2019
DOI: 10.3934/dcds.2019083
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Effect of quantified irreducibility on the computability of subshift entropy

Abstract: We study the difficulty of computing topological entropy of subshifts subjected to mixing restrictions. This problem is well-studied for multidimensional subshifts of finite type: there exists a threshold in the irreducibility rate where the difficulty jumps from computable to uncomputable, but its location is an open problem. In this paper, we establish the location of this threshold for a more general class, subshifts with decidable languages, in any dimension.

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Cited by 30 publications
(12 citation statements)
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“…Proof. This follows from the proof of Theorem 3.7 in [15]. We now show how to "encode" decidable mixing subshifts onto computable maps of the Cantor set.…”
Section: Upper Bound On the Minimal Cardinality Of A Sub-cover Ofmentioning
confidence: 85%
“…Proof. This follows from the proof of Theorem 3.7 in [15]. We now show how to "encode" decidable mixing subshifts onto computable maps of the Cantor set.…”
Section: Upper Bound On the Minimal Cardinality Of A Sub-cover Ofmentioning
confidence: 85%
“…[12] with [6] or [18]) by breaking our ability to embed computation. In particular, finding the border where the difficulty jump occurs gives a fine understanding of the effect of the restriction [7].…”
Section: Introductionmentioning
confidence: 99%
“…Once again, dynamical constraints are another relevant parameter: under strong irreducibility constraints, such as being block gluing, the entropy becomes computable [PS15]. It is possible to extend the notion of block gluingness by adding a gap function f that yields the distance f (n) which allows for the concatenation of two rectangular blocks of size n of the language: depending on the asymptotic behavior of f (n), the set of entropies can be either any Π 1 -computable number or only some computable numbers [Gd19]. The exact frontier for this parametrization is only known for subshifts with decidable language [GS20].…”
Section: Introductionmentioning
confidence: 99%