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Piecewise linear recurrent neural networks (PLRNNs) form the basis of many successful machine learning applications for time series prediction and dynamical systems identification, but rigorous mathematical analysis of their dynamics and…

Dynamical Systems · Mathematics 2020-07-02 Zahra Monfared , Daniel Durstewitz

We study sequences of bounded operators \((T_n)_{n \ge 0}\) on a complex separable Hilbert space \(\mathcal{H}\) that satisfy a linear recurrence relation of the form $$ T_{n+r} = A_0 T_n + A_1 T_{n+1} + \cdots + A_{r-1} T_{n+r-1}…

Functional Analysis · Mathematics 2026-05-12 Raul E. Curto , Abderrazzak Ech-charyfy , Kaissar Idrissi , El Hassan Zerouali

Understanding stickiness and power-law behavior of Poincar\'e recurrence statistics is an open problem for higher-dimensional systems, in contrast to the well-understood case of systems with two degrees-of-freedom. We study such…

Chaotic Dynamics · Physics 2020-03-11 Swetamber Das , Arnd Bäcker

A natural number N is said to be palindromic if its binary representation reads the same forwards and backwards. In this paper we study the quotients of two palindromic numbers and answer some basic questions about the resulting sets of…

Number Theory · Mathematics 2022-03-01 James Haoyu Bai , Joseph Meleshko , Samin Riasat , Jeffrey Shallit

We calculate the 1-loop renormalization of the fermion self-energy, all local fermion bilinears, as well as a set of extended bilinears which form a basis corresponding to moments of the parton distribution functions. We use the overlap…

High Energy Physics - Lattice · Physics 2009-11-11 M. Ioannou , H. Panagopoulos

The behavior of a linear oscillator under the action of an external almost periodic force is investigated. The constructed solutions grow more slowly than the resonant ones. The dependence of the amplitude of growing solutions on the…

Classical Analysis and ODEs · Mathematics 2021-04-05 P. Y. Astafyeva , O. M. Kiselev

The NP-hard problem of optimizing a shallow ReLU network can be characterized as a combinatorial search over each training example's activation pattern followed by a constrained convex problem given a fixed set of activation patterns. We…

Machine Learning · Computer Science 2022-10-04 Michael Matena , Colin Raffel

We classify the unitary, renormalizable, Lorentz violating quantum field theories of interacting scalars and fermions, obtained improving the behavior of Feynman diagrams by means of higher space derivatives. Higher time derivatives are not…

High Energy Physics - Theory · Physics 2008-11-26 Damiano Anselmi , Milenko Halat

The celebrated $3x+1$ problem is reformulated via the use of an analytic expression of the trailing zeros sequence resulting in a single branch formula $f(x)+1$ with a unique fixed point. The resultant formula $f(x)$ is also found to…

General Mathematics · Mathematics 2024-08-05 T. Raptis

We consider the class of simple Brown-Resnick max-stable processes whose spectral processes are continuous exponential martingales. We develop the asymptotic theory for the realized power variations of these max-stable processes, that is,…

Statistics Theory · Mathematics 2019-06-11 Christian Y. Robert

In this work, orthogonal polynomials satisfying $R_I$ type recurrence relation %$\mathcal{P}_{n+1}(z) = (z-c_n)\mathcal{P}_n(z)-\lambda_n (z-a_n)\mathcal{P}_{n-1}(z),$ with $\mathcal{P}_{-1}(z) = 0$ and $\mathcal{P}_0(z) = 1$ are analyzed…

Classical Analysis and ODEs · Mathematics 2024-05-24 Vinay Shukla , A. Swaminathan

We propose a recursive method that makes use of the basic principle of unitarity to calculate the Landau singularities of n-point scattering amplitudes directly in kinematic space. For a vast class of Feynman diagrams, the method enables…

High Energy Physics - Theory · Physics 2025-08-27 Simon Caron-Huot , Miguel Correia , Mathieu Giroux

We derive a set of constraints, which we will call hierarchy constraints (HCs), on scattering amplitudes of an arbitrary multistate Landau-Zener model (MLZM). The presence of additional symmetries can transform such constraints into…

Quantum Physics · Physics 2017-02-08 N. A. Sinitsyn , J. Lin , V. Y. Chernyak

The recurrence phenomena of an initially well localized wave packet are studied in periodically driven power-law potentials. For our general study we divide the potentials in two kinds, namely tightly binding and loosely binding potentials.…

Quantum Physics · Physics 2009-11-13 Shahid Iqbal , Qurat-ul-Ann , Farhan Saif

A recursive form of arbitrary-order Wronskian associated with transformation functions in the confluent algorithm of supersymmetric quantum mechanics (SUSY) is constructed. With this recursive form regularity conditions for the generated…

Mathematical Physics · Physics 2017-02-06 Alonso Contreras-Astorga , Axel Schulze-Halberg

This paper investigates the combinatorics that gives rise to the Boltzmann probability distribution. Despite being one of the most important distributions in physics and other fields of science, the mathematics of the underlying model of…

Probability · Mathematics 2025-07-09 Bart Jacobs

In this paper, we study the periodicity structure of finite field linear recurring sequences whose period is not necessarily maximal and determine necessary and sufficient conditions for the characteristic polynomial~\(f\) to have exactly…

Combinatorics · Mathematics 2021-03-02 Ghurumuruhan Ganesan

We consider the question of simultaneous extension of (pseudo)metrics defined on nonempty closed subsets of a compact metrizable space. The main result is a counterpart of the result due to K\"unzi and Shapiro for the case of extension…

General Topology · Mathematics 2007-05-23 E. D. Tymchatyn , M. Zarichnyi

We introduce and study isomonodromy transformations of the matrix linear difference equation Y(z+1)=A(z)Y(z) with polynomial (or rational) A(z). Our main result is a construction of an isomonodromy action of Z^{m(n+1)-1} on the space of…

Classical Analysis and ODEs · Mathematics 2007-05-23 Alexei Borodin

Recurrent neural networks (RNNs) are capable of learning features and long term dependencies from sequential and time-series data. The RNNs have a stack of non-linear units where at least one connection between units forms a directed cycle.…

Neural and Evolutionary Computing · Computer Science 2018-02-26 Hojjat Salehinejad , Sharan Sankar , Joseph Barfett , Errol Colak , Shahrokh Valaee