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Separation of variables (SoV) is an extremely efficient and elegant technique for analysing physical systems but its application to integrable spin chains was limited until recently to the simplest su(2) cases. In this paper we continue…

High Energy Physics - Theory · Physics 2020-09-24 Nikolay Gromov , Fedor Levkovich-Maslyuk , Paul Ryan , Dmytro Volin

Functional data analysis is becoming increasingly popular to study data from real-valued random functions. Nevertheless, there is a lack of multiple testing procedures for such data. These are particularly important in factorial designs to…

Methodology · Statistics 2024-06-04 Merle Munko , Marc Ditzhaus , Markus Pauly , Łukasz Smaga

In this paper I consider the applications of several kinds of approximations of real functions to the problem of verified computation (reliable computing) of the range of implicitly defined real function $x_{n+1} = G(x_{1}, ..., x_{n}),$…

Numerical Analysis · Mathematics 2025-10-20 Nikolaj M. Glazunov

Multivariate functional data present theoretical and practical complications which are not found in univariate functional data. One of these is a situation where the component functions of multivariate functional data are positive and are…

Methodology · Statistics 2023-03-09 Cody Carroll , Hans-Georg Müller

A Koopman decomposition is a powerful method of analysis for fluid flows leading to an apparently linear description of nonlinear dynamics in which the flow is expressed as a superposition of fixed spatial structures with exponential time…

Fluid Dynamics · Physics 2019-09-25 Jacob Page , Rich R. Kerswell

Decoupling is a powerful modeling paradigm for representing multivariate functions as compositions of linear transformations and univariate nonlinear functions. A single-layer decoupling can be viewed as a fully connected neural network…

Machine Learning · Computer Science 2026-05-20 Joppe De Jonghe , Van Tien Pham , Mariya Ishteva

This note examines linear combinations of multi-indexed sequences and derives the multivariate generating function of such a linear combination in terms of the original sequence's m.g.f. Applications include finding distributions and…

Combinatorics · Mathematics 2012-09-18 Michael C. Burkhart

Let $K[x]$ be a polynomial algebra in a variable $x$ over a commutative $\Q$-algebra $K$, and $\G'$ be the monoid of $K$-algebra monomorphisms of $K[x]$ of the type $\s : x\mapsto x+\l_2x^2+... +\l_nx^n$, $\l_i\in K$, $\l_n$ is a unit of…

Rings and Algebras · Mathematics 2007-05-23 V. V. Bavula

Multiway data analysis aims to uncover patterns in data structured as multi-indexed arrays, with multiway covariance playing a crucial role in many applications. However, the high dimensionality of multiway covariance presents significant…

Statistics Theory · Mathematics 2026-03-19 Dogyoon Song , Alfred O. Hero

Bivariate matrix functions provide a unified framework for various tasks in numerical linear algebra, including the solution of linear matrix equations and the application of the Fr\'echet derivative. In this work, we propose a novel…

Numerical Analysis · Mathematics 2018-02-22 Daniel Kressner

Necessary and sufficient conditions are obtained under which the numerator of the partial derivative of a rational function holomorphic in open upper poly-halfplane is the sum of squares of polynomials.

Complex Variables · Mathematics 2021-07-01 M. F. Bessmertnyi

We consider Boolean functions f:{-1,1}^n->{-1,1} that are close to a sum of independent functions on mutually exclusive subsets of the variables. We prove that any such function is close to just a single function on a single subset. We also…

Probability · Mathematics 2015-12-31 Aviad Rubinstein , Muli Safra

Spatio-temporal covariances are important for describing the spatio-temporal variability of underlying random processes in geostatistical data. For second-order stationary processes, there exist subclasses of covariance functions that…

Applications · Statistics 2017-05-05 Huang Huang , Ying Sun

We discuss some aspects of approximating functions on high-dimensional data sets with additive functions or ANOVA decompositions, that is, sums of functions depending on fewer variables each. It is seen that under appropriate smoothness…

Data Structures and Algorithms · Computer Science 2009-11-17 Markus Hegland , Vladimir Pestov

In using the spectral theorem of many-body Green's function theory in order to relate correlations to commutator Green's functions, it is necessary in the standard procedure to consider the anti-commutator Green's functions as well whenever…

Statistical Mechanics · Physics 2009-11-10 P. Fröbrich , P. J. Kuntz

The multitime probability distributions obtained by repeatedly probing a quantum system via the measurement of an observable generally violate Kolmogorov's consistency property. Therefore, one cannot interpret such distributions as the…

New density functional theory approach based on a complete active space self-consistent field (CASSCF) reference function in Extended Koopmans' approximation is discussed. Recently, the number of generalizations of density functional theory…

Chemical Physics · Physics 2018-02-15 Sergey Gusarov , Yurii Dmitriev

We consider Knizhnik-Zamolodchikov system of linear differential equations. The coefficients of this system are rational functions. We prove that under some conditions the solution of KZ system is rational too. This assertion confirms…

Mathematical Physics · Physics 2007-05-23 Lev Sakhnovich

Novikov-Furutsu (NF) theorem is a well-known mathematical tool, used in stochastic dynamics for correlation splitting, that is, for evaluating the mean value of the product of a random functional with a Gaussian argument multiplied by the…

Mathematical Physics · Physics 2021-06-04 Gerassimos A. Athanassoulis , Konstantinos I. Mamis

Functionals (i.e. functions of functions) are widely used in quantum field theory and solid-state physics. In this paper, functionals are given a rigorous mathematical framework and their main properties are described. The choice of the…

Mathematical Physics · Physics 2018-03-14 Christian Brouder , Nguyen Viet Dang , Camille Laurent-Gengoux , Kasia Rejzner
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