Dense Peelable Random Uniform Hypergraphs
Dense Peelable Random Uniform Hypergraphs
复制标题
密集可剥离随机均匀超图
DOI:
10.4230/lipics.esa.2019.38
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发表时间:
2019
期刊:
影响因子:
--
通讯作者:
Stefan Walzer
中科院分区:
文献类型:
--
作者:
Martin Dietzfelbinger;Stefan Walzer
We describe a new family of $k$-uniform hypergraphs with independent random edges. The hypergraphs have a high probability of being peelable, i.e. to admit no sub-hypergraph of minimum degree $2$, even when the edge density (number of edges over vertices) is close to $1$. In our construction, the vertex set is partitioned into linearly arranged segments and each edge is incident to random vertices of $k$ consecutive segments. Quite surprisingly, the linear geometry allows our graphs to be peeled "from the outside in". The density thresholds $f_k$ for peelability of our hypergraphs ($f_3 \approx 0.918$, $f_4 \approx 0.977$, $f_5 \approx 0.992$, ...) are well beyond the corresponding thresholds ($c_3 \approx 0.818$, $c_4 \approx 0.772$, $c_5 \approx 0.702$, ...) of standard $k$-uniform random hypergraphs. To get a grip on $f_k$, we analyse an idealised peeling process on the random weak limit of our hypergraph family. The process can be described in terms of an operator on functions and $f_k$ can be linked to thresholds relating to the operator. These thresholds are then tractable with numerical methods.
Random hypergraphs underlie the construction of various data structures based on hashing. These data structures frequently rely on peelability of the hypergraph or peelability allows for simple linear time algorithms. To demonstrate the usefulness of our construction, we used our $3$-uniform hypergraphs as a drop-in replacement for the standard $3$-uniform hypergraphs in a retrieval data structure by Botelho et al. This reduces memory usage from $1.23m$ bits to $1.12m$ bits ($m$ being the input size) with almost no change in running time.
DOI:
10.1007/978-3-540-70575-8_32
发表时间:
2008
期刊:
影响因子:
--
作者:
Martin Dietzfelbinger;Rasmus Pagh
通讯作者:
Rasmus Pagh
影响因子:
0.5
作者:
Martin Dietzfelbinger;Michael Rink
通讯作者:
Michael Rink
DOI:
10.1007/978-3-642-35843-2_31
发表时间:
2013
期刊:
影响因子:
--
作者:
Michael Rink
通讯作者:
Michael Rink