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Related papers: Involution symmetries and the PMNS matrix

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This dissertation presents a multifaceted look into the structural decomposition of permutation classes. The theory of permutation patterns is a rich and varied field, and is a prime example of how an accessible and intuitive definition…

Combinatorics · Mathematics 2014-10-13 Cheyne Homberger

We describe a framework for random pairwise comparisons matrices, inspired by selected constructions releted to the so called inconsistency reduction of pairwise comparisons (PC) matrices. In to build up structures on random pairwise…

Statistics Theory · Mathematics 2023-12-04 Jean-Pierre Magnot

We introduce an ansatz of the PMNS matrix that consists of specific types of transformations. Bi-maximal mixing is taken for the neutrino masses, while a single-angle rotation in the 1-2 block is taken for the charged lepton masses.…

High Energy Physics - Phenomenology · Physics 2012-08-14 Kim Siyeon

A candidate for the simple empirical neutrino mass formula is found, predicting the mass proportion m_1:m_2:m_3 = 0:4:24 and so, the mass ratio Delta m^2_{32}/Delta m^2_{21} = 35 not inconsistent with its experimental estimate. It involves…

High Energy Physics - Phenomenology · Physics 2011-03-17 Wojciech Krolikowski

It was recently argued that f(T) gravity could inherit "remnant symmetry" from the full Lorentz group, despite the fact that the theory is not locally Lorentz invariant. Confusion has arisen regarding the implication of this result for the…

General Relativity and Quantum Cosmology · Physics 2015-03-11 Pisin Chen , Keisuke Izumi , James M. Nester , Yen Chin Ong

Following a polynomial approach, many robust fixed-order controller design problems can be formulated as optimization problems whose set of feasible solutions is modelled by parametrized polynomial matrix inequalities (PMI). These…

Optimization and Control · Mathematics 2012-06-01 Didier Henrion , Jean Bernard Lasserre

Recently, it has been proven that evolutionary algorithms produce good results for a wide range of combinatorial optimization problems. Some of the considered problems are tackled by evolutionary algorithms that use a representation which…

Neural and Evolutionary Computing · Computer Science 2013-01-18 Benjamin Doerr , Anton Eremeev , Frank Neumann , Madeleine Theile , Christian Thyssen

In this paper, we aim at introducing a new machine learning model, namely reconciled polynomial machine, which can provide a unified representation of existing shallow and deep machine learning models. Reconciled polynomial machine predicts…

Machine Learning · Computer Science 2018-05-22 Jiawei Zhang , Limeng Cui , Fisher B. Gouza

We present the general form of the unitary matrices keeping invariant the Majorana neutrino mass matrix of specific texture suitable for explaining oscillation data. In the case of the Tri-bimaximal pattern with two degenerate masses we…

High Energy Physics - Phenomenology · Physics 2011-02-01 E. I. Lashin , S. Nasri , E. Malkawi , N. Chamoun

The problem of whether a metabolic idempotent of a central simple algebra with involution is contained in an invariant quaternion subalgebra is investigated. As an application, the similar problem is studied for skew-symmetric elements…

Rings and Algebras · Mathematics 2016-07-12 Amir Hossein Nokhodkar

Deep learning frameworks commonly implement convolution operators with GEMM-based algorithms. In these algorithms, convolution is implemented on top of matrix-matrix multiplication (GEMM) functions, provided by highly optimized BLAS…

Computer Vision and Pattern Recognition · Computer Science 2019-07-05 Marat Dukhan

Evolution is a dynamic process. The two classical forces of evolution are mutation and selection. Assuming small mutation rates, evolution can be predicted based solely on the fitness differences between phenotypes. Predicting an…

Populations and Evolution · Quantitative Biology 2015-03-23 Benedikt Bauer , Chaitanya S. Gokhale

Several approximate equalities among the matrix elements of CKM and PMNS imply that hidden symmetries may exist and be common for both quark and neutrino sectors. The CP phase of the CKM matrix ($\delta_{\rm CKM}$) is involved in these…

High Energy Physics - Phenomenology · Physics 2017-02-21 Hong-Wei Ke , Jia-Hui Zhou , Xue-Qian Li

We construct a neutrino mass matrix $M_{\nu}$ via a seesaw mechanism whith perturbed invariant under a cyclic permutation by introducing one parameter $\delta$ into the diagonal elements of $M_{\nu}$ with assumption that trace of the…

High Energy Physics - Phenomenology · Physics 2011-05-11 Asan Damanik

In this article, we develop a process to symmetrize the irreducible admissible representation of $GL_N(\mathbb{Q}_p)$, as a consequence we obtain a more geometric understanding of the coefficient $m(\mathbf{b}, \mathbf{a})$ appearing in the…

Representation Theory · Mathematics 2019-05-15 Taiwang Deng

We provide a complete structure theorem for involutory matrices. This yields a new approach to principal angles between subspaces and provide a series of nice formulae for these angles.

Functional Analysis · Mathematics 2026-02-24 Jean-Christophe Bourin , Eun-Young Lee

Recently we have proposed a renormalizable grand unified theory, based on the SU(5) gauge symmetry, where the neutrino masses are generated through the type I and type III seesaw mechanisms. In this letter we study the supersymmetric…

High Energy Physics - Phenomenology · Physics 2011-11-09 Pavel Fileviez Perez

Assuming that neutrinos are Majorana particles, we perform a complete classification of all possible mixing matrices which are fully determined by residual symmetries in the charged-lepton and neutrino mass matrices. The classification is…

High Energy Physics - Phenomenology · Physics 2014-09-16 Renato M. Fonseca , Walter Grimus

We apply non-invertible selection rules coming from a fusion algebra to radiative neutrino mass models where fields are labeled by the elements in the algebra. Since non-invertible selection rules only hold at tree level, radiative…

High Energy Physics - Phenomenology · Physics 2025-12-17 Tatsuo Kobayashi , Hiroshi Okada , Hajime Otsuka

Symmetries built into a neural network have appeared to be very beneficial for a wide range of tasks as it saves the data to learn them. We depart from the position that when symmetries are not built into a model a priori, it is…

Machine Learning · Computer Science 2023-02-01 Artem Moskalev , Anna Sepliarskaia , Ivan Sosnovik , Arnold Smeulders
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