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https://dx.doi.org/10.48550/ar...
Article . 2022
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Antisquares and Critical Exponents

Authors: Aseem Baranwal; James Currie; Lucas Mol; Pascal Ochem; Narad Rampersad; Jeffrey Shallit;

Antisquares and Critical Exponents

Abstract

The (bitwise) complement $\overline{x}$ of a binary word $x$ is obtained by changing each $0$ in $x$ to $1$ and vice versa. An $\textit{antisquare}$ is a nonempty word of the form $x\, \overline{x}$. In this paper, we study infinite binary words that do not contain arbitrarily large antisquares. For example, we show that the repetition threshold for the language of infinite binary words containing exactly two distinct antisquares is $(5+\sqrt{5})/2$. We also study repetition thresholds for related classes, where "two" in the previous sentence is replaced by a larger number. We say a binary word is $\textit{good}$ if the only antisquares it contains are $01$ and $10$. We characterize the minimal antisquares, that is, those words that are antisquares but all proper factors are good. We determine the growth rate of the number of good words of length $n$ and determine the repetition threshold between polynomial and exponential growth for the number of good words.

Keywords

FOS: Computer and information sciences, Discrete Mathematics (cs.DM), Formal Languages and Automata Theory (cs.FL), mathematics - combinatorics, Computer Science - Formal Languages and Automata Theory, computer science - discrete mathematics, computer science - formal languages and automata theory, QA1-939, FOS: Mathematics, Mathematics - Combinatorics, Combinatorics (math.CO), Mathematics, Computer Science - Discrete Mathematics

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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