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I define the Standard Supersymmetric Model (SSM) as the minimal supersymmetric extension ofthe Standard Model with gauge coupling unification and universal soft supersymmetry breaking at the unification scale. This well-defined model has a…

High Energy Physics - Phenomenology · Physics 2007-05-23 S. Kelley

We introduce a new technique for solving uni-parametric versions of linear programs, convex quadratic programs, and linear complementarity problems in which a single parameter is permitted to be present in any of the input data. We…

Optimization and Control · Mathematics 2022-03-25 Nathan Adelgren

Given that the existing parametric functional forms for the Lorenz curve do not fit all possible size distributions, a universal parametric functional form is introduced. By using the empirical data from different scientific disciplines and…

Data Analysis, Statistics and Probability · Physics 2023-04-28 Thitithep Sitthiyot , Kanyarat Holasut

We develop a constructive process which determines all extreme points of the unit ball of the space of $m$--linear forms, $m\geq1.$ Our method provides a full characterization of the geometry of that space through finitely many elementary…

Functional Analysis · Mathematics 2017-08-02 W. V. Cavalcante , D. M. Pellegrino , E. V. Teixeira

Dimension-varying linear systems are investigated. First, a dimension-free state space is proposed. A cross dimensional distance is constructed to glue vectors of different dimensions together to form a cross-dimensional topological space.…

Dynamical Systems · Mathematics 2019-04-17 Daizhan Cheng , Zhenhui Xu , Tielong Shen

In the overview, a generic mathematical object (mapping) is introduced, and its relation to model physics parameterization is explained. Machine learning (ML) tools that can be used to emulate and/or approximate mappings are introduced.…

Atmospheric and Oceanic Physics · Physics 2022-06-22 Vladimir Krasnopolsky , Aleksei A. Belochitski

This work describes numerical methods that are useful in many areas: examples include statistical modelling (bioinformatics, computational biology), theoretical physics, and even pure mathematics. The methods are primarily useful for the…

Numerical Analysis · Mathematics 2025-10-20 U. D. Jentschura , S. V. Aksenov , P. J. Mohr , M. A. Savageau , G. Soff

In this paper, we mainly introduce the notion of an open uniform (G) at non-isolated points, and show that a space $X$ has an open uniform (G) at non-isolated points if and only if $X$ is the open boundary-compact image of metric spaces.…

General Topology · Mathematics 2011-06-22 Fucai Lin , Shou Lin

Symmetries concerning the ordinary coordinate spacetime and internal spacetime are discussed. A possible unification model of electroweak, strong and gravitational interactions is briefly described.

High Energy Physics - Phenomenology · Physics 2007-05-23 Yue-Liang Wu

This paper frames a general prediction system as an observer traveling around a continuous space, measuring values at some locations, and predicting them at others. The observer is completely agnostic about any particular task being solved;…

Neural and Evolutionary Computing · Computer Science 2021-03-24 Elliot Meyerson , Risto Miikkulainen

In this paper we introduce the concept of the rectangular metric like spaces, along with its topology and we prove some fixed point theorems under different contraction principles. We introduce the concept of modified metric-like space as…

General Topology · Mathematics 2018-03-16 Nabil Mlaiki , Kamal Abudayeh , Thabet Abdeljawad , Muhib Abuloha

Topic models are a popular tool for clustering and analyzing textual data. They allow texts to be classified on the basis of their affiliation to the previously calculated topics. Despite their widespread use in research and application, an…

Artificial Intelligence · Computer Science 2024-03-07 Johannes Hirth , Tom Hanika

How to distribute a set of points uniformly on a spherical surface is a very old problem that still lacks a definite answer. In this work, we introduce a physical measure of uniformity based on the distribution of distances between points,…

Statistical Mechanics · Physics 2025-01-09 Luca Maria Del Bono , Flavio Nicoletti , Federico Ricci-Tersenghi

We investigate metric projections and distance functions referring to convex bodies in finite-dimensional normed spaces. For this purpose we identify the vector space with its dual space by using, instead of the usual identification via the…

Metric Geometry · Mathematics 2019-08-26 Vitor Balestro , Horst Martini , Ralph Teixeira

The General Curve Lemma is a tool of Infinite-Dimensional Analysis, which enables refined studies of differentiability properties of mappings between real locally convex spaces. In this article, we generalize the General Curve Lemma in two…

Functional Analysis · Mathematics 2007-05-23 Helge Glockner

The purpose of this work is to demonstrate how an arbitrarily chosen background of the Universe can be made a solution of a simple geometric sigma model. Geometric sigma models are purely geometric theories in which spacetime coordinates…

General Relativity and Quantum Cosmology · Physics 2017-04-03 Milovan Vasilić

We test a recently proposed model of commuting networks on 80 case studies from different regions of the world (Europe and United-States) and with geographic units of different sizes (municipality, county, region). The model takes as input…

Statistics Theory · Mathematics 2018-12-27 Maxime Lenormand , Sylvie Huet , Floriana Gargiulo , Guillaume Deffuant

``Can number and geometric spaces be reconstructed from their symmetries?'' This question, which is at the heart of anabelian geometry, a theory built on the collaborative efforts of an international community in many variants and with the…

Number Theory · Mathematics 2025-08-05 Benjamin Collas , Takahiro Murotani , Naganori Yamaguchi

We solve the problem of best approximation by partial isometries of given rank to an arbitrary rectangular matrix, when the distance is measured in any unitarily invariant norm. In the case where the norm is strictly convex, we parametrize…

Functional Analysis · Mathematics 2016-11-08 Jorge Antezana , Eduardo Chiumiento

In this work, we propose to study the global geometrical properties of generative models. We introduce a new Riemannian metric to assess the similarity between any two data points. Importantly, our metric is agnostic to the parametrization…

Machine Learning · Computer Science 2024-07-17 Beomsu Kim , Michael Puthawala , Jong Chul Ye , Emanuele Sansone