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arXiv 1007.4230cs.DScs.DM
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次线性时间中的圈与树

Finding Cycles and Trees in Sublinear Time

Artur Czumaj, Oded Goldreich, Dana Ron, C. Seshadhri, Asaf Shapira, Christian Sohler

摘要:

我们提出了次线性时间(随机)算法,找到简单的周期长度至少$k\geq 3$和树未成年人在有界度图。这些算法的复杂度与图距无$C_k$ -次要者的距离有关(分别地,不具有相应的树子)。特别地,如果图是远的(即,$Ω(1)$(远){from}是无环的,即,如果必须删除边的恒定部分以使其无环,则该算法找到时间上的多对数长度的循环$\tildeO(\sqrt{N})$,其中$N$表示顶点的数量。这个时间复杂度对于多对数因子来说是最优的。上述结果是我们在有界度图模型中研究{ \em单侧误差}属性测试算法复杂性的结果。例如,我们证明了$N$顶点图的无圈性可以在时间复杂度$\tildeO(\poly(1/\e)\cdot\sqrt{N})$内用单侧误差进行测试。这与已知的$Ω(\sqrt{N})$查询下限相匹配,并且与以下事实形成对比:任何无次项属性都允许查询复杂性的{ \em双侧误差}测试器仅取决于邻近参数$\e$。对于任何常数$k\geq3$,我们将这个结果扩展到测试输入图是否具有长度至少为$k$的简单循环。另一方面,对于任何固定的树$T$,我们表明,$T$ -未成年人的自由度有一个单侧错误测试的查询复杂性,只依赖于接近参数$\e$。我们的算法在有界度图中找到循环扩展到一般的图形,距离测量相对于实际的边缘数。这样的扩展对于在$o(\sqrt{N})$复杂度中寻找树-子式是不可能的。

英文摘要:

We present sublinear-time (randomized) algorithms for finding simple cycles of length at least $k\geq 3$ and tree-minors in bounded-degree graphs. The complexity of these algorithms is related to the distance of the graph from being $C_k$-minor-free (resp., free from having the corresponding tree-minor). In particular, if the graph is far (i.e., $Ω(1)$-far) {from} being cycle-free, i.e. if one has to delete a constant fraction of edges to make it cycle-free, then the algorithm finds a cycle of polylogarithmic length in time $\tildeO(\sqrt{N})$, where $N$ denotes the number of vertices. This time complexity is optimal up to polylogarithmic factors. The foregoing results are the outcome of our study of the complexity of {\em one-sided error} property testing algorithms in the bounded-degree graphs model. For example, we show that cycle-freeness of $N$-vertex graphs can be tested with one-sided error within time complexity $\tildeO(\poly(1/\e)\cdot\sqrt{N})$. This matches the known $Ω(\sqrt{N})$ query lower bound, and contrasts with the fact that any minor-free property admits a {\em two-sided error} tester of query complexity that only depends on the proximity parameter $\e$. For any constant $k\geq3$, we extend this result to testing whether the input graph has a simple cycle of length at least $k$. On the other hand, for any fixed tree $T$, we show that $T$-minor-freeness has a one-sided error tester of query complexity that only depends on the proximity parameter $\e$. Our algorithm for finding cycles in bounded-degree graphs extends to general graphs, where distances are measured with respect to the actual number of edges. Such an extension is not possible with respect to finding tree-minors in $o(\sqrt{N})$ complexity.

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