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A normalizable complex distribution $P(x)$ on a manifold $\mathcal{M}$ can be regarded as a complex weight, thereby allowing to define expectation values of observables $A(x)$ defined on $\mathcal{M}$. Straightforward importance sampling,…

High Energy Physics - Lattice · Physics 2018-11-27 L. L. Salcedo

In our joint papers [FL1-FL2] we revive quaternionic analysis and show deep relations between quaternionic analysis, representation theory and four-dimensional physics. As a guiding principle we use representation theory of various real…

Mathematical Physics · Physics 2007-12-04 Matvei Libine

Filliman duality expresses (the characteristic measure of) a convex polytope P containing the origin as an alternating sum of simplices that share supporting hyperplanes with P. The terms in the alternating sum are given by a triangulation…

Metric Geometry · Mathematics 2019-09-16 Greg Kuperberg

We consider a class of $0$-$1$ polynomial programming termed multiple choice polynomial programming (MCPP) where the constraint requires exact one component per subset of the partition to be $1$ after all the entries are partitioned.…

Optimization and Control · Mathematics 2024-06-21 Sihong Shao , Yishan Wu

Trigonometric and hyperbolic B-splines can be computed via recurrence relations analogous to the classical polynomial B-splines. However, in their original formulation, these two types of B-splines do not form a partition of unity and…

Numerical Analysis · Mathematics 2025-12-16 Hendrik Speleers

We introduce and study a family of polytopes which can be seen as a generalization of the permutahedron of type $B_d$. We highlight connections with the largest possible diameter of the convex hull of a set of points in dimension $d$ whose…

Optimization and Control · Mathematics 2017-02-07 Antoine Deza , George Manoussakis , Shmuel Onn

The status of analytical evaluation of double and triple box diagrams is characterized. The method of Mellin-Barnes representation as a tool to evaluate master integrals in these problems is advocated. New MB representations for massive…

High Energy Physics - Phenomenology · Physics 2009-11-10 V. A. Smirnov

The Minkowski operators (addition and substraction of sets in vectorial spaces) has been extensively used for Computer Graphics and Image Processing to represent complex shapes. Here we propose to apply those mathematical concepts to extend…

Materials Science · Physics 2013-05-29 Sergio-Andres Galindo-Torres , Fernando Alonso-Marroquin

Any homogeneous polynomial $P(x, y, z)$ of degree $d$, being restricted to a unit sphere $S^2$, admits essentially a unique representation of the form $\lambda + \sum_{k = 1}^d [\prod_{j = 1}^k L_{kj}]$, where $L_{kj}$'s are linear forms in…

Complex Variables · Mathematics 2007-05-23 Gabriel Katz

This paper is about a small combinatorial trick, which is well known, but has no name. Let G be a permutation group acting on a vector space M. There is a natural way to assign a cosimplicial space to these data. We call the resulting…

Quantum Algebra · Mathematics 2011-03-29 Pavol Severa , Thomas Willwacher

In this paper, we endow the space of continuous translation invariant valuation on convex sets generated by mixed volumes coupled with a suitable Radon measure on tuples of convex bodies with two appropriate norms. This enables us to…

Differential Geometry · Mathematics 2019-03-26 Nguyen-Bac Dang , Jian Xiao

A sum-of-squares is a polynomial that can be expressed as a sum of squares of other polynomials. Determining if a sum-of-squares decomposition exists for a given polynomial is equivalent to a linear matrix inequality feasibility problem.…

Optimization and Control · Mathematics 2013-03-07 Peter Seiler , Qian Zheng , Gary Balas

Multivariate distributions are fundamental to modeling. Discrete copulas can be used to construct diverse multivariate joint distributions over random variables from estimated univariate marginals. The space of discrete copulas admits a…

Statistics Theory · Mathematics 2018-05-31 Elisa Perrone , Liam Solus , Caroline Uhler

In this paper we construct a geometric analogue of the Weil representation over a finite field. Our construction is principally invariant, not choosing any specific realization. This eliminates most of the unpleasant formulas that appear in…

Representation Theory · Mathematics 2007-10-18 Shamgar Gurevich , Ronny Hadani

To determine the relative position of any two surfaces in a system, one approach is to useoperations (Minkowski sum and intersection) on sets of constraints. These constraints aremade compliant with half-spaces of R^n where each set of…

Computational Geometry · Computer Science 2015-09-30 Lazhar Homri , Denis Teissandier , Alex Ballu

Starting from the parametric representation of a Feynman diagram, we obtain it's well defined value in dimensional regularisation by changing the integrals over parameters into contour integrals. That way we eventually arrive at a…

High Energy Physics - Phenomenology · Physics 2007-05-23 K. Knecht , H. Verschelde

This paper presents methods for using zonotopes and constrained zonotopes to improve the practicality of a wide variety of set-based operations commonly used in control theory. The proposed methods extend the use of constrained zonotopes to…

Systems and Control · Electrical Eng. & Systems 2020-09-15 Vignesh Raghuraman , Justin P. Koeln

Volume polynomials measure the growth of Minkowski sums of convex bodies and of tensor powers of positive line bundles on projective varieties. We show that Aluffi's covolume polynomials are precisely the polynomial differential operators…

Algebraic Geometry · Mathematics 2025-06-30 Lukas Grund , June Huh , Mateusz Michałek , Hendrik Süss , Botong Wang

For functions defined on C^n or (R_+)^n we construct a dequantization transform, which is closely related to the Maslov dequantization. The subdifferential at the origin of a dequantized polynomial coincides with its Newton polytope. For…

Mathematical Physics · Physics 2007-05-23 G. L. Litvinov , G. B. Shpiz

Convolution is an efficient technique to obtain abstract feature representations using hierarchical layers in deep networks. Although performing convolution in Euclidean geometries is fairly straightforward, its extension to other…

Machine Learning · Computer Science 2019-01-04 Sameera Ramasinghe , Salman Khan , Nick Barnes
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