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On a non-compact, smooth, connected, boundaryless, complete Riemannian manifold $(M,g)$, one can define its ideal boundary by rays (or equivalently, Busemann functions). From the viewpoint of Mather theory, boundary elements could be…

Dynamical Systems · Mathematics 2013-12-20 Xiaojun Cui

We introduce the notion of a relative marked basis over quasi-stable ideals, together with constructive methods and a functorial interpretation, developing computational methods for the study of Hilbert schemes over quotients of polynomial…

Commutative Algebra · Mathematics 2024-02-06 Cristina Bertone , Francesca Cioffi , Matthias Orth , Werner M. Seiler

We develop a general theory of "almost Hadamard matrices". These are by definition the matrices $H\in M_N(\mathbb R)$ having the property that $U=H/\sqrt{N}$ is orthogonal, and is a local maximum of the 1-norm on O(N). Our study includes a…

Combinatorics · Mathematics 2013-02-19 Teodor Banica , Ion Nechita , Karol Zyczkowski

A phenomenological Hamiltonian of a closed (i.e., unitary) quantum system is assumed to have an $N$ by $N$ real-matrix form composed of a unperturbed diagonal-matrix part $H^{(N)}_0$ and of a tridiagonal-matrix perturbation…

Mathematical Physics · Physics 2021-06-01 Miloslav Znojil

Hopf-link semimetals exhibit exotic gapless band structures with fascinating topological properties, which have never been observed in nature. Here we demonstrate nodal lines with topological form of Hopf-link chains in artificial…

Quantum Physics · Physics 2018-05-23 Xinsheng Tan , Mengmeng Li , Danyu Li , Kunzhe Dai , Haifeng Yu , Yang Yu

To characterize categorical constraints - associativity, commutativity and monoidality - in the context of quasimonoidal categories, from a cohomological point of view, we define the notion of a parity (quasi)complex. Applied to groups…

Category Theory · Mathematics 2007-05-23 Lucian M. Ionescu

Hopfield model is one of the few neural networks for which analytical results can be obtained. However, most of them are derived under the assumption of random uncorrelated patterns, while in real life applications data to be stored show…

Statistical Mechanics · Physics 2023-02-01 Giordano De Marzo , Giulio Iannelli

In this article we study a class of hyperbolic partial differential equations of order one on the semi-axis. The so-called port-Hamiltonian systems cover for instance the wave equation and the transport equation, but also networks of the…

Functional Analysis · Mathematics 2020-05-26 Birgit Jacob , Sven-Ake Wegner

This paper is concerned with the modeling and analysis of two of the most commonly used recurrent neural network models (i.e., Hopfield neural network and firing-rate neural network) with dynamic recurrent connections undergoing Hebbian…

Optimization and Control · Mathematics 2024-03-25 Veronica Centorrino , Francesco Bullo , Giovanni Russo

Similar to linear spaces, many examples of quasilinear spaces have a notion of multiplication of the elements. To characterising these examples, in the present paper we generalize the notion of quasilinear spaces and introduce…

Functional Analysis · Mathematics 2020-10-20 Reza Dehghanizade , Seyed Mohamad Sadegh Modarres Mosadegh

The problem of determining whether a diagonally dominant matrix is singular or nonsingular is a classical topic in matrix theory. This paper develops necessary and sufficient conditions for the singularity or nonsingularity of diagonally…

Rings and Algebras · Mathematics 2025-12-02 Jidong Jin

We give a criterion for almost Gorenstein property for semigroup rings associated with simplicial semigroups. We extend Nari's theorem for almost symmetric numerical semigroups to simplicial semigroups with higher rank. By this criterion,…

Commutative Algebra · Mathematics 2024-06-11 Kazufumi Eto , Naoyuki Matsuoka , Takahiro Numata , Kei-ichi Watanabe

An analytic reversible Hamiltonian system with two degrees of freedom is studied in a neighborhood of its symmetric heteroclinic connection made up of a symmetric saddle-center, a symmetric orientable saddle periodic orbit lying in the same…

Dynamical Systems · Mathematics 2021-02-24 L. M. Lerman , K. N. Trifonov

We consider the Hopfield neural network as a model of associative memory and we define its neuronal interaction matrix $\mathbf{J}$ as a function of a set of $K \times M$ binary vectors $\{\mathbf{\xi}^{\mu, A} \}_{\mu=1,...,K}^{A=1,...,M}$…

Mathematical Physics · Physics 2025-05-16 Elena Agliari , Domenico Luongo , Alberto Fachechi

The Hamiltonian of a recently proposed supersymmetric matrix model has been shown to become block-diagonal in the large-N, infinite 't Hooft coupling limit. We show that (most of) these blocks can be mapped into seemingly non-supersymmetric…

High Energy Physics - Theory · Physics 2011-07-28 G. Veneziano , J. Wosiek

Compound matrices have found applications in many fields of science including systems and control theory. In particular, a sufficient condition for $k$-contraction is that a logarithmic norm (also called matrix measure) of the $k$-additive…

Dynamical Systems · Mathematics 2022-09-05 Omri Dalin , Ron Ofir , Eyal Bar Shalom , Alexander Ovseevich , Francesco Bullo , Michael Margaliot

Hopfield networks are artificial neural networks which store memory patterns on the states of their neurons by choosing recurrent connection weights and update rules such that the energy landscape of the network forms attractors around the…

Neural and Evolutionary Computing · Computer Science 2023-05-10 Thomas F Burns , Tomoki Fukai

We consider the moduli space of abelian varieties with two marked points and a frame of the relative de Rham cohomolgy with boundary at these points compatible with its mixed Hodge structure. Such a moduli space gives a natural…

Algebraic Geometry · Mathematics 2021-09-03 Jin Cao , Hossein Movasati , Roberto Villaflor Loyola

We classify finite-dimensional Hopf algebras over an algebraically closed field of characteristic zero whose Hopf coradcial is isomorphic to the smallest non-pointed basic Hopf algebra, under the assumption that the diagrams are strictly…

Quantum Algebra · Mathematics 2018-05-16 Rongchuan Xiong

The gap between the huge volumes of data needed to train artificial neural networks and the relatively small amount of data needed by their biological counterparts is a central puzzle in machine learning. Here, inspired by biological…

Disordered Systems and Neural Networks · Physics 2022-04-19 Miriam Aquaro , Francesco Alemanno , Ido Kanter , Fabrizio Durante , Elena Agliari , Adriano Barra
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