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The canonical polyadic decomposition (CPD) is a compact decomposition which expresses a tensor as a sum of its rank-1 components. A common step in the computation of a CPD is computing a generalized eigenvalue decomposition (GEVD) of the…

Numerical Analysis · Mathematics 2021-12-16 Eric Evert , Michiel Vandecappelle , Lieven De Lathauwer

In this paper, we propose a new general and stable fixed-point approach to compute the resolvents of the composition of a set-valued maximal monotone operator with a linear bounded mapping. Weak, strong and linear convergence of the…

Optimization and Control · Mathematics 2025-02-05 Samir Adly , Ba Khiet Le

Applied magnetic fields can couple to atomic displacements via generalized Lorentz forces, which are commonly expressed as gyromagnetic $g$ factors. We develop an efficient first-principles methodology based on density-functional…

Materials Science · Physics 2022-03-23 Asier Zabalo , Cyrus E. Dreyer , Massimiliano Stengel

We provide simple criteria and algorithms for expressing homogeneous polynomials as sums of powers of independent linear forms, or equivalently, for decomposing symmetric tensors into sums of rank-1 symmetric tensors of linearly independent…

Rings and Algebras · Mathematics 2021-10-08 Hua-Lin Huang , Huajun Lu , Yu Ye , Chi Zhang

Tensors are multidimensional analogs of matrices. In this paper, based on degree-theoretic ideas, we study homogeneous nonlinear complementarity problems induced by tensors. By specializing this to $Z$-tensors (which are tensors with…

Optimization and Control · Mathematics 2017-01-02 M. Seetharama Gowda , Ziyan Luo , Liqun Qi , Naihua Xiu

To define a minimal mathematical framework for isolating some of the characteristic properties of quantum entanglement, we introduce a generalization of the tensor product of graphs. Inspired by the notion of a density matrix, the…

Combinatorics · Mathematics 2009-09-17 Sandi Klavzar , Simone Severini

A numerical approach to compute tensor integrals in one-loop calculations is presented. The algorithm is based on a recursion relation which allows to express high rank tensor integrals as a function of lower rank ones. At each level of…

High Energy Physics - Phenomenology · Physics 2010-02-03 F. del Aguila , R. Pittau

Since Kilmer et al. introduced the new multiplication method between two third-order tensors around 2008 and third-order tensors with such multiplication structure are also called as T-product tensors, T-product tensors have been applied to…

Probability · Mathematics 2021-10-06 Shih Yu Chang , Yimin Wei

We demonstrate a concise method to enumerate the number of generalized polarizabilities---quantities characterizing the independent observables in singly-virtual Compton scattering---for a target particle of arbitrary spin s. By using…

High Energy Physics - Phenomenology · Physics 2009-11-07 Richard F. Lebed

Entanglement is one of the fundamental properties of a quantum state and is a crucial differentiator between classical and quantum computation. There are many ways to define entanglement and its measure, depending on the problem or…

Quantum Physics · Physics 2025-01-07 Andrii Semenov , Niall Murphy , Simone Patscheider , Alessandra Bernardi , Elena Blokhina

Inflation gives rise to a nearly scale-invariant spectrum of tensor perturbations (gravitational waves), their contribution to the Cosmic Background Radiation (CBR) anisotropy depends upon the present cosmological parameters as well as…

Astrophysics · Physics 2014-10-13 Michael S. Turner , Yun Wang

Producing large complex simulation datasets can often be a time and resource consuming task. Especially when these experiments are very expensive, it is becoming more reasonable to generate synthetic data for downstream tasks. Recently,…

Machine Learning · Computer Science 2025-08-28 Paimon Goulart , Shaan Pakala , Evangelos Papalexakis

We propose a real-space renormalization group algorithm for accurately coarse-graining two-dimensional tensor networks. The central innovation of our method lies in utilizing variational boundary tensors as a globally optimized environment…

Statistical Mechanics · Physics 2026-03-03 Feng-Feng Song , Naoki Kawashima

Certain computable polynomials are described whose leading coefficients are equal to multiplicities in the tensor product decomposition for representations of a Lie algebra of ADE type.

Representation Theory · Mathematics 2007-05-23 Anton Malkin

The coupling effects in multiphysics processes are often neglected in designing multiscale methods. The coupling may be described by a non-positive definite operator, which in turn brings significant challenges in multiscale simulations. In…

Numerical Analysis · Mathematics 2024-01-05 Xiaofei Guan , Lijian Jiang , Yajun Wang

The entropy computation of Gaussian mixture distributions with a large number of components has a prohibitive computational complexity. In this paper, we propose a novel approach exploiting the sphere decoding concept to bound and…

Information Theory · Computer Science 2015-10-28 Su Min Kim , Tan Tai Do , Tobias J. Oechtering , Gunnar Peters

This paper studies the issues about the generalized inverses of tensors under the C-Product. The aim of this paper is threefold. Firstly, this paper present the definition of the Moore-Penrose inverse, Drazin inverse of tensors under the…

Rings and Algebras · Mathematics 2024-12-12 Hongwei Jin , Shumin Xu , Hongjie Jiang , Xiaoji Liu

This paper proposes a general framework to estimate coefficients of generalized polynomial chaos (gPC) used in uncertainty quantification via rotational sparse approximation. In particular, we aim to identify a rotation matrix such that the…

Computation · Statistics 2021-09-20 Mengqi Hu , Yifei Lou , Xiu Yang

Formal expressions are derived for the multipole expansion of the structure functions of a general polarization observable of exclusive electrodisintegration of the deuteron using a longitudinally polarized beam and/or an oriented target.…

Nuclear Theory · Physics 2007-05-23 Hartmuth Arenhoevel , Winfried Leidemann , Edward L. Tomusiak

In general, matrix or tensor-valued functions are approximated using the method developed for vector-valued functions by transforming the matrix-valued function into vector form. This paper proposes a tensor-based interpolation method to…

Numerical Analysis · Mathematics 2026-05-08 Brij Nandan Tripathi , Hanumant Singh Shekhawat , Seip Weiland