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The problem of inferring the distribution of a random vector given that its norm is large requires modeling a homogeneous limiting density. We suggest an approach based on graphical models which is suitable for high-dimensional vectors. We…

Probability · Mathematics 2022-12-20 Adrien Hitz , Robin Evans

We study numerically statistical distributions of sums of orbit coordinates, viewed as independent random variables in the spirit of the Central Limit Theorem, in weakly chaotic regimes associated with the excitation of the first ($k=1$)…

Chaotic Dynamics · Physics 2015-05-28 Chris G. Antonopoulos , Helen Christodoulidi

We consider two stable heteroclinic cycles rotating in opposite directions, coupled via diffusive terms. A complete synchronization in this system is impossible, and numerical exploration shows that chaos is abundant at low levels of…

Chaotic Dynamics · Physics 2023-06-14 Arkady Pikovsky , Alexander Nepomnyashchy

Let $\{x_{\alpha}\}_{\alpha \in \mathbb{Z}}$ and $\{y_{\alpha}\}_{\alpha \in \mathbb{Z}}$ be two independent collections of zero mean, unit variance random variables with uniformly bounded moments of all orders. Consider a nonsymmetric…

Probability · Mathematics 2022-09-07 Soumendu Sundar Mukherjee

In this brief note, we show that chaotic Boltzmann machines truly yield samples from the probabilistic distribution of the corresponding Boltzmann machines if they are composed of only two elements. This note is an English translation (with…

Chaotic Dynamics · Physics 2015-01-29 Hideyuki Suzuki

We treat $n$-dimensional piecewise-linear continuous maps with two pieces, each of which has exactly one unstable direction, and identify an explicit set of sufficient conditions for the existence of a chaotic attractor. The conditions…

Chaotic Dynamics · Physics 2024-10-31 Indranil Ghosh , David J. W. Simpson

Having spectral correlations that, over small enough energy scales, are described by random matrix theory is regarded as the most general defining feature of quantum chaotic systems as it applies in the many-body setting and away from any…

Statistical Mechanics · Physics 2024-09-02 Jonathon Riddell , Curt von Keyserlingk , Tomaž Prosen , Bruno Bertini

Dynamical chaos has recently been shown to exist in the Gaussian approximation in quantum mechanics and in the self-consistent mean field approach to studying the dynamics of quantum fields. In this study, we first show that any variational…

Quantum Physics · Physics 2008-11-26 Fred Cooper , John Dawson , Salman Habib , Robert D. Ryne

This paper presents an elementary proof of quantitative uniform-in-time propagation of chaos for the Cucker--Smale model under sufficiently strong interaction. The idea is to combine existing finite-time propagation of chaos estimates with…

Probability · Mathematics 2025-11-03 Nicolai Jurek Gerber , Urbain Vaes

We study properties of chaos in generic one-dimensional nonlinear Hamiltonian lattices comprised of weakly coupled nonlinear oscillators, by numerical simulations of continuous-time systems and symplectic maps. For small coupling, the…

Chaotic Dynamics · Physics 2011-12-06 Mario Mulansky , Karsten Ahnert , Arkady Pikovsky , Dima Shepelyansky

We have developed the {\it general method} for the description of {\it separatrix chaos}, basing on the analysis of the separatrix map dynamics. Matching it with the resonant Hamiltonian analysis, we show that, for a given amplitude of…

Chaotic Dynamics · Physics 2007-11-01 S. M. Soskin , R. Mannella , O. M. Yevtushenko

We study distributions of random vectors whose components are second order polynomials in Gaussian random variables. Assuming that the law of such a vector is not absolutely continuous with respect to Lebesgue measure, we derive some…

Probability · Mathematics 2013-05-28 Vladimir I. Bogachev , Egor D. Kosov , Ivan Nourdin , Guillaume Poly

Random projection (RP) have recently emerged as popular techniques in the machine learning community for their ability in reducing the dimension of very high-dimensional tensors. Following the work in [30], we consider a tensorized random…

Machine Learning · Computer Science 2022-02-04 Beheshteh T. Rakhshan , Guillaume Rabusseau

Due to the deterministic nature of chaotic systems, fluctuations in their trajectories arise solely from the choice of initial conditions. Some of these dynamical fluctuations may lead to extremely unlikely scenarios. Understanding the…

Statistical Mechanics · Physics 2025-07-23 Yllari K. González-Koda , Ricardo Gutiérrez , Carlos Pérez-Espigares

We show that the probability distribution function that best fits the distribution of return times between two consecutive visits of a chaotic trajectory to finite size regions in phase space deviates from the exponential statistics by a…

Chaotic Dynamics · Physics 2015-05-13 Murilo S. Baptista , Dariel M. Maranhao , Jose C. Sartorelli

We consider a $2$-dimensional autonomous system subject to a $1$-periodic perturbation, i.e. $$ \dot{\vec{x}}=\vec{f}(\vec{x})+\epsilon\vec{g}(t,\vec{x},\epsilon),\quad \vec{x}\in\Omega .$$ We assume that for $\epsilon=0$ there is a…

Dynamical Systems · Mathematics 2025-09-11 Alessandro Calamai , Matteo Franca , Michal Pospisil

The starting point of this work is a theorem due to Maxwell characterizing the distribution of a Gaussian vector with at least two coordinates. We define the Gaussian orthogonal, unitary and symplectic tensor ensembles for notions of real…

Mathematical Physics · Physics 2026-04-02 Rémi Bonnin

We develop a new technique that allows us to show in a unified way that many well-known combinatorial theorems, including Tur\'an's theorem, Szemer\'edi's theorem and Ramsey's theorem, hold almost surely inside sparse random sets. For…

Combinatorics · Mathematics 2015-02-03 D. Conlon , W. T. Gowers

Weakly chaotic or weakly interacting systems have a wide regime where the common random matrix theory modeling does not apply. As an example we consider cold atoms in a nearly integrable optical billiard with displaceable wall ("piston").…

Quantum Physics · Physics 2011-07-08 Alexander Stotland , Louis M. Pecora , Doron Cohen

We present a simple combinatorial framework for establishing approximate tensorization of variance and entropy in the setting of spin systems (a.k.a. undirected graphical models) based on balanced separators of the underlying graph. Such…

Data Structures and Algorithms · Computer Science 2023-07-18 Zongchen Chen
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