Sierpinski地毯上自相似测度以及Markov测度的加倍性质

Doubling properties of self-similar measures and Markov measures on Sierpinski carpets

众所周知,当自相似集满足强分离条件时,其上的自相似测度都是加倍的.本文进一步证明在强分离条件下,自相似集上的Markov测度都是加倍的.随后,本文讨论了Sierpinski地毯S上自相似测度及Markov测度的加倍性质.当S不满足强分离条件时,将S分为不同的类型,完全刻画了S上加倍的自相似测度及加倍的Markov测度.

As is well known, when a self-similar set satisfies the strong separation condition, all self-similar measures are doubling. In this paper, we further prove that all Markov measures are doubling on a self-similar set with the strong separation condition. Subsequently, we focus on self-similar measures and Markov measures on Sierpinski carpets. Without the strong separation condition, Sierpinski carpets can be divided into different types. In each case, we fully characterize doubling self-similar measures and doubling Markov measures on a Sierpifiski carpet.