluid systems. Geometric transformations are used to identify clusters of particles in such a manner that every cluster move is accepted, irrespective of…

Statistical Mechanics · Physics 2016-08-31 Jiwen Liu , Erik Luijten

The goal of this paper is to provide computational tools able to find a solution of a system of polynomial inequalities. The set of inequalities is reformulated as a system of polynomial equations. Three different methods, two of which…

Dynamical Systems · Mathematics 2016-03-04 Laura Menini , Corrado Possieri , Antonio Tornambè

Given a functional for a one-dimensional physical system, a classical problem is to minimize it by finding stationary solutions and then checking the positive definiteness of the second variation. Establishing the positive definiteness is,…

Classical Analysis and ODEs · Mathematics 2017-04-26 Thomas Lessinnes , Alain Goriely

Likelihood-free methods, such as approximate Bayesian computation, are powerful tools for practical inference problems with intractable likelihood functions. Markov chain Monte Carlo and sequential Monte Carlo variants of approximate…

Computation · Statistics 2019-02-26 David J. Warne , Ruth E. Baker , Matthew J. Simpson

We test the hypothesis that simulataneous linear contrasts of multiple variance components equal zero in a Gaussian variance components model via a parametric bootstrap. Applications include but are not limited to nested and crossed…

Methodology · Statistics 2026-04-29 Alex Stringer , Jeffrey Negrea

The linearization of complex ordinary differential equations is studied by extending Lie's criteria for linearizability to complex functions of complex variables. It is shown that the linearization of complex ordinary differential equations…

Classical Analysis and ODEs · Mathematics 2011-07-25 S. Ali , F. M. Mahomed , Asghar Qadir

In this paper, we present and analyze methods for solving a system of linear equations over idempotent semifields. The first method is based on the pseudo-inverse of the system matrix. We then present a specific version of Cramer's rule…

Commutative Algebra · Mathematics 2019-06-25 Fateme Olia , Shaban Ghalandarzadeh , Amirhossein Amiraslani , Sedighe Jamshidvand

We propose a random-effects approach to missing values for generalized linear mixed model (GLMM) analysis. The method converts a GLMM with missing covariates to another GLMM without missing covariates. The standard GLMM analysis tools for…

Methodology · Statistics 2026-01-01 Thuan Nguyen , Jiangshan Zhang , Jiming Jiang

Applications of variational methods are typically restricted to conservative systems. Some extensions to dissipative systems have been reported too but require ad hoc techniques such as the artificial doubling of the dynamical variables.…

Plasma Physics · Physics 2017-04-05 I. Y. Dodin , A. I. Zhmoginov , D. E. Ruiz

We give a direct proof of a cancellation formula raised in [7] on the level of differential forms. We also obtain more cancellation formulas for even dimensional Riemannian manifolds with a complex line bundle involved. Relations among…

Differential Geometry · Mathematics 2007-05-23 Fei Han , Xiaoling Huang

Two moment-matching methods for model reduction of linear switched systems (LSSs) are presented. The methods are similar to the Krylov subspace methods used for moment matching for linear systems. The more general one of the two methods, is…

Systems and Control · Computer Science 2016-11-15 Mert Bastug , Mihaly Petreczky , Rafael Wisniewski , John Leth

In many applied fields incomplete covariate vectors are commonly encountered. It is well known that this can be problematic when making inference on model parameters, but its impact on prediction performance is less understood. We develop a…

Methodology · Statistics 2020-07-14 Garritt L. Page , Fernando A. Quintana , Peter Müller

The purpose of this tutorial is to give a brief introduction to linear quantum control systems. The mathematical model of linear quantum control systems is presented first, then some fundamental control-theoretic notions such as stability,…

Quantum Physics · Physics 2022-05-26 Guofeng Zhang , Zhiyuan Dong

In this paper, we present a geometric approach for computing controlled invariant sets for hybrid control systems. While the problem is well studied in the ellipsoidal case, this family is quite conservative for constrained or switched…

Optimization and Control · Mathematics 2021-12-08 Benoît Legat , Raphaël M. Jungers

Cylindrical Algebraic Decomposition (CAD) was the first practical means for doing real quantifier elimination (QE), and is still a major method, with many improvements since Collins' original method. Nevertheless, its complexity is…

Symbolic Computation · Computer Science 2023-12-08 James H. Davenport , Zak P. Tonks , Ali K. Uncu

In this paper, we discuss the classification problem for linear time-invariant multivariable systems without control. It turns out that the observability and stability are invariant for topological equivalent systems. Abstract results…

Optimization and Control · Mathematics 2022-06-23 Jing Li , Zhixiong Zhang

The Markov chain Monte Carlo method is a versatile tool in statistical physics to evaluate multi-dimensional integrals numerically. For the method to work effectively, we must consider the following key issues: the choice of ensemble, the…

Statistical Mechanics · Physics 2014-01-07 Synge Todo , Hidemaro Suwa

We apply symmetry and invariance methods to analyse systems of difference equations. Non trivial symmetries are derived and their exact solutions obtained.

Dynamical Systems · Mathematics 2017-11-28 JJ Bashingwa , AH Kara , M Folly-Gbetoula

The normal form and zero dynamics are powerful tools useful in analysis and control of both linear and nonlinear systems. There are no simple closed form solutions to the general zero dynamics problem for nonlinear systems. A few algorithms…

Optimization and Control · Mathematics 2018-12-06 Siamak Tafazoli

An approach to amputation, the process of introducing missing values to a complete dataset, is presented. It allows to construct missingness indicators in a flexible and principled way via copulas and Bernoulli margins and to incorporate…

Applications · Statistics 2025-07-28 Marius Hofert , James Jackson , Niels Hagenbuch
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