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We introduce a method for transforming low-order tensors into higher-order tensors and apply it to tensors defined by graphs and hypergraphs. The transformation proceeds according to a surgery-like procedure that splits vertices, creates…

Combinatorics · Mathematics 2018-06-08 Matthias Christandl , Jeroen Zuiddam

Starting from essentially commutative exponential map $E(B|I)$ for generic tensor-valued 2-forms $B$, introduced in \cite{Akh} as direct generalization of the ordinary non-commutative $P$-exponent for 1-forms with values in matrices (i.e.…

High Energy Physics - Theory · Physics 2008-11-26 E. T. Akhmedov , V. Dolotin , A. Morozov

Multipolar expansions are a foundational tool for describing basis functions in quantum mechanics, many-body polarization, and other distributions on the unit sphere. Progress on these topics is often held back by complicated and competing…

Mathematical Physics · Physics 2015-11-24 David M. Rogers

Asymptotic tensor rank is notoriously difficult to determine. Indeed, determining its value for the $2\times 2$ matrix multiplication tensor would determine the matrix multiplication exponent, a long-standing open problem. On the other…

Computational Complexity · Computer Science 2024-11-26 Matthias Christandl , Koen Hoeberechts , Harold Nieuwboer , Péter Vrana , Jeroen Zuiddam

We show that three notions of rank for matrices of multilinear forms are equivalent. This result generalizes a classical result of Flanders, corrects a minor hole in work of Fortin and Reutenauer, answers a question of Lampert on the…

Combinatorics · Mathematics 2026-03-12 Guy Moshkovitz , Daniel G. Zhu

Following the breakthrough of Croot, Lev, and Pach, Tao introduced a symmetrized version of their argument, which is now known as the slice rank method. In this paper, we introduce a more general version of the slice rank of a tensor, which…

Combinatorics · Mathematics 2023-03-13 Eric Naslund

A fully tensorial theoretical framework for hypercomplex-valued neural networks is presented. The proposed approach enables neural network architectures to operate on data defined over arbitrary finite-dimensional algebras. The central…

Machine Learning · Computer Science 2026-01-27 Agnieszka Niemczynowicz , Radosław Antoni Kycia

By a tensor we mean an element of a tensor product of vector spaces over a field. Up to a choice of bases in factors of tensor products, every tensor may be coordinatized, that is, represented as an array consisting of numbers. This note is…

Functional Analysis · Mathematics 2019-01-11 R. N. Gumerov , A. S. Sharafutdinov

We introduce various notions of rank for a symmetric tensor, namely: rank, border rank, catalecticant rank, generalized rank, scheme length, border scheme length, extension rank and smoothable rank. We analyze the stratification induced by…

Algebraic Geometry · Mathematics 2012-11-28 Alessandra Bernardi , Jérôme Brachat , Bernard Mourrain

The signature of a path is a sequence of tensors which allows to uniquely reconstruct the path. In this paper we propose a systematic study of basic properties of signature tensors, starting from their rank, symmetries and conciseness. We…

Algebraic Geometry · Mathematics 2024-07-31 Francesco Galuppi , Pierpaola Santarsiero

We generalize the representation formula from slice-domains of regularity to general Riemann slice-domains. This result allows us to extend the $*$-product of slice regular functions on axially symmetric domains to certain Riemann…

Complex Variables · Mathematics 2018-09-26 Xinyuan Dou , Guangbin Ren

In this paper, we develop a geometric framework for matrix rank-metric codes based on generator tensors and their slice spaces. To every nondegenerate matrix rank-metric code, we associate two systems, which translate metric properties of…

Combinatorics · Mathematics 2026-05-20 Gianira N. Alfarano , Martino Borello , Alessandro Neri

We develop a framework to analyse invariant decompositions of elements of tensor product spaces. Namely, we define an invariant decomposition with indices arranged on a simplicial complex, and which is explicitly invariant under a group…

Combinatorics · Mathematics 2024-03-05 Gemma De las Cuevas , Matt Hoogsteder Riera , Tim Netzer

We study $SU(n)$ symmetry breaking by rank three and rank two antisymmetric tensor fields. Using tensor analysis, we derive branching rules for the adjoint and antisymmetric tensor representations, and explain why for general $SU(n)$ one…

High Energy Physics - Theory · Physics 2015-05-22 Stephen L. Adler

Three-dimensional random tensor models are a natural generalization of the celebrated matrix models. The associated tensor graphs, or 3D maps, can be classified with respect to a particular integer or half-integer, the degree of the…

Combinatorics · Mathematics 2015-05-07 Eric Fusy , Adrian Tanasa

In this paper, we present a partial survey of the tools borrowed from tensor algebra, which have been utilized recently in Statistics and Signal Processing. It is shown why the decompositions well known in linear algebra can hardly be…

Applications · Statistics 2009-05-05 Pierre Comon

An important conjecture in additive combinatorics, number theory, and algebraic geometry posits that the partition rank and analytic rank of tensors are equal up to a constant, over any finite field. We prove the conjecture up to a…

Combinatorics · Mathematics 2024-11-04 Guy Moshkovitz , Daniel G. Zhu

We determine the tensor rank of all semifields of order 16 over $\mathbb{F}_2$ and of all semifields of order 81 over $\mathbb{F}_3$. Our results imply that some semifields of order 81 have lower multiplicative complexity than the finite…

Combinatorics · Mathematics 2021-02-04 Michel Lavrauw , John Sheekey

In this lecture note, we discuss a fundamental concept, referred to as the {\it characteristic rank}, which suggests a general framework for characterizing the basic properties of various low-dimensional models used in signal processing.…

Statistics Theory · Mathematics 2020-11-12 Alexander Shapiro , Yao Xie , Rui Zhang

We prove a lower bound on the rank of tensors constructed from families of linear maps that `expand' the dimension of every subspace. Such families, called {\em dimension expanders} have been studied for many years with several known…

Combinatorics · Mathematics 2025-12-10 Zeev Dvir