论文标题
（理论上）弱混合等级的单词复杂性的单词复杂性
Word Complexity of (Measure-Theoretically) Weakly Mixing Rank-One Subshifts
论文作者
论文摘要
我们展示了弱混合（概率）度量的次班，对于任意$ε> 0 $，带有单词复杂性$ p $满足$ \ limsup \ frac \ frac {p（q）} {q} {q} <1.5 +ε$。对于任意的$ f（q）\至\ infty $，可以进行乘坐$ p（q）<q + f（q）$无限频繁地满足。 我们确定与排名第一转换（在概率空间上）相关的每个子班，这不是里程表都满足$ \ limsup p（q）-1.5q = \ infty $，这对于等级式是最佳的。
We exhibit subshifts admitting weakly mixing (probability) measures, for arbitrary $ε> 0$, with word complexity $p$ satisfying $\limsup \frac{p(q)}{q} < 1.5 + ε$. For arbitrary $f(q) \to \infty$, said subshifts can be made to satisfy $p(q) < q + f(q)$ infinitely often. We establish that every subshift associated to a rank-one transformation (on a probability space) which is not an odometer satisfies $\limsup p(q) - 1.5q = \infty$ and that this is optimal for rank-ones.
