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The tensor rank decomposition problem consists of recovering the unique set of parameters representing a robustly identifiable low-rank tensor when the coordinate representation of the tensor is presented as input. A condition number for…

Algebraic Geometry · Mathematics 2022-09-02 Nick Vannieuwenhoven

We prove that the generic element of the fifth secant variety $\sigma_5(Gr(\mathbb{P}^2,\mathbb{P}^9)) \subset \mathbb{P}(\bigwedge^3 \mathbb{C}^{10})$ of the Grassmannian of planes of $\mathbb{P}^9$ has exactly two decompositions as a sum…

Algebraic Geometry · Mathematics 2018-02-19 Davide Vanzo , Alessandra Bernardi

The pursue of what are properties that can be identified to permit an automated reasoning program to generate and find new and interesting theorems is an interesting research goal (pun intended). The automatic discovery of new theorems is a…

Artificial Intelligence · Computer Science 2024-01-23 Pedro Quaresma , Pierluigi Graziani , Stefano M. Nicoletti

By combining a parameterized Hermitian matrix, the realignment matrix of the bipartite density matrix $\rho$ and the vectorization of its reduced density matrices, we present a family of separability criteria, which are stronger than the…

Quantum Physics · Physics 2015-11-03 Shu-Qian Shen , Meng-Yuan Wang , Ming Li , Shao-Ming Fei

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

Employing a recently proposed separability criterion we develop analytical lower bounds for the concurrence and for the entanglement of formation of bipartite quantum systems. The separability criterion is based on a nondecomposable…

Quantum Physics · Physics 2007-05-23 Heinz-Peter Breuer

General physical background of Peres-Horodecki positive partial transpose (ppt-) separability criterion is revealed. Especially, the physical sense of partial transpose operation is shown to be equivalent to the "local causality reversal"…

Quantum Physics · Physics 2021-08-09 Gleb A. Skorobagatko

We introduce a weak form of the realignment separability criterion which is particularly suited to detect continuous-variable entanglement and is physically implementable (it requires linear optics transformations and homodyne detection).…

Quantum Physics · Physics 2021-08-24 Anaelle Hertz , Matthieu Arnhem , Ali Asadian , Nicolas J. Cerf

In this paper a new general approach is developed to construct and study Lebesgue type decompositions of linear operators $T$ in the Hilbert space setting. The new approach allows to introduce an essentially wider class of Lebesgue type…

Functional Analysis · Mathematics 2023-09-20 Seppo Hassi , Henk de Snoo

A projective variety $X\subset\mathbb{P}^N$ is $h$-identifiable if the generic element in its $h$-secant variety uniquely determines $h$ points on $X$. In this paper we propose an entirely new approach to study identifiability, connecting…

Algebraic Geometry · Mathematics 2019-11-05 Alex Casarotti , Massimiliano Mella

A basic question in the study of measure-once quantum finite automata is whether two distinct input words can be separated with certainty. The exact separation problem reduces to a trace-vanishing question in \(SU(2)\). The main difficulty…

Formal Languages and Automata Theory · Computer Science 2026-05-04 Zeyu Chen , Junde Wu

A theorem of N. Katz \cite{Ka} p.45, states that an irreducible differential operator $L$ over a suitable differential field $k$, which has an isotypical decomposition over the algebraic closure of $k$, is a tensor product $L=M\otimes_k N$…

Algebraic Geometry · Mathematics 2010-01-05 Elie Compoint , Marius van der Put , Jacques-Arthur Weil

The need to know a few singular triplets associated with the largest singular values of third-order tensors arises in data compression and extraction. This paper describes a new method for their computation using the t-product. Methods for…

Numerical Analysis · Mathematics 2023-01-10 Anas El Hachimi , Khalide Jbilou , Ahmed Ratnani , Lothar Reichel

In this paper we provide a new method to certify that a nearby polynomial system has a singular isolated root with a prescribed multiplicity structure. More precisely, given a polynomial system f $=(f\_1, \ldots, f\_N)\in C[x\_1, \ldots,…

Commutative Algebra · Mathematics 2020-07-16 Angelos Mantzaflaris , Bernard Mourrain , Agnes Szanto

The deformation theory of singular varieties plays a central role in understanding the geometry and moduli of algebraic varieties. For a variety $X$ with possibly singular points, the space of first-order infinitesimal deformations is given…

Algebraic Geometry · Mathematics 2025-12-16 Mounir Nisse

We prove a generalization to Jennrich's uniqueness theorem for tensor decompositions in the undercomplete setting. Our uniqueness theorem is based on an alternative definition of the standard tensor decomposition, which we call…

Computational Complexity · Computer Science 2025-10-31 Pascal Koiran , Rafael Oliveira

A new criterion is developed which provides a check as to whether a chosen set of polarization observables is complete with respect to the determination of all independent $T$-matrix elements of a reaction of the type $a+b\to c+d+...$. As…

Nuclear Theory · Physics 2009-10-31 Hartmuth Arenhoevel , Winfried Leidemann , Edward L. Tomusiak

For many years, exact metric search relied upon the property of triangle inequality to give a lower bound on uncalculated distances. Two exclusion mechanisms derive from this property, generally known as pivot exclusion and hyperplane…

Data Structures and Algorithms · Computer Science 2022-11-11 Richard Connor

The accuracy and complexity of kernel learning algorithms is determined by the set of kernels over which it is able to optimize. An ideal set of kernels should: admit a linear parameterization (tractability); be dense in the set of all…

Machine Learning · Statistics 2020-05-04 Brendon K. Colbert , Matthew M. Peet

Tensor decompositions have become a central tool in data science, with applications in areas such as data analysis, signal processing, and machine learning. A key property of many tensor decompositions, such as the canonical polyadic…

Numerical Analysis · Mathematics 2025-05-20 Subhayan Saha , Giovanni Barbarino , Nicolas Gillis