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Cellular automata are synchronous discrete dynamical systems used to describe complex dynamic behaviors. The dynamic is based on local interactions between the components, these are defined by a finite graph with an initial node coloring…

Data Structures and Algorithms · Computer Science 2023-12-22 Volker Turau

Cellular automata are a set of computational models in discrete space that have a discrete time evolution defined by neighbourhood rules. They are used to simulate many complex systems in physics and science in general. In this work,…

Cellular Automata and Lattice Gases · Physics 2023-05-12 Luca Bertolani , Andrea Idini

A classical local cellular automaton can describe an interacting quantum field theory for fermions. We construct a simple classical automaton for a particular version of the Thirring model with imaginary coupling. This interacting fermionic…

Quantum Physics · Physics 2021-02-03 C. Wetterich

Convolutional networks are large linear systems divided into layers and connected by non-linear units. These units are the "articulations" that allow the network to adapt to the input. To understand how a network manages to solve a problem…

Computer Vision and Pattern Recognition · Computer Science 2019-11-15 Pablo Navarrete Michelini , Hanwen Liu , Yunhua Lu , Xingqun Jiang

We present algorithms for classification of linear codes over finite fields, based on canonical augmentation and on lattice point enumeration. We apply these algorithms to obtain classification results over fields with 2, 3 and 4 elements.…

Information Theory · Computer Science 2021-09-21 Iliya Bouyukliev , Stefka Bouyuklieva , Sascha Kurz

Here we propose an evolutionary algorithm that self modifies its operators at the same time that candidate solutions are evolved. This tackles convergence and lack of diversity issues, leading to better solutions. Operators are represented…

Neural and Evolutionary Computing · Computer Science 2017-12-19 Andres Felipe Cruz Salinas , Jonatan Gomez Perdomo

The convolution potential arises in a wide variety of application areas, and its efficient and accurate evaluation encounters three challenges: singularity, nonlocality and anisotropy. We introduce a fast algorithm based on a far-field…

Numerical Analysis · Mathematics 2025-04-29 Xin Liu , Yong Zhang

The search for symmetry as an unusual yet profoundly appealing phenomenon, and the origin of regular, repeating configuration patterns have long been a central focus of complexity science and physics. To better grasp and understand symmetry…

Cellular Automata and Lattice Gases · Physics 2019-07-01 Peter Banda , John Caughman , Martin Cenek , Christof Teuscher

Symmetry -- invariance to certain operators -- is a fundamental concept in many branches of physics. We propose ways to measure symmetric properties of vertices, and their surroundings, in networks. To be stable to the randomness inherent…

Disordered Systems and Neural Networks · Physics 2008-06-29 Petter Holme

Cellular automata are discrete and computational models thatcan be shown as general models of complexity. They are used in varied applications to derive the generalized behavior of the presented model. In this paper we have took one such…

Neural and Evolutionary Computing · Computer Science 2020-05-14 Karan Nayak

Non-relativistic conformally invariant systems in a rotating cosmic string (conical) spacetime are analyzed at the classical and quantum levels by means of the gravitoelectromagnetic interpretation of the background. Solutions of the…

High Energy Physics - Theory · Physics 2022-02-02 Luis Inzunza , Mikhail S. Plyushchay

A general mathematical method is presented for the systematic construction of coupled map lattices (CMLs) out of deterministic cellular automata (CAs). The entire CA rule space is addressed by means of a universal map for CAs that we have…

Cellular Automata and Lattice Gases · Physics 2016-06-09 Vladimir García-Morales

Take a cellular automaton, consider that each configuration is a basis vector in some vector space, and linearize the global evolution function. If lucky, the r esult could actually make sense physically, as a valid quantum evolution; but…

Quantum Physics · Physics 2009-03-03 Pablo Arrighi , Vincent Nesme

We present a novel surface convolution operator acting on vector fields that is based on a simple observation: instead of combining neighboring features with respect to a single coordinate parameterization defined at a given point, we have…

Computer Vision and Pattern Recognition · Computer Science 2021-09-17 Thomas W. Mitchel , Vladimir G. Kim , Michael Kazhdan

This paper contains an $L^{p}$ improving result for convolution operators defined by singular measures associated to hypersurfaces on the motion group. This needs only mild geometric properties of the surfaces, and it extends earlier…

Functional Analysis · Mathematics 2010-01-05 Luca Brandolini , Giacomo Gigante , Sundaram Thangavelu , Giancarlo Travaglini

A classification algorithm, called the Linear Centralization Classifier (LCC), is introduced. The algorithm seeks to find a transformation that best maps instances from the feature space to a space where they concentrate towards the center…

Machine Learning · Computer Science 2017-12-25 Mohammad Reza Bonyadi , Viktor Vegh , David C. Reutens

We introduce and study cellular automata whose cell spaces are left-homogeneous spaces. Examples of left-homogeneous spaces are spheres, Euclidean spaces, as well as hyperbolic spaces acted on by isometries; uniform tilings acted on by…

Group Theory · Mathematics 2017-06-27 Simon Wacker

Many natural shapes have most of their characterizing features concentrated over a few regions in space. For example, humans and animals have distinctive head shapes, while inorganic objects like chairs and airplanes are made of…

Computer Vision and Pattern Recognition · Computer Science 2022-06-27 Marco Pegoraro , Simone Melzi , Umberto Castellani , Riccardo Marin , Emanuele Rodolà

Deep learning techniques have recently demonstrated broad success in predicting complex dynamical systems ranging from turbulence to human speech, motivating broader questions about how neural networks encode and represent dynamical rules.…

Cellular Automata and Lattice Gases · Physics 2020-01-20 William Gilpin

Any algorithm (in the sense of Gurevich's abstract-state-machine axiomatization of classical algorithms) operating over any arbitrary unordered domain can be simulated by a dynamic cellular automaton, that is, by a pattern-directed cellular…

Logic in Computer Science · Computer Science 2015-04-14 Nachum Dershowitz , Evgenia Falkovich