English
Related papers

Related papers: Tensor products of coherent configurations

200 papers

Under the name prime decomposition (pd), a unique decomposition of an arbitrary $N$-dimensional density matrix $\rho$ into a sum of seperable density matrices with dimensions given by the coprime factors of $N$ is introduced. For a class of…

Quantum Physics · Physics 2011-07-19 D. Ellinas , E. G. Floratos

Complicated mathematical equations involving products of tensors with permutation symmetries, frequently encountered in fields such as general relativity and quantum chemistry (e.g., equations in high-order coupled cluster theories),…

Chemical Physics · Physics 2018-12-19 Zhendong Li , Sihong Shao , Wenjian Liu

This paper discusses the problem of symmetric tensor decomposition on a given variety $X$: decomposing a symmetric tensor into the sum of tensor powers of vectors contained in $X$. In this paper, we first study geometric and algebraic…

Numerical Analysis · Mathematics 2020-03-24 Jiawang Nie , Ke Ye , Lihong Zhi

Tensors decompositions are a class of tools for analysing datasets of high dimensionality and variety in a natural manner, with the Canonical Polyadic Decomposition (CPD) being a main pillar. While the notion of CPD is closely intertwined…

Signal Processing · Electrical Eng. & Systems 2019-11-15 Giuseppe G. Calvi , Bruno Scalzo Dees , Danilo P. Mandic

We discuss extended definitions of linear and multilinear operations such as Kronecker, Hadamard, and contracted products, and establish links between them for tensor calculus. Then we introduce effective low-rank tensor approximation…

Numerical Analysis · Mathematics 2016-02-26 Namgil Lee , Andrzej Cichocki

We consider representations of tensors as sums of decomposable tensors or, equivalently, decomposition of multilinear forms into one--forms. In this short note we show that there exists a particular finite strongly orthogonal decomposition…

Numerical Analysis · Mathematics 2014-09-19 Juan Manuel Peña , Tomas Sauer

We recover the rays in the tensor product of Hilbert spaces within a larger class of so called `states of compoundness', structured as a complete lattice with the `state of separation' as its top element. At the base of the construction…

Quantum Physics · Physics 2007-05-23 Bob Coecke

The method for calculation of the canonical decomposition that approximates a tensor of high order is considered, which requires moderate computational resources. It is based on the replacement of the approximation error norm (global…

Numerical Analysis · Mathematics 2025-05-05 A. K. Alekseev , A. E. Bondarev , Y. S. Pyatakova

Tensor data with rich structural information becomes increasingly important in process modeling, monitoring, and diagnosis. Here structural information is referred to structural properties such as sparsity, smoothness, low-rank, and…

Machine Learning · Statistics 2024-10-30 Shancong Mou , Andi Wang , Chuck Zhang , Jianjun Shi

The Candecomp/Parafac (CP) decomposition of the tensor whose maximal dimension is greater than its rank is considered. We derive the upper bound of rank under which the generic uniqueness of CP decomposition is guaranteed. The bound only…

Numerical Analysis · Mathematics 2016-07-26 Tsung-Lin Lee , Yueh-Cheng Kuo

Every finite graph $G$ can be decomposed in a canonical way that displays its local connectivity-structure [DJKK26]. These decompositions are defined via a suitable more tree-like covering of $G$, whose tangle-tree structure is projected…

Combinatorics · Mathematics 2026-03-20 Raphael W. Jacobs , Paul Knappe , Jan Kurkofka

To any finite ordered subset and any finite partition of a group a set of tuples of positive integers, named as configurations, is associated that describes the group's behavior. The present paper provides an exposition of this notion and…

Group Theory · Mathematics 2018-04-24 Akram Yousofzadeh

We consider the problem of decomposing a real-valued symmetric tensor as the sum of outer products of real-valued vectors. Algebraic methods exist for computing complex-valued decompositions of symmetric tensors, but here we focus on…

Numerical Analysis · Mathematics 2018-08-23 Tamara G. Kolda

Triangular decomposition is a classic, widely used and well-developed way to represent algebraic varieties with many applications. In particular, there exist sharp degree bounds for a single triangular set in terms of intrinsic data of the…

Algebraic Geometry · Mathematics 2018-06-08 Gleb Pogudin , Agnes Szanto

It is well-known that tensor decompositions show separations, that is, that constraints on local terms (such as positivity) may entail an arbitrarily high cost in their representation. Here we show that many of these separations disappear…

Optimization and Control · Mathematics 2021-09-03 Gemma De las Cuevas , Andreas Klingler , Tim Netzer

Canonical Polyadic Decomposition (CPD) represents a third-order tensor as the minimal sum of rank-1 terms. Because of its uniqueness properties the CPD has found many concrete applications in telecommunication, array processing, machine…

Spectral Theory · Mathematics 2019-12-06 Ignat Domanov , Lieven De Lathauwer

We give a formula of the connected component decomposition of the Alexander quandle: $\mathbb{Z}[t^{\pm1}]/(f_1(t),\ldots, f_k(t))=\bigsqcup^{a-1}_{i=0}\mathrm{Orb}(i)$, where $a=\gcd (f_1(1),\ldots, f_k(1))$. We show that the connected…

Geometric Topology · Mathematics 2017-04-26 Yusuke Iijima , Tomo Murao

We introduce a notion of compatibility between constraint encoding and compositional structure. Phrased in the language of category theory, it is given by a "composable constraint encoding". We show that every composable constraint encoding…

Category Theory · Mathematics 2021-12-14 Matt Wilson , Augustin Vanrietvelde

In this paper, the canonical polyadic (CP) decomposition of tensors that corresponds to matrix multiplications is studied. Finding the rank of these tensors and computing the decompositions is a fundamental problem of algebraic complexity…

Computational Complexity · Computer Science 2021-04-13 Petr Tichavsky

It is known that the spatial product of two product systems is intrinsic. Here we extend this result by analyzing subsystems of the tensor product of product systems. A relation with cluster systems is established. In a special case, we…

Functional Analysis · Mathematics 2015-02-12 Mithun Mukherjee