Besicovitch subsets of self-similar sets

@article{Ma2002,
abstract = {Let $E$ be a self-similar set with similarities ratio $r_j (0\le j\le m-1)$ and Hausdorff dimension $s$, let $\vec\{p\}(p_0,p_1)\ldots p_\{m-1\}$ be a probability vector. The Besicovitch-type subset of $E$ is defined as\[E(\vec\{p\})=\Big \lbrace x\in E\colon \lim \_\{n\rightarrow \infty \}\{1\over n\} \sum \_\{k=1\}^\{n\}\chi \_\{j\}(x\_k)=p\_j,\quad 0\le j\le m- 1\Big \rbrace ,\]where $\chi _j$ is the indicator function of the set $\lbrace j\rbrace $. Let $\alpha =\dim _H(E(\vec\{p\}))=\dim _P(E(\vec\{p\})) =\{\sum _\{j=0\}^\{m-1\} p_j\log p_j\over \sum _\{j=0\}^\{m- 1\}p_i \log r_j\}$ and $g$ be a gauge function, then we prove in this paper:(i) If $\vec\{p\}=(r_0^s,r_1^s,\cdots ,r_\{m-1\}^s)$, then\[\{\mathcal \{H\}\}^s(E(\vec\{p\}))=\{\mathcal \{H\}\}^s(E),\;\{\mathcal \{P\}\}^s(E(\vec\{p\}))=\{\mathcal \{P\}\}^s(E),\]moreover both of $\{\mathcal \{H\}\}^s(E)$ and $\{\mathcal \{P\}\}^s(E)$ are finite positive;(ii) If $\vec\{p\}$ is a positive probability vector other than $(r_0^s,r_1^s,\cdots ,r_\{m-1\}^s)$, then the gauge functions can be partitioned as follows\begin\{equation*\} \{\mathcal \{H\}\}^g(E(\vec\{p\}))=+\infty \iff \mathop \{\overline\{\rm lim\}\}\_\{t\rightarrow 0\}\{\log g(t)\over \log t\}\le \alpha ;\ \{\mathcal \{H\}\}^g(E(\vec\{p\}))=0 \Longleftrightarrow \mathop \{\overline\{\rm lim\}\}\_\{t\rightarrow 0\}\{\log g(t)\over \log t\}>\alpha , \end\{equation*\}\begin\{equation*\} \{\mathcal \{P\}\}^g(E(\vec\{p\}))=+\infty \Longleftrightarrow \mathop \{\underline\{\rm lim\}\}\_\{t\rightarrow 0\}\{\log g(t)\over \log t\}\le \alpha ;\ \{\mathcal \{P\}\}^g(E(\vec\{p\}))=0 \Longleftrightarrow \mathop \{\underline\{\rm lim\}\}\_\{t\rightarrow 0\}\{\log g(t)\over \log t\}>\alpha . \end\{equation*\}},
affiliation = {Wuhan University, Department of Mathematics, Wuhan 430072 (Rép. Pop. Chine); Tsinghua University, Department of mathematics, Beijing 10084 (Rép. Pop. Chine); Wuhan University, Department of Mathematics, Wuhan 430072 (Rép. Pop. Chine)},
author = {Ma, Ji-Hua, Wen, Zhi-Ying, Wu, Jun},
journal = {Annales de l’institut Fourier},
keywords = {perturbation measures; gauge functions; Besicovitch set; Besicovitch sets; normal numbers; Hausdorff measures},
language = {eng},
number = {4},
pages = {1061-1074},
publisher = {Association des Annales de l'Institut Fourier},
title = {Besicovitch subsets of self-similar sets},
url = {http://eudml.org/doc/116003},
volume = {52},
year = {2002},
}

TY - JOUR
AU - Ma, Ji-Hua
AU - Wen, Zhi-Ying
AU - Wu, Jun
TI - Besicovitch subsets of self-similar sets
JO - Annales de l’institut Fourier
PY - 2002
PB - Association des Annales de l'Institut Fourier
VL - 52
IS - 4
SP - 1061
EP - 1074
AB - Let $E$ be a self-similar set with similarities ratio $r_j (0\le j\le m-1)$ and Hausdorff dimension $s$, let $\vec{p}(p_0,p_1)\ldots p_{m-1}$ be a probability vector. The Besicovitch-type subset of $E$ is defined as\[E(\vec{p})=\Big \lbrace x\in E\colon \lim _{n\rightarrow \infty }{1\over n} \sum _{k=1}^{n}\chi _{j}(x_k)=p_j,\quad 0\le j\le m- 1\Big \rbrace ,\]where $\chi _j$ is the indicator function of the set $\lbrace j\rbrace $. Let $\alpha =\dim _H(E(\vec{p}))=\dim _P(E(\vec{p})) ={\sum _{j=0}^{m-1} p_j\log p_j\over \sum _{j=0}^{m- 1}p_i \log r_j}$ and $g$ be a gauge function, then we prove in this paper:(i) If $\vec{p}=(r_0^s,r_1^s,\cdots ,r_{m-1}^s)$, then\[{\mathcal {H}}^s(E(\vec{p}))={\mathcal {H}}^s(E),\;{\mathcal {P}}^s(E(\vec{p}))={\mathcal {P}}^s(E),\]moreover both of ${\mathcal {H}}^s(E)$ and ${\mathcal {P}}^s(E)$ are finite positive;(ii) If $\vec{p}$ is a positive probability vector other than $(r_0^s,r_1^s,\cdots ,r_{m-1}^s)$, then the gauge functions can be partitioned as follows\begin{equation*} {\mathcal {H}}^g(E(\vec{p}))=+\infty \iff \mathop {\overline{\rm lim}}_{t\rightarrow 0}{\log g(t)\over \log t}\le \alpha ;\ {\mathcal {H}}^g(E(\vec{p}))=0 \Longleftrightarrow \mathop {\overline{\rm lim}}_{t\rightarrow 0}{\log g(t)\over \log t}>\alpha , \end{equation*}\begin{equation*} {\mathcal {P}}^g(E(\vec{p}))=+\infty \Longleftrightarrow \mathop {\underline{\rm lim}}_{t\rightarrow 0}{\log g(t)\over \log t}\le \alpha ;\ {\mathcal {P}}^g(E(\vec{p}))=0 \Longleftrightarrow \mathop {\underline{\rm lim}}_{t\rightarrow 0}{\log g(t)\over \log t}>\alpha . \end{equation*}
LA - eng
KW - perturbation measures; gauge functions; Besicovitch set; Besicovitch sets; normal numbers; Hausdorff measures
UR - http://eudml.org/doc/116003
ER -