2,513 research outputs found
Topology Inspired Problems for Cellular Automata, and a Counterexample in Topology
We consider two relatively natural topologizations of the set of all cellular
automata on a fixed alphabet. The first turns out to be rather pathological, in
that the countable space becomes neither first-countable nor sequential. Also,
reversible automata form a closed set, while surjective ones are dense. The
second topology, which is induced by a metric, is studied in more detail.
Continuity of composition (under certain restrictions) and inversion, as well
as closedness of the set of surjective automata, are proved, and some
counterexamples are given. We then generalize this space, in the sense that
every shift-invariant measure on the configuration space induces a pseudometric
on cellular automata, and study the properties of these spaces. We also
characterize the pseudometric spaces using the Besicovitch distance, and show a
connection to the first (pathological) space.Comment: In Proceedings AUTOMATA&JAC 2012, arXiv:1208.249
Applying causality principles to the axiomatization of probabilistic cellular automata
Cellular automata (CA) consist of an array of identical cells, each of which
may take one of a finite number of possible states. The entire array evolves in
discrete time steps by iterating a global evolution G. Further, this global
evolution G is required to be shift-invariant (it acts the same everywhere) and
causal (information cannot be transmitted faster than some fixed number of
cells per time step). At least in the classical, reversible and quantum cases,
these two top-down axiomatic conditions are sufficient to entail more
bottom-up, operational descriptions of G. We investigate whether the same is
true in the probabilistic case. Keywords: Characterization, noise, Markov
process, stochastic Einstein locality, screening-off, common cause principle,
non-signalling, Multi-party non-local box.Comment: 13 pages, 6 figures, LaTeX, v2: refs adde
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