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Related papers: Kronecker differences

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We introduce and extend the outer product and contractive product of tensors and matrices, and present some identities in terms of these products. We offer tensor expressions of derivatives of tensors, focus on the tensor forms of…

Classical Analysis and ODEs · Mathematics 2025-09-22 Yiran Xu , Guangbin Wang , Changqing Xu

We relate the $m$-truncated Kronecker products of symmetric functions to the semi-invariant rings of a family of quiver representations. We find cluster algebra structures for these semi-invariant rings when $m=2$. Each {\sf g}-vector cone…

Representation Theory · Mathematics 2015-08-26 Jiarui Fei

New bounds are derived for the eigenvalues of sums of Kronecker products of square matrices by relating the corresponding matrix expressions to the covariance structure of suitable bi-linear stochastic systems in discrete and continuous…

Probability · Mathematics 2014-04-18 Sergey V Lototsky

The group $SL(2,\mathbb{C})$ of all complex $2\times 2$ matrices with determinant one is closely related to the group $\boldsymbol{\mathcal{L}}_{+}^\uparrow$ of real $4\times 4$ matrices representing the restricted Lorentz transformations.…

Classical Physics · Physics 2022-02-18 Jonas Larsson , Karl Larsson

We propose the tensor Kronecker product singular value decomposition~(TKPSVD) that decomposes a real $k$-way tensor $\mathcal{A}$ into a linear combination of tensor Kronecker products with an arbitrary number of $d$ factors $\mathcal{A} =…

Numerical Analysis · Mathematics 2016-03-09 Kim Batselier , Ngai Wong

The Kronecker coefficients are the structure constants for the restriction of irreducible representations of the general linear group $GL(n m)$ into irreducibles for the subgroup $GL(n)\times GL(m)$. In this work we study the…

Representation Theory · Mathematics 2025-09-09 Marni Mishna , Mercedes Rosas , Sheila Sundaram

Tensor operations play an essential role in various fields of science and engineering, including multiway data analysis. In this study, we establish a few basic properties of the range and null space of a tensor using block circulant…

Numerical Analysis · Mathematics 2023-11-30 Ratikanta Behera , Jajati Keshari Sahoo , Yimin Wei

In this paper, we give a combinatorial rule to calculate the decomposition of the tensor product (Kronecker product) of two irreducible complex representations of the symmetric group ${\mathfrak S}_n$, when one of the representations…

Representation Theory · Mathematics 2015-07-09 Takahiro Hayashi

For polynomial representations of $GL_n$ of a fixed degree, H. Krause defined a new internal tensor product using the language of strict polynomial functors. We show that over an arbitrary commutative base ring $k$, the Schur functor…

Representation Theory · Mathematics 2016-05-06 Upendra Kulkarni , Shraddha Srivastava , K V Subrahmanyam

We present a study of three families of Kronecker coefficients, which we describe in terms of reduced Kronecker coefficients. This study is grounded on the generating function of the coefficients, proved by a bijection between two…

Combinatorics · Mathematics 2016-04-05 L. Colmenarejo

We study the commutation relations and normal ordering between families of operators on symmetric functions. These operators can be naturally defined by the operations of multiplication, Kronecker product, and their adjoints. As…

Combinatorics · Mathematics 2020-04-14 Emmanuel Briand , Peter R. W. McNamara , Rosa Orellana , Mercedes Rosas

Kruskal's theorem states that a sum of product tensors constitutes a unique tensor rank decomposition if the so-called k-ranks of the product tensors are large. We prove a "splitting theorem" for sets of product tensors, in which the k-rank…

Combinatorics · Mathematics 2023-05-09 Benjamin Lovitz , Fedor Petrov

Our main result is an elementary derivation of the spectral decomposition of hypermatrices generated by arbitrary combinations of Kronecker products and direct sums of cubic side length 2

Spectral Theory · Mathematics 2016-08-09 Yuval Filmus , Edinah K. Gnang

The Kronecker product is a key algorithm and is ubiquitous across the physical, biological, and computation social sciences. Thus considerations of optimal implementation are important. The need to have high performance and computational…

Mathematical Software · Computer Science 2009-07-07 Lenore M. Mullin , James E. Raynolds

We present combinatorial operators for the expansion of the Kronecker product of irreducible representations of the symmetric group. These combinatorial operators are defined in the ring of symmetric functions and act on the Schur functions…

Representation Theory · Mathematics 2016-09-07 Alain Goupil , Cedric Chauve

Using an algorithm for computing the symmetric function Kronecker product of D-finite symmetric functions we find some new Kronecker product identities. The identities give closed form formulas for trace-like values of the Kronecker…

Combinatorics · Mathematics 2011-02-11 Marni Mishna

While every matrix admits a singular value decomposition, in which the terms are pairwise orthogonal in a strong sense, higher-order tensors typically do not admit such an orthogonal decomposition. Those that do have attracted attention…

Algebraic Geometry · Mathematics 2015-12-29 Ada Boralevi , Jan Draisma , Emil Horobet , Elina Robeva

This paper gives an overview of notations used in multiway array processing. We redefine the vectorization and matricization operators to comply with some properties of the Kronecker product. The tensor product and Kronecker product are…

Numerical Analysis · Computer Science 2016-02-04 Jeremy E. Cohen

We investigate several properties of Kronecker (direct, tensor) products of graphs that are planar and $3$-connected (polyhedral, $3$-polytopal). This class of graphs was recently characterised and constructed by the second author [15]. Our…

Combinatorics · Mathematics 2024-11-21 Ruben De March , Riccardo W. Maffucci

A matrix completion problem is to recover the missing entries in a partially observed matrix. Most of the existing matrix completion methods assume a low rank structure of the underlying complete matrix. In this paper, we introduce an…

Machine Learning · Statistics 2020-11-16 Chencheng Cai , Rong Chen , Han Xiao