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We construct some new Integrable Systems (IS) both classical and quantum associated with elliptic algebras. Our constructions are partly based on the algebraic integrability mechanism given by the existence of commuting families in skew…

Quantum Algebra · Mathematics 2007-05-23 A. Odesskii , V. Rubtsov

We give the necessary and sufficient (local) conditions for a metric tensor to be the Kerr solution. These conditions exclusively involve explicit concomitants of the Riemann tensor.

General Relativity and Quantum Cosmology · Physics 2009-03-24 Joan Josep Ferrando , Juan Antonio Sáez

We construct a family of vector fields that generate local symmetries in the solution space of low frequency massless field perturbations in the general Kerr geometry. This yields a one-parameter family of SL(2,R)x SL(2,R) algebras. We…

High Energy Physics - Theory · Physics 2015-06-03 David A. Lowe , Antun Skanata

The E. Cartan's equations defining "simple" spinors (renamed "pure" by C. Chevalley) are interpreted as equations of motions for fermion multiplets in momentum spaces which, in a constructive approach based bilinearly on those spinors,…

High Energy Physics - Theory · Physics 2008-11-26 P. Budinich

We develop a linear theory of discrete complex analysis on general quad-graphs, continuing and extending previous work of Duffin, Mercat, Kenyon, Chelkak and Smirnov on discrete complex analysis on rhombic quad-graphs. Our approach based on…

Complex Variables · Mathematics 2017-03-14 Alexander I. Bobenko , Felix Günther

We develop a theory of reduction for generalized Kahler and hyper-Kahler structures which uses the generalized Riemannian metric in an essential way, and which is not described with reference solely to a single generalized complex…

Differential Geometry · Mathematics 2023-05-26 Henrique Bursztyn , Gil R. Cavalcanti , Marco Gualtieri

Understanding the metric structure of permutation families is fundamental to combinatorics and has applications in social choice theory, bioinformatics, and coding theory. We study permutation families defined by restriction…

Discrete Mathematics · Computer Science 2025-07-16 Danylo Tymoshenko , Leonhard Nagel

The geometric conjecture developed by the authors in [1,2,3,4] applies to the smooth dual Irr(G) of any reductive p-adic group G. It predicts a definite geometric structure - the structure of an extended quotient - for each component in the…

Representation Theory · Mathematics 2011-11-01 Anne-Marie Aubert , Paul Baum , Roger Plymen

The self-dual double copy is further explored. In previous work, it has been shown that hyper-Hermitian manifolds also have associated the self-dual gauge theories via Kerr-Schild double copy. The self-dual double copy is generalized in the…

High Energy Physics - Theory · Physics 2024-11-22 E. Chacón , H. García-Compeán , G. Robles

For an undirected graph G=(V,E), a vertex x \in V separates vertices u and v (where u,v \in V, u \neq v) if their distances to x are not equal. Given an integer parameter k \geq 1, a set of vertices L \subseteq V is a feasible solution if…

Data Structures and Algorithms · Computer Science 2014-10-17 Ron Adar , Leah Epstein

The paper introduces the class of O-metric spaces, a novel generalization of metric-type spaces, classifying almost all possible metric types into upward and downward O-metrics. We list some topologies arising from O-metrics and discuss…

General Mathematics · Mathematics 2025-04-29 Hallowed O. Olaoluwa , Aminat O. Ige , Johnson O. Olaleru

We introduce the framework of discrete holomorphic functions on t-embeddings of weighted bipartite planar graphs; t-embeddings also appeared under the name Coulomb gauges in a recent paper arXiv:1810.05616. We argue that this framework is…

Probability · Mathematics 2022-11-08 Dmitry Chelkak , Benoît Laslier , Marianna Russkikh

A vertex set $U \subseteq V$ of an undirected graph $G=(V,E)$ is a $\textit{resolving set}$ for $G$, if for every two distinct vertices $u,v \in V$ there is a vertex $w \in U$ such that the distances between $u$ and $w$ and the distance…

Computational Complexity · Computer Science 2018-06-28 Duygu Vietz , Stefan Hoffmann , Egon Wanke

Learning a distance metric from the given training samples plays a crucial role in many machine learning tasks, and various models and optimization algorithms have been proposed in the past decade. In this paper, we generalize several…

Machine Learning · Computer Science 2013-09-24 Faqiang Wang , Wangmeng Zuo , Lei Zhang , Deyu Meng , David Zhang

In this study, we introduce the notion of $PL_\delta$-homeomorphisms of $\mathbb{R}^n$. Furthermore, we provide a combinatorial criterion reliant on the vertices and edges of simplicial structures, to determine whether a piecewise-linear…

Geometric Topology · Mathematics 2023-12-27 Swarup Bhowmik , Prateep Chakraborty

A few physicists have recently constructed the generating compatibility conditions (CC) of the Killing operator for the Minkowski (M) , Schwarzschild (S) and Kerr (K) metrics. They discovered second order CC, well known for M, but also…

General Physics · Physics 2020-12-02 J. -F. Pommaret

This thesis studies general relativity (GR) using chiral formulations, which take advantage of the decomposition of the four-dimensional Lorentz group into self-dual and anti-self-dual sectors. Within this framework, GR can be expressed…

General Relativity and Quantum Cosmology · Physics 2026-04-23 Adam Shaw

In the representation theory of reductive $p$-adic groups $G$, the issue of reducibility of induced representations is an issue of great intricacy. It is our contention, expressed as a conjecture in [3], that there exists a simple geometric…

Representation Theory · Mathematics 2010-08-05 Anne-Marie Aubert , Paul Baum , Roger Plymen

We show how the modular symmetries that have been found to be consistent with most available scaling data from quantum Hall systems, derive from a rigid family of algebraic curves of the elliptic type. The complicated special functions…

Strongly Correlated Electrons · Physics 2012-07-20 J. Nissinen , C. A. Lütken

We present a geometric formulation of the Multiple Kernel Learning (MKL) problem. To do so, we reinterpret the problem of learning kernel weights as searching for a kernel that maximizes the minimum (kernel) distance between two convex…

Machine Learning · Computer Science 2014-03-18 John Moeller , Parasaran Raman , Avishek Saha , Suresh Venkatasubramanian