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We apply the Noether Symmetry Approach to point-like teleparallel Lagrangians in view to derive minisuperspaces suitable for Quantum Cosmology. Adopting the Arnowitt-Deser-Misner formalism, we find out related Wave Functions of the…

General Relativity and Quantum Cosmology · Physics 2021-11-29 Francesco Bajardi , Salvatore Capozziello

Among plenty of applications, low-dimensional homogeneous spaces appear in cosmological models as both, classical factor spaces of multidimensional geometry and minisuperspaces in canonical quantization. Here a new tool to restrict their…

General Relativity and Quantum Cosmology · Physics 2016-08-31 M. Rainer

The Kalman variety of a linear subspace in a vector space consists of all endomorphism that possess an eigenvector in that subspace. We study the defining polynomials and basic geometric invariants of the Kalman variety.

Algebraic Geometry · Mathematics 2012-10-22 Giorgio Ottaviani , Bernd Sturmfels

In this article we study standard subspaces of Hilbert spaces of vector-valued holomorphic functions on tube domains E + i C^0, where C \subeq E is a pointed generating cone invariant under e^{R h} for some endomorphism h \in \End(E),…

Representation Theory · Mathematics 2021-08-18 Karl-Hermann Neeb , Bent Ørsted , Gestur Olafsson

This work studies the limitations of uniquely identifying the structure (i.e., topology) of a networked linear system from partial measurements of its nodal dynamics. In general, many networks can be consistent with these measurements; this…

Systems and Control · Electrical Eng. & Systems 2026-03-13 Jaidev Gill , Jing Shuang Li

We show that, for vector spaces in which distance measurement is performed using a gauge, the existence of best coapproximations in $1$-codimensional closed linear subspaces implies in dimensions $\geq 2$ that the gauge is a norm, and in…

Metric Geometry · Mathematics 2021-01-15 Thomas Jahn , Christian Richter

Reducing dimension redundancy to find simplifying patterns in high-dimensional datasets and complex networks has become a major endeavor in many scientific fields. However, detecting the dimensionality of their latent space is challenging…

Physics and Society · Physics 2022-11-09 Pedro Almagro , Marian Boguna , M. Angeles Serrano

In this paper we introduce the systematic study of invariant functions and equivariant mappings defined on Minkowski space under the action of the Lorentz group. We adapt some known results from the orthogonal group acting on the Euclidean…

Representation Theory · Mathematics 2025-03-27 Miram Manoel , Leandro Nery de Oliveira

Exploiting the properties of the Jost-Lehmann-Dyson representation, it is shown that in 1+2 or more spacetime dimensions, a nonempty smallest localization region can be associated with each local observable (except for the c-numbers) in a…

Mathematical Physics · Physics 2009-10-31 Bernd Kuckert

We consider the problem of inferring meaningful spatial information in networks from incomplete information on the connection intensity between the nodes of the network. We consider two spatially distributed networks: a population migration…

Social and Information Networks · Computer Science 2011-11-04 Mihai Cucuringu , Vincent D. Blondel , Paul Van Dooren

A geometric entropy is defined as the Riemannian volume of the parameter space of a statistical manifold associated with a given network. As such it can be a good candidate for measuring networks complexity. Here we investigate its ability…

Mathematical Physics · Physics 2017-12-20 D. Felice , R. Franzosi , S. Mancini , M. Pettini

Motivated by results of Henry, Pralat and Zhang (PNAS 108.21 (2011): 8605-8610), we propose a general scheme for evolving spatial networks in order to reduce their total edge lengths. We study the properties of the equilbria of two networks…

Physics and Society · Physics 2014-07-17 Chris Varghese , Rick Durrett

A refined notion of curvature for a linear system of Hermitian vector spaces, in the sense of Grothendieck, leads to the unitary classification of a large class of analytic Hilbert modules. Specifically, we study Hilbert sub-modules, for…

Spectral Theory · Mathematics 2009-09-11 Shibananda Biswas , Gadadhar Misra , Mihai Putinar

Alignment, the tendency of adjacent weight matrices in deep networks to develop compatible subspace orientations, underlies gradient flow, Neural Collapse, and representation similarity across architectures. Despite extensive empirical…

Machine Learning · Computer Science 2026-05-12 Jingchuan Xiao , Xinyi Sui , Cihan Ruan

Two new notions of equivalence for representations of a Toeplitz algebra $\mathcal{E}_n$, $n<\infty$, on a common Hilbert space are defined. Our main results apply to $C^*$-dynamics and the conjugacy of certain $*$-endomorphisms. One…

Operator Algebras · Mathematics 2016-10-10 Philip M. Gipson

Quantum corrections to holographic entanglement entropy require knowledge of the bulk quantum state. In this paper, we derive a novel dual prescription for the generalized entropy that allows us to interpret the leading quantum corrections…

High Energy Physics - Theory · Physics 2022-02-25 Cesar A. Agón , Juan F. Pedraza

Lorentz covariant generalisations of the notions of supersymmetry, superspace and self-duality are discussed. The essential idea is to extend standard constructions by allowing tangent vectors and coordinates which transform according to…

High Energy Physics - Theory · Physics 2009-10-31 Chandrashekar Devchand , Jean Nuyts

It is surprising, but an established fact that the field of Elementary Geometry referring to normed spaces (= Minkowski spaces) is not a systematically developed discipline. There are many natural notions and problems of elementary and…

Metric Geometry · Mathematics 2016-02-22 Undine Leopold , Horst Martini

We prove Bertini type theorems for the inverse image, under a proper morphism, of any Schubert variety in an homogeneous space. Using generalisations of Deligne's trick, we deduce connectedness results for the inverse image of the diagonal…

Algebraic Geometry · Mathematics 2010-05-05 Nicolas Perrin

We analytically derive the geometrical structure of the weight space in multilayer neural networks (MLN), in terms of the volumes of couplings associated to the internal representations of the training set. Focusing on the parity and…

Condensed Matter · Physics 2016-08-31 R. Monasson , R. Zecchina