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In this paper, we first give an expression for the Moore-Penrose inverse of the product of two tensors via the Einstein product. We then introduce a new generalized inverse of a tensor called product Moore-Penrose inverse. A necessary and…

Rings and Algebras · Mathematics 2025-08-07 Krushnachandra Panigrahy , Debasisha Mishra

Hypergraphs and tensors extend classic graph and matrix theory to account for multiway relationships, which are ubiquitous in engineering, biological, and social systems. While the Kronecker product is a potent tool for analyzing the…

Dynamical Systems · Mathematics 2024-04-11 Joshua Pickard , Can Chen , Cooper Stansbury , Amit Surana , Anthony Bloch , Indika Rajapakse

We consider an approximate computation of several minimal eigenpairs of large Hermitian matrices which come from high--dimensional problems. We use the tensor train format (TT) for vectors and matrices to overcome the curse of…

Numerical Analysis · Mathematics 2014-03-05 Sergey V. Dolgov , Boris N. Khoromskij , Ivan V. Oseledets , Dmitry V. Savostyanov

A third order real tensor is called a piezoelectric-type tensor if it is partially symmetric with respect to its last two indices. The piezoelectric tensor is a piezoelectric-type tensor of dimension three. We introduce C-eigenvalues and…

Mathematical Physics · Physics 2017-03-24 Yannan Chen , Antal Jákli , Liqun Qi

We introduce $t$-Hermitian forms of arbitrary degree $k$, a natural extension of classical degree $k$ Hermitian forms obtained through a synthesis of the tensor transformation law and the $t$-product of third-order tensors. We show that…

Spectral Theory · Mathematics 2026-02-25 Isaac Dobes

We provide formulas for computing the discriminant of noncommutative algebras over central subalgebras in the case of Ore extensions and skew group extensions. The formulas follow from a more general result regarding the discriminants of…

Rings and Algebras · Mathematics 2018-09-28 Jason Gaddis , Ellen Kirkman , W. Frank Moore

Developing equivariant neural networks for the E(3) group plays an important role in modeling 3D data across real-world applications. Enforcing this equivariance primarily involves the tensor products of irreducible representations…

Machine Learning · Computer Science 2024-11-12 Shengjie Luo , Tianlang Chen , Aditi S. Krishnapriyan

The real symmetric tridiagonal eigenproblem is of outstanding importance in numerical computations; it arises frequently as part of eigensolvers for standard and generalized dense Hermitian eigenproblems that are based on a reduction to…

Mathematical Software · Computer Science 2014-01-21 Matthias Petschow

We present a new framework for computing Z-eigenvectors of general tensors based on numerically integrating a dynamical system that can only converge to a Z-eigenvector. Our motivation comes from our recent research on spacey random walks,…

Numerical Analysis · Mathematics 2019-03-14 Austin R. Benson , David F. Gleich

For tensor linear systems with respect to the popular t-product, we first present the sketch-and-project method and its adaptive variants. Their Fourier domain versions are also investigated. Then, considering that the existing sketching…

Numerical Analysis · Mathematics 2022-03-30 Ling Tang , Yajie Yu , Yanjun Zhang , Hanyu Li

This is the third part in a series of papers in which we introduce and develop a natural, general tensor category theory for suitable module categories for a vertex (operator) algebra. In this paper (Part III), we introduce and study…

Quantum Algebra · Mathematics 2012-05-14 Yi-Zhi Huang , James Lepowsky , Lin Zhang

We introduce the tubal tensor train (TTT) decomposition, a tensor-network model that combines the t-product algebra of the tensor singular value decomposition (T-SVD) with the low-order core structure of the tensor train (TT) format. For an…

Numerical Analysis · Mathematics 2026-03-12 Salman Ahmadi-Asl , Valentin Leplat , Anh-Huy Phan , Andrzej Cichocki

We present eigenvalue decay estimates of integral operators associated with compositional dot-product kernels. The estimates improve on previous ones established for power series kernels on spheres. This allows us to obtain the volumes of…

Machine Learning · Statistics 2021-03-01 Meyer Scetbon , Zaid Harchaoui

We consider computing the $k$-th eigenvalue and its corresponding eigenvector of a generalized Hermitian eigenvalue problem of $n\times n$ large sparse matrices. In electronic structure calculations, several properties of materials, such as…

Numerical Analysis · Mathematics 2018-08-01 Dongjin Lee , Takeo Hoshi , Tomohiro Sogabe , Yuto Miyatake , Shao-Liang Zhang

We start by showing how to approximate unitary and bounded self-adjoint operators by operators in finite dimensional spaces. Using ultraproducts we give a precise meaning for the approximation. In this process we see how the spectral…

Logic · Mathematics 2022-08-16 Åsa Hirvonen , Tapani Hyttinen

We compute the spectrum of the "all ones" hypermatrix using the Poisson product formula. This computation includes a complete description of the eigenvalues' multiplicities, a seemingly elusive aspect of the spectral theory of tensors. We…

Spectral Theory · Mathematics 2013-01-22 Joshua Cooper , Aaron Dutle

We equip the tensor algebra of a vector space $U$ over the real or complex field with an alternative product. The new product has the property that if we specialize it to the symmetric tensor algebra becomes the circle product introduced by…

Quantum Algebra · Mathematics 2011-03-16 V. Anagnostopoulos , Y. Sarantopoulos

We introduce and study, for a process P delivering edges on the Cartesian product of the vertex sets of a given set of graphs, the P-product of these graphs, thereby generalizing many types of product graph. Analogous to the notion of a…

Combinatorics · Mathematics 2017-02-10 Izak Broere , Johannes Heidema

Tensor decomposition is a fundamental method used in various areas to deal with high-dimensional data. \emph{Tensor power method} (TPM) is one of the widely-used techniques in the decomposition of tensors. This paper presents a novel tensor…

Machine Learning · Computer Science 2023-06-02 Yichuan Deng , Zhao Song , Junze Yin

We extend the method for constructing symmetry operators of higher order for two-dimensional quantum Hamiltonians by Kalnins, Kress and Miller (2010). This expansion method expresses the integral in a finite power series in terms of lower…

Mathematical Physics · Physics 2025-05-26 Ian Marquette , Anthony Parr