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arxiv: 1505.05746 · v2 · pith:AX5SYDVNnew · submitted 2015-05-21 · 🧮 math.DS

Dimension approximation of attractors of graph directed IFSs by self-similar sets

classification 🧮 math.DS
keywords setsdirectedgraphself-similarvarepsilonapproximationassumeattractor
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We show that for the attractor $(K_{1},\dots,K_{q})$ of a graph directed iterated function system, for each $1\leq j\leq q$ and $\varepsilon>0$ there exits a self-similar set $K\subseteq K_{j}$ that satisfies the strong separation condition and $\dim_{H}K_{j}-\varepsilon<\dim_{H}K$. We show that we can further assume convenient conditions on the orthogonal parts and similarity ratios of the defining similarities of $K$. Using this property as a `black box' we obtain results on a range of topics including on dimensions of projections, intersections, distance sets and sums and products of sets.

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