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The automorphism groups of various linear codes are extensively studied yielding insights into the respective code structure. This knowledge is used in, e.g., theoretical analysis and in improving decoding performance, motivating the…

Information Theory · Computer Science 2024-04-16 Jonathan Mandelbaum , Sisi Miao , Holger Jäkel , Laurent Schmalen

This is the second in a series of papers on rank decompositions of the matrix multiplication tensor. We present new rank $23$ decompositions for the $3\times 3$ matrix multiplication tensor $M_{\langle 3\rangle}$. All our decompositions…

Computational Complexity · Computer Science 2018-01-04 Grey Ballard , Christian Ikenmeyer , J. M. Landsberg , Nick Ryder

Just as the Hamming weight spectrum of a linear block code sheds light on the performance of a maximum likelihood decoder, the pseudo-weight spectrum provides insight into the performance of a linear programming decoder. Using properties of…

Information Theory · Computer Science 2016-11-17 Panu Chaichanavong , Paul H. Siegel

The weighted-Hamming metric generalizes the Hamming metric by assigning different weights to blocks of coordinates. It is well-suited for applications such as coding over independent parallel channels, each of which has a different level of…

Information Theory · Computer Science 2026-01-21 Sebastian Bitzer , Alberto Ravagnani , Violetta Weger

Duadic group algebra codes are a generalization of quadratic residue codes. This paper settles an open problem raised by Zhu concerning the existence of duadic group algebra codes. These codes can be used to construct degenerate quantum…

Information Theory · Computer Science 2007-07-13 Salah A. Aly , Andreas Klappenecker , Pradeep Kiran Sarvepalli

Benders' decomposition (BD) is a framework for solving optimization problems by removing some variables and modeling their contribution to the original problem via so-called Benders cuts. While many advanced optimization techniques can be…

Optimization and Control · Mathematics 2025-12-18 Christopher Hojny , Cédric Roy

A packing of partial difference sets is a collection of disjoint partial difference sets in a finite group $G$. This configuration has received considerable attention in design theory, finite geometry, coding theory, and graph theory over…

Combinatorics · Mathematics 2021-09-22 Jonathan Jedwab , Shuxing Li

Many objects, especially these made by humans, are symmetric, e.g. cars and aeroplanes. This paper addresses the estimation of 3D structures of symmetric objects from multiple images of the same object category, e.g. different cars, seen…

Computer Vision and Pattern Recognition · Computer Science 2016-09-23 Yuan Gao , Alan Yuille

In this paper we study numerical semigroups generated by three elements. We give a characterization of pseudo-symmetric numerical semigroups. Also, we will give a simple algorithm to get all the pseudo-symmetric numerical semigroups with…

Group Theory · Mathematics 2011-04-20 Hirokatsu Nari , Takahiro Numata , Kei-ichi Watanabe

In this paper we give some basic results on blocking sets on minimum size for a finite chain geometry.

Combinatorics · Mathematics 2013-04-05 Andrea Blunck , Hans Havlicek , Corrado Zanella

A method for the deformation quantization of coadjoint orbits of semisimple Lie groups is proposed. It is based on the algebraic structure of the orbit. Its relation to geometric quantization and differentiable deformations is explored.

Quantum Algebra · Mathematics 2009-10-31 M. A. Lledó

A set of proper subgroups is a covering for a group if its union is the whole group. The minimal number of subgroups needed to cover $G$ is called the covering number of $G$, denoted by $\sigma(G)$. Determining $\sigma(G)$ is an open…

Group Theory · Mathematics 2014-09-09 Luise-Charlotte Kappe , Daniela Nikolova-Popova , Eric Swartz

We consider the decoding of rank metric codes assuming the error matrix is symmetric. We prove two results. First, for rates $<1/2$ there exists a broad family of rank metric codes for which any symmetric error pattern, even of maximal rank…

Information Theory · Computer Science 2023-03-23 Alain Couvreur

The aim of this paper is to study a Lie conformal algebra of Block type. In this paper, conformal derivation, conformal module of rank 1 and low-dimensional comohology of the Lie conformal algebra of Block type are studied. Also, the vertex…

Rings and Algebras · Mathematics 2016-01-28 Lamei Yuan

A symmetric tensor of small rank decomposes into a configuration of only few vectors. We study the variety of tensors for which this configuration is a unit norm tight frame.

Algebraic Geometry · Mathematics 2015-11-18 Luke Oeding , Elina Robeva , Bernd Sturmfels

A block decomposition method is proposed for minimizing a (possibly non-convex) continuously differentiable function subject to one linear equality constraint and simple bounds on the variables. The proposed method iteratively selects a…

Optimization and Control · Mathematics 2019-03-06 Andrea Cristofari

If supersymmetric particles are discovered, an important problem will be to determine how supersymmetry has been broken. At collider energies, supersymmetry breaking can be parameterised by soft supersymmetry breaking parameters. Several…

High Energy Physics - Phenomenology · Physics 2012-11-07 Jamil Hetzel

The purpose of this article is to give another molecular decomposition for members of the weighted Hardy spaces.

Classical Analysis and ODEs · Mathematics 2023-05-30 Pablo Rocha

We propose a new method for computing the eigenvalue decomposition of a dense real normal matrix $A$ through the decomposition of its skew-symmetric part. The method relies on algorithms that are known to be efficiently implemented, such as…

Numerical Analysis · Mathematics 2026-03-31 Simon Mataigne , Kyle A. Gallivan

We present constructions and results about GDDs with two groups and block size 6. We study those GDDs in which each block has configuration (s,t), that is in which each block has exactly s points from one of the two groups and t points from…

Combinatorics · Mathematics 2011-05-10 Melissa Keranen , Melanie Laffin