In this paper, we study quantum algorithms for computing the exact value of the treewidth of a graph. Our algorithms are based on the classical algorithm by Fomin and Villanger (Combinatorica 32, 2012) that uses $O(2.616^n)$ time and polynomial space. We show three quantum algorithms with the following complexity, using QRAM in both exponential space algorithms: $\bullet$ $O(1.618^n)$ time and polynomial space; $\bullet$ $O(1.554^n)$ time and $O(1.452^n)$ space; $\bullet$ $O(1.538^n)$ time and space. In contrast, the fastest known classical algorithm for treewidth uses $O(1.755^n)$ time and space. The first two speed-ups are obtained in a fairly straightforward way. The first version uses additionally only Grover's search and provides a quadratic speedup. The second speedup is more time-efficient and uses both Grover's search and the quantum exponential dynamic programming by Ambainis et al. (SODA '19). The third version uses the specific properties of the classical algorithm and treewidth, with a modified version of the quantum dynamic programming on the hypercube. Lastly, as a small side result, we also give a new classical time-space tradeoff for computing treewidth in $O^*(2^n)$ time and $O^*(\sqrt{2^n})$ space.
翻译:在本文中,我们研究了用于计算图树枝准确值的量子算法。我们的算法基于Fomin和Villanger(Combinatorica 32,2012年)的经典算法(Combinatorica 32,2012年),使用O(2.616美元)美元的时间和多元空间。我们展示了三种具有以下复杂性的量子算法,在两个指数式空间算法中使用QRAM,使用下列复杂性的量子算法:$(1.618美元)时间和多元空间;美元(1.554美元)时间和美元(1.452美元)空间;美元(1.538美元)的时间和美元;美元(1.538美元)的时间和空间。相比之下,我们展示了三种已知最快的量子算算算法,在两种指数式空间算法中,前两种加速算法以比较简单的方式获得。第一版只使用格罗弗的侧搜索,提供二次加速速度。第二版是时间效率更高,同时使用格罗弗的搜索和克罗弗的(1.538美元) 时间。