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Deterministic Algorithms for Unique Sink Orientations of Grids

机译:网格唯一水槽取向的确定性算法

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We study Unique Sink Orientations (USOs) of grids: Cartesian products of two complete graphs on n vertices, where the edges are oriented in such a way that each subgrid has a unique sink. We consider two different oracle models, the edge query and the vertex query model. An edge query provides the orientation of the queried edge, whereas a vertex query provides the orientation of all edges incident to the queried vertex. We are interested in bounding the number of queries to the oracle needed by an algorithm to find the sink. In the randomized setting, the best known algorithms find the sink using either Θ(n) edge queries, or O(log~2 n) vertex queries, in expectation. We prove that O(n~(log_4~7)) edge queries and O(n log n) vertex queries suffice to find the sink in the deterministic setting. A deterministic lower bound for both models is Ω(n). Grid USOs are instances of LP-type problems and violator spaces for which derandomizations of known algorithms remain elusive.
机译:我们研究了网格的独特水槽方向(USOS):在N顶点上的两个完整图表的笛卡尔产品,边缘以每个子耕作有一个独特的水槽为定向。我们考虑两个不同的Oracle模型,边缘查询和顶点查询模型。边缘查询提供查询边缘的方向,而顶点查询提供了引发到查询顶点的所有边缘的方向。我们有兴趣将算法所需的oracle次数绑定以找到接收器。在随机设置中,最着名的算法使用θ(n)边缘查询或o(log〜2 n)顶点查询,在期望中找到宿。我们证明O(n〜(log_4〜7))边缘查询和o(n log n)顶点查询足以在确定性设置中找到宿。两个模型的确定性下限是ω(n)。网格USOS是LP类型问题和违规空间的实例,其中已知算法的Deransomizats仍然难以捉摸。

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