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Nature features a plethora of extraordinary photonic architectures that have been optimized through natural evolution. While numerical optimization is increasingly and successfully used in photonics, it has yet to replicate any of these…

We introduce a new framework called linear algebraic number theory (LANT) that reformulates the number-theoretic problem as a regression model and solves it using matrix algebra. This framework restricts all computations to log space,…

General Mathematics · Mathematics 2017-09-19 Joram Soch

Phylogenetic models have polynomial parametrization maps. For symmetric group-based models, Matsen studied the polynomial inequalities that characterize the joint probabilities in the image of these parametrizations. We employ this…

Populations and Evolution · Quantitative Biology 2017-08-18 Dimitra Kosta , Kaie Kubjas

We suggest the method for group classification of evolution equations admitting nonlocal symmetries which are associated with a given evolution equation possessing nontrivial Lie symmetry. We apply this method to second-order evolution…

Exactly Solvable and Integrable Systems · Physics 2009-07-13 Renat Zhdanov

We provide a complete answer to the following question: what are the flavour groups and representations providing, in the symmetric limit, an approximate description of lepton masses and mixings? We assume that neutrinos masses are…

High Energy Physics - Phenomenology · Physics 2018-04-12 Y. Reyimuaji , A. Romanino

Using the fact that any linear representation of a group can be embedded into permutations, we propose a constructive description of quantum behavior that provides, in particular, a natural explanation of the appearance of complex numbers…

Quantum Physics · Physics 2016-03-24 Vladimir V. Kornyak

The Luminous Convolution Model (LCM) demonstrates that it is possible to predict the rotation curves of spiral galaxies directly from estimates of the luminous matter. We consider two frame-dependent effects on the light observed from other…

Astrophysics of Galaxies · Physics 2014-07-30 S. Cisneros , N. S. Oblath , J. A. Formaggio , R. A. Ott , D. Chester , D. J. Battaglia , A. Ashley , R. Robinson , A. Rodriguez

We consider Convolutional Neural Networks (CNNs) with 2D structured features that are symmetric in the spatial dimensions. Such networks arise in modeling pairwise relationships for a sequential recommendation problem, as well as secondary…

Machine Learning · Statistics 2022-03-07 Kehelwala Dewage Gayan Maduranga , Vasily Zadorozhnyy , Qiang Ye

We propose a simple phenomenological model of quarks-leptons mass matrices having fundamentally universal symmetry structure. These mass matrices consist of democratic and semi-democratic mass matrix terms commonly to the neutrino and the…

High Energy Physics - Phenomenology · Physics 2016-01-20 Hiroyuki Nishiura , Takeshi Fukuyama

We investigate the representation of symmetric polynomials as a sum of squares. Since this task is solved using semidefinite programming tools we explore the geometric, algebraic, and computational implications of the presence of discrete…

Commutative Algebra · Mathematics 2007-05-23 Karin Gatermann , Pablo A. Parrilo

We relate leptogenesis in a class of theories to low-energy experimental observables: quark and lepton masses and mixings. With reasonable assumptions motivated by grand unification, one can show that the CP-asymmetry parameter takes a…

High Energy Physics - Phenomenology · Physics 2009-11-07 M. S. Berger , Kim Siyeon

We discuss the possibility of flavor symmetries to explain the pattern of charged lepton and neutrino masses and mixing angles. We emphasize what are the obstacles for the generation of an almost maximal atmospheric mixing and what are the…

High Energy Physics - Phenomenology · Physics 2014-11-17 Shao-Long Chen , Michele Frigerio , Ernest Ma

An equivalence between an integro-differential operator M and an evolution operator Ln is determined. From this equivalence the fundamental solution of Ln is estimated in terms of the fundamental solution related to the third-order operator…

Materials Science · Physics 2012-03-05 M. De Angelis

Simple deformations, with a parameter $\epsilon$, of classical $R$-matrices which follow from decomposition of appropriate Lie algebras, are considered. As a result nonstandard Lax representations for some well known integrable systems are…

Exactly Solvable and Integrable Systems · Physics 2016-02-18 Blazej M. Szablikowski , Maciej Blaszak

Modulated symmetries are internal symmetries that are not invariant under spacetime symmetry actions. We propose a general way to describe the lattice translation modulated symmetries in 1+1D, including the non-invertible ones, via the…

Strongly Correlated Electrons · Physics 2025-12-09 Ching-Yu Yao

We generalize a map by S. Mason regarding two combinatorial models for key polynomials, in a way that accounts for the major index. We also define similar variants of this map, that regards alternative models for the modified Macdonald…

Combinatorics · Mathematics 2018-09-26 Per Alexandersson , Mehtaab Sawhney

The discovery of neutrino masses makes leptogenesis a very attractive scenario for explaining the puzzle of the baryon asymmetry of the Universe. We present the basic ingredients of leptogenesis, explain the predictive power of this…

High Energy Physics - Phenomenology · Physics 2007-05-23 Yosef Nir

We develop a machine learning method for mapping data originating from both Standard Model processes and various theories beyond the Standard Model into a unified representation (latent) space while conserving information about the…

High Energy Physics - Phenomenology · Physics 2025-01-23 Anna Hallin , Gregor Kasieczka , Sabine Kraml , André Lessa , Louis Moureaux , Tore von Schwartz , David Shih

Violated mirror symmetry (MS) is capable of reproducing observed qualitative properties of weak mixing for quarks and leptons. In violated MS, lepton phenomenology, that is, small neutrino masses and mixing properties different from those…

High Energy Physics - Phenomenology · Physics 2017-05-24 Igor T. Dyatlov

Treating neural network inputs and outputs as random variables, we characterize the structure of neural networks that can be used to model data that are invariant or equivariant under the action of a compact group. Much recent research has…

Machine Learning · Statistics 2020-09-18 Benjamin Bloem-Reddy , Yee Whye Teh