5,341 research outputs found
Quantum Cellular Automata
Quantum cellular automata (QCA) are reviewed, including early and more recent
proposals. QCA are a generalization of (classical) cellular automata (CA) and
in particular of reversible CA. The latter are reviewed shortly. An overview is
given over early attempts by various authors to define one-dimensional QCA.
These turned out to have serious shortcomings which are discussed as well.
Various proposals subsequently put forward by a number of authors for a general
definition of one- and higher-dimensional QCA are reviewed and their properties
such as universality and reversibility are discussed.Comment: 12 pages, 3 figures. To appear in the Springer Encyclopedia of
Complexity and Systems Scienc
Cellular Automata Models of Road Traffic
In this paper, we give an elaborate and understandable review of traffic
cellular automata (TCA) models, which are a class of computationally efficient
microscopic traffic flow models. TCA models arise from the physics discipline
of statistical mechanics, having the goal of reproducing the correct
macroscopic behaviour based on a minimal description of microscopic
interactions. After giving an overview of cellular automata (CA) models, their
background and physical setup, we introduce the mathematical notations, show
how to perform measurements on a TCA model's lattice of cells, as well as how
to convert these quantities into real-world units and vice versa. The majority
of this paper then relays an extensive account of the behavioural aspects of
several TCA models encountered in literature. Already, several reviews of TCA
models exist, but none of them consider all the models exclusively from the
behavioural point of view. In this respect, our overview fills this void, as it
focusses on the behaviour of the TCA models, by means of time-space and
phase-space diagrams, and histograms showing the distributions of vehicles'
speeds, space, and time gaps. In the report, we subsequently give a concise
overview of TCA models that are employed in a multi-lane setting, and some of
the TCA models used to describe city traffic as a two-dimensional grid of
cells, or as a road network with explicitly modelled intersections. The final
part of the paper illustrates some of the more common analytical approximations
to single-cell TCA models.Comment: Accepted for publication in "Physics Reports". A version of this
paper with high-quality images can be found at: http://phdsven.dyns.cx (go to
"Papers written"
An Objective Definition of Damage Spreading - Application to Directed Percolation
We present a general definition of damage spreading in a pair of models.
Using this general framework, one can define damage spreading in an objective
manner, that does not depend on the particular dynamic procedure that is being
used. The formalism is applied to the Domany-Kinzel cellular automaton in one
dimension; the active phase of this model is shown to consist of three
sub-phases, characterized by different damage-spreading properties.Comment: 10 pages, RevTex, 2 ps figure
Simply modified GKL density classifiers that reach consensus faster
The two-state Gacs-Kurdyumov-Levin (GKL) cellular automaton has been a staple
model in the study of complex systems due to its ability to classify binary
arrays of symbols according to their initial density. We show that a class of
modified GKL models over extended neighborhoods, but still involving only three
cells at a time, achieves comparable density classification performance but in
some cases reach consensus more than twice as fast. Our results suggest the
time to consensus (relative to the length of the CA) as a complementary measure
of density classification performance.Comment: Short note, 3 pages, 1 table, 2 composite figures, 18 reference
Cellular Automata Applications in Shortest Path Problem
Cellular Automata (CAs) are computational models that can capture the
essential features of systems in which global behavior emerges from the
collective effect of simple components, which interact locally. During the last
decades, CAs have been extensively used for mimicking several natural processes
and systems to find fine solutions in many complex hard to solve computer
science and engineering problems. Among them, the shortest path problem is one
of the most pronounced and highly studied problems that scientists have been
trying to tackle by using a plethora of methodologies and even unconventional
approaches. The proposed solutions are mainly justified by their ability to
provide a correct solution in a better time complexity than the renowned
Dijkstra's algorithm. Although there is a wide variety regarding the
algorithmic complexity of the algorithms suggested, spanning from simplistic
graph traversal algorithms to complex nature inspired and bio-mimicking
algorithms, in this chapter we focus on the successful application of CAs to
shortest path problem as found in various diverse disciplines like computer
science, swarm robotics, computer networks, decision science and biomimicking
of biological organisms' behaviour. In particular, an introduction on the first
CA-based algorithm tackling the shortest path problem is provided in detail.
After the short presentation of shortest path algorithms arriving from the
relaxization of the CAs principles, the application of the CA-based shortest
path definition on the coordinated motion of swarm robotics is also introduced.
Moreover, the CA based application of shortest path finding in computer
networks is presented in brief. Finally, a CA that models exactly the behavior
of a biological organism, namely the Physarum's behavior, finding the
minimum-length path between two points in a labyrinth is given.Comment: To appear in the book: Adamatzky, A (Ed.) Shortest path solvers. From
software to wetware. Springer, 201
A computational framework for aesthetical navigation in musical search space
Paper presented at 3rd AISB symposium on computational creativity, AISB 2016, 4-6th April, Sheffield. Abstract. This article addresses aspects of an ongoing project in the generation of artificial Persian (-like) music. Liquid Persian Music software (LPM) is a cellular automata based audio generator. In this paper LPM is discussed from the view point of future potentials of algorithmic composition and creativity. Liquid Persian Music is a creative tool, enabling exploration of emergent audio through new dimensions of music composition. Various configurations of the system produce different voices which resemble musical motives in many respects. Aesthetical measurements are determined by Zipf’s law in an evolutionary environment. Arranging these voices together for producing a musical corpus can be considered as a search problem in the LPM outputs space of musical possibilities. On this account, the issues toward defining the search space for LPM is studied throughout this paper
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