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New insight into the correspondence between Quantum Chaos and Random Matrix Theory is gained by developing a semiclassical theory for the autocorrelation function of spectral determinants. We study in particular the unitary operators which…

chao-dyn · Physics 2016-08-31 U. Smilansky

Cellular automata have been useful artificial models for exploring how relatively simple rules combined with spatial memory can give rise to complex emergent patterns. Moreover, studying the dynamics of how rules emerge under artificial…

Cellular Automata and Lattice Gases · Physics 2014-07-11 Theodore P. Pavlic , Alyssa M. Adams , Paul C. W. Davies , Sara Imari Walker

We give a categorical description of all abelian varieties with commutative endomorphism ring over a finite field with $q=p^a$ elements in a fixed isogeny class in terms of pairs consisting of a fractional $\mathbb Z[\pi,q/\pi]$-ideal and a…

Number Theory · Mathematics 2025-08-05 Jonas Bergström , Valentijn Karemaker , Stefano Marseglia

In this dissertation, we study two of the global properties of 1-dimensional cellular automata (CAs) under periodic boundary condition, namely, reversibility and randomness. To address reversibility of finite CAs, we develop a mathematical…

Formal Languages and Automata Theory · Computer Science 2019-11-12 Kamalika Bhattacharjee

Recursive algorithms for computing the Frobenius norm of a real array are proposed, based on hypot, a hypotenuse function. Comparing their relative accuracy bounds with those of the BLAS routine DNRM2 it is shown that the proposed…

Numerical Analysis · Mathematics 2026-05-13 Vedran Novaković

A new class of deterministic dynamical systems, termed semipredictable dynamical systems, is presented. The spatiotemporal evolution of these systems have both predictable and unpredictable traits, as found in natural complex systems. We…

Chaotic Dynamics · Physics 2016-04-15 Vladimir García-Morales

Recursive equations for the number of cells with nonzero values at $n$-th step for some two-dimensional reversible second-order cellular automata are proved in this work. Initial configuration is a single cell with the value one and all…

Combinatorics · Mathematics 2014-07-31 Alexander Yu. Vlasov

Using the concept of the Boolean derivative we study damage spreading for one dimensional elementary cellular automata and define their maximal Lyapunov exponent. A random matrix approximation describes quite well the behavior of…

Statistical Mechanics · Physics 2007-05-23 F. Bagnoli , R. Rechtman , S. Ruffo

We report surprisingly regular behaviors observed for a class 4 cellular automaton, the totalistic rule 20: starting from disordered initial configurations the automaton produces patterns which are periodic not only in time but also in…

Statistical Mechanics · Physics 2009-11-11 Jason A. C. Gallas , Hans J. Herrmann

Morphogenesis of complex body shapes is reproducible despite the noise inherent in the underlying morphogenetic processes. However, how these morphogenetic processes work together to achieve this reproducibility remains unclear. Here, we…

Cell Behavior · Quantitative Biology 2025-12-24 Dominic K Devlin , Austen RD Ganley , Nobuto Takeuchi

The cellular automaton (CA) pulsing model (arXiv:1806.06416) described the surprising phenomenon of spontaneous, sustained and robust rhythmic oscillations, pulsing dynamics, when random wiring is applied to a 2D `glider' rule running in a…

Cellular Automata and Lattice Gases · Physics 2021-03-02 Andrew Wuensche , Edward Coxon

We propose a general method for constructing a fuzzy cellular automaton from a given cellular automaton. Unlike previous approaches that use fuzzy distinctive normal form, whose update function is restricted to third-order polynomials, our…

Cellular Automata and Lattice Gases · Physics 2026-01-26 Seiryu Shimizu , Tetsuji Tokihiro

In this paper we study the statistical properties of a reversible cellular automaton in two out-of-equilibrium settings. In the first part we consider two instances of the initial value problem, corresponding to the inhomogeneous quench and…

Statistical Mechanics · Physics 2019-06-26 Marko Medenjak , Vladislav Popkov , Tomaž Prosen , Eric Ragoucy , Matthieu Vanicat

Auto-regressive neural sequence models have been shown to be effective across text generation tasks. However, their left-to-right decoding order prevents generation from being parallelized. Insertion Transformer (Stern et al., 2019) is an…

Computation and Language · Computer Science 2023-02-01 Zhisong Zhang , Yizhe Zhang , Bill Dolan

This study presents an internalized morphogenesis model for autonomous systems, such as swarm robotics and micro-nanomachines, that eliminates the need for external spatial computation. Traditional self-organizing models often require…

Robotics · Computer Science 2026-02-09 Takeshi Ishida

Self-organization to ferromagnetic phase transition in cellular automata of spins governed by stochastic majority rule and when topology between spins is changed, is investigated numerically. Three types of edge rewiring are considered. The…

Statistical Mechanics · Physics 2007-05-23 Danuta Makowiec

This note is a survey of examples and results about cellular automata with the purpose of recalling that there is no 'universal' way of being computationally universal. In particular, we show how some cellular automata can embed efficient…

Computational Complexity · Computer Science 2021-12-03 Guillaume Theyssier

We study the problem of sequentializing a cellular automaton without introducing any intermediate states, and only performing reversible permutations on the tape. We give a decidable characterization of cellular automata which can be…

Dynamical Systems · Mathematics 2018-04-09 Jarkko Kari , Ville Salo , Thomas Worsch

In this work, we propose and analyze a class of distributed algorithms performing the joint optimization of radio resources in heterogeneous cellular networks made of a juxtaposition of macro and small cells. Within this context, it is…

Optimization and Control · Mathematics 2013-07-30 Chung Shue Chen , Francois Baccelli

We propose a machine-learning algorithm for Bayesian inverse problems in the function-space regime based on one-step generative transport. Building on the Mean Flows, we learn a fully conditional amortized sampler with a neural-operator…

Machine Learning · Statistics 2026-03-17 Zilan Cheng , Li-Lian Wang , Zhongjian Wang
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