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The striking fractal geometry of strange attractors underscores the generative nature of chaos: like probability distributions, chaotic systems can be repeatedly measured to produce arbitrarily-detailed information about the underlying…

Machine Learning · Computer Science 2023-01-31 William Gilpin

We review the occurrence of the patterns of the onset of chaos in low-dimensional nonlinear dissipative systems in leading topics of condensed matter physics and complex systems of various disciplines. We consider the dynamics associated…

Statistical Mechanics · Physics 2018-11-14 Carlos Velarde , Alberto Robledo

Recently, neural networks (NNs) have become a powerful tool for detecting quantum phases of matter. Unfortunately, NNs are black boxes and only identify phases without elucidating their properties. Novel physics benefits most from insights…

Quantum Physics · Physics 2024-11-05 Kacper Cybiński , James Enouen , Antoine Georges , Anna Dawid

The brain efficiently performs nonlinear computations through its intricate networks of spiking neurons, but how this is done remains elusive. While nonlinear computations can be implemented successfully in spiking neural networks, this…

Neurons and Cognition · Quantitative Biology 2021-11-23 Michele Nardin , James W Phillips , William F Podlaski , Sander W Keemink

We quantify the finite size effects in a stochastic network made up of rate neurons, for several kinds of recurrent connectivity matrices. This analysis is performed by means of a perturbative expansion of the neural equations, where the…

Dynamical Systems · Mathematics 2013-07-09 D. Fasoli , O. Faugeras

Recently, nonnegative matrix factorization (NMF) has been widely adopted for community detection, because of its better interpretability. However, the existing NMF-based methods have the following three problems: 1) they directly transform…

Machine Learning · Computer Science 2024-02-15 Yuecheng Li , Jialong Chen , Chuan Chen , Lei Yang , Zibin Zheng

Spherical convolutional neural networks (Spherical CNNs) learn nonlinear representations from 3D data by exploiting the data structure and have shown promising performance in shape analysis, object classification, and planning among others.…

Machine Learning · Computer Science 2021-04-06 Zhan Gao , Fernando Gama , Alejandro Ribeiro

We report experimental evidence of the route to spatiotemporal chaos in a large 1D-array of hotspots in a thermoconvective system. Increasing the driving force, a stationary cellular pattern becomes unstable towards a mixed pattern of…

Chaotic Dynamics · Physics 2011-03-10 M. A. Miranda , J. Burguete

Chaotic oscillators have gained significant attention in the research community because of their ability to reproduce and investigate the complex dynamics of real-world phenomena. Recent advances in the design of chaotic oscillator…

Chaotic Dynamics · Physics 2026-03-19 Toni Ivas , Georgios Violakis , Roland Richter , Patrik Hoffmann , Sergey Shevchik

In recent years, a lot of research has gone into creating multi-layer chaotic mapping-based cryptosystems. Random-like behavior, a continuous broadband power spectrum, and a weak baseline condition dependency are all characteristics of…

Cryptography and Security · Computer Science 2022-08-15 Awnon Bhowmik , Emon Hossain , Mahmudul Hasan

In this paper we present an analytical study on the synchronization dynamics observed in unidirectionally-coupled quasiperiodically-forced systems that exhibit Strange Non-chaotic Attractors (SNA) in their dynamics. The SNA dynamics…

Chaotic Dynamics · Physics 2016-12-23 G. Sivaganesh , A. Arulgnanam

Based on the principle of chaotification for continuous-time autonomous systems, which relies on two basic properties of chaos, i.e., globally bounded with necessary positive-zero-negative Lyapunov exponents, this paper derives a feasible…

Chaotic Dynamics · Physics 2016-12-21 Simin Yu , Guanrong Chen

Further analysis and experimentation is carried out in this paper for a chaotic dynamic model, viz. the Nonlinear Dynamic State neuron (NDS). The analysis and experimentations are performed to further understand the underlying dynamics of…

Neural and Evolutionary Computing · Computer Science 2014-08-19 Mohammad Alhawarat , Waleed Nazih , Mohammad Eldesouki

Chaos provides many interesting properties that can be used to achieve computational tasks. Such properties are sensitivity to initial conditions, space filling, control and synchronization. Chaotic neural models have been devised to…

Neural and Evolutionary Computing · Computer Science 2015-01-12 M. Alhawarat , T. Olde Scheper , N. T. Crook

The spectral form factor (SFF) is a powerful diagnostic of random matrix behavior in quantum many-body systems. We introduce a family of random circuit ensembles whose SFFs can be computed \textit{exactly}. These ensembles describe the…

Statistical Mechanics · Physics 2025-04-24 Tatsuhiko N. Ikeda , Lev Vidmar , Michael O. Flynn

Nonlinear system identification often involves a fundamental trade-off between interpretability and flexibility, often requiring the incorporation of physical constraints. We propose a unified data-driven framework that combines the…

Machine Learning · Computer Science 2025-09-16 Federico J. Gonzalez , Luis P. Lara

Chaotic dynamics is widely used to design pseudo-random number generators and for other applications such as secure communications and encryption. This paper aims to study the dynamics of discrete-time chaotic maps in the digital (i.e.,…

Cryptography and Security · Computer Science 2018-12-19 Chengqing Li , Bingbing Feng , Shujun Li , Juergen Kurths , Guanrong Chen

We study the monotone skew-product semiflow generated by a family of neutral functional differential equations with infinite delay and stable D-operator. The stability properties of D allow us to introduce a new order and to take the…

Dynamical Systems · Mathematics 2024-02-01 Víctor Muñoz-Villarragut , Sylvia Novo , Rafael Obaya

Pairs of numerically computed trajectories of a chaotic system may coalesce because of finite arithmetic precision. We analyse an example of this phenomenon, showing that it occurs surprisingly frequently. We argue that our model belongs to…

Chaotic Dynamics · Physics 2020-08-26 Bruce N. Roth , Michael Wilkinson

Non-integrability in the sense of dynamical systems, also known as dynamical chaos, is a strongly nonlinear qualitative phenomenon. Its most promising theoretical descriptions are likely to emerge from non-perturbative approaches, with…

High Energy Physics - Theory · Physics 2025-03-25 Igor V. Ovchinnikov