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A new type of deterministic chaos for a system described by iterative two-dimensional maps is reported. The series being generated by the original map has an average upward trend while the first difference, which is the series of changes…

Chaotic Dynamics · Physics 2010-07-22 Taisei Kaizoji

This paper is devoted to integrability conditions for systems of linear difference and differential equations with difference parameters. It is shown that such a system is difference isomonodromic if and only if it is difference…

Commutative Algebra · Mathematics 2014-04-15 Alexey Ovchinnikov

Discrete time evolution of one-dimensional maps is embedded in continuous time by truncating the Taylor series expansion of the time evolution operator to a finite order N. Truncations with N > 4 leads to unconditional instability.…

Mathematical Physics · Physics 2009-11-10 M. C. Valsakumar , A. Rajan Nambiar , P. Rameshan

We study the synchronization of a linear array of globally coupled identical logistic maps. We consider a time-delayed coupling that takes into account the finite velocity of propagation of the interactions. We find globally synchronized…

Chaotic Dynamics · Physics 2016-08-16 A. C. Martí , C. Masoller

Two symmetrically coupled logistic equations are proposed to mimic the competitive interaction between two species. The phenomena of coexistence, oscillations and chaos are present in this cubic discrete system. This work, together with two…

Chaotic Dynamics · Physics 2007-05-23 Ricardo Lopez-Ruiz , Daniele Fournier-Prunaret

Comparing time series is essential in various tasks such as clustering and classification. While elastic distance measures that allow warping provide a robust quantitative comparison, a qualitative comparison on top of them is missing.…

Machine Learning · Computer Science 2025-06-19 Simiao Lin , Wannes Meert , Pieter Robberechts , Hendrik Blockeel

Consider the problem of learning the drift coefficient of a stochastic differential equation from a sample path. In this paper, we assume that the drift is parametrized by a high dimensional vector. We address the question of how long the…

Information Theory · Computer Science 2011-03-10 José Bento , Morteza Ibrahimi , Andrea Montanari

A spatially one dimensional coupled map lattice possessing the same symmetries as the Miller Huse model is introduced. Our model is studied analytically by means of a formal perturbation expansion which uses weak coupling and the vicinity…

Chaotic Dynamics · Physics 2015-06-26 F. Schmuser , W. Just , H. Kantz

We address the issue of how to identify the equations of a largely unknown chaotic system from knowledge about its state evolution. The technique can be applied to the estimation of parameters that drift slowly with time. To accomplish…

Disordered Systems and Neural Networks · Physics 2009-09-17 Francesco Sorrentino , Edward Ott

We consider a parameter dependent periodic-logistic problem with a logistic term involving a degeneracy that replicates time dependent refuges in the habitat of a population. Working under no or very minimal assumptions on the boundary…

Analysis of PDEs · Mathematics 2025-02-21 Daniel Daners , Zeaiter Zeaiter

Defect-chaos is studied numerically in coupled Ginzburg-Landau equations for parametrically driven waves. The motion of the defects is traced in detail yielding their life-times, annihilation partners, and distances traveled. In a regime in…

chao-dyn · Physics 2015-06-24 Glen D. Granzow , Hermann Riecke

We present analytical expressions for the time-dependent and stationary probability distributions corresponding to a stochastically perturbed one-dimensional flow with critical points, in two physically relevant situations: delayed…

Statistical Mechanics · Physics 2007-05-23 V. Balakrishnan , C. Van den Broeck , I. Bena

We study the dynamics of an ensemble of globally coupled chaotic logistic maps under the action of a learning algorithm aimed at driving the system from incoherent collective evolution to a state of spontaneous full synchronization.…

Adaptation and Self-Organizing Systems · Physics 2009-10-31 Luis G. Moyano , Guillermo Abramson , Damian H. Zanette

We study two-dimensional, two-piece, piecewise-linear maps having two saddle fixed points. Such maps reduce to a four-parameter family and are well known to have a chaotic attractor throughout open regions of parameter space. The purpose of…

Chaotic Dynamics · Physics 2024-02-09 Indranil Ghosh , Robert I. McLachlan , David J. W. Simpson

This work presents a complete geometrical characterisation of divisible and indivisible time-evolution at the level of probabilities for systems with two configurations, open or closed. Our new geometrical construction in the space of…

Quantum Physics · Physics 2025-05-14 Leandro Silva Pimenta

We propose a novel approach to intrinsic decoherence without adding new assumptions to standard Quantum Mechanics. We generalize the Liouville equation just by requiring the dynamical semigroup property of time evolution and dropping the…

Quantum Physics · Physics 2015-06-26 Rodolfo Bonifacio

The large deviations properties of trajectory observables for chaotic non-invertible deterministic maps as studied recently by N. R. Smith, Phys. Rev. E 106, L042202 (2022) and by R. Gutierrez, A. Canella-Ortiz, C. Perez-Espigares,…

Statistical Mechanics · Physics 2024-01-30 Cecile Monthus

Estimating and quantifying uncertainty in unknown system parameters from limited data remains a challenging inverse problem in a variety of real-world applications. While many approaches focus on estimating constant parameters, a subset of…

Methodology · Statistics 2023-05-09 Andrea Arnold

In this letter we present a method of constructing dynamical systems with any preassigned number of equilibria by adding symmetry to another system with at least one equilibrium point. If the resulting system is chaotic, we call this…

Chaotic Dynamics · Physics 2012-09-03 Zeraoulia Elhadj , J. C. Sprott

The reconstruction from observations of high-dimensional chaotic dynamics such as geophysical flows is hampered by (i) the partial and noisy observations that can realistically be obtained, (ii) the need to learn from long time series of…

Machine Learning · Statistics 2020-03-31 Marc Bocquet , Julien Brajard , Alberto Carrassi , Laurent Bertino