We consider the problem of counting the number of copies of a fixed graph $H$ within an input graph $G$. This is one of the most well-studied algorithmic graph problems, with many theoretical and practical applications. We focus on solving this problem when the input $G$ has bounded degeneracy. This is a rich family of graphs, containing all graphs without a fixed minor (e.g. planar graphs), as well as graphs generated by various random processes (e.g. preferential attachment graphs). We say that $H$ is easy if there is a linear-time algorithm for counting the number of copies of $H$ in an input $G$ of bounded degeneracy. A seminal result of Chiba and Nishizeki from '85 states that every $H$ on at most 4 vertices is easy. Bera, Pashanasangi, and Seshadhri recently extended this to all $H$ on 5 vertices, and further proved that for every $k > 5$ there is a $k$-vertex $H$ which is not easy. They left open the natural problem of characterizing all easy graphs $H$. Bressan has recently introduced a framework for counting subgraphs in degenerate graphs, from which one can extract a sufficient condition for a graph $H$ to be easy. Here we show that this sufficient condition is also necessary, thus fully answering the Bera--Pashanasangi--Seshadhri problem. We further resolve two closely related problems; namely characterizing the graphs that are easy with respect to counting induced copies, and with respect to counting homomorphisms. Our proofs rely on several novel approaches for proving hardness results in the context of subgraph-counting.
翻译:我们考虑的是固定图形($H美元)在输入图形($G$)中计算复制件数量的问题。这是在很多理论和实践应用中最受研究的算法图表问题之一。当输入($G$)已经捆绑了退化性时,我们专注于解决这个问题。这是一个丰富的图表组合,包含所有没有固定小数的图表(如平面图)以及各种随机流程(如优惠附件图)产生的图表(如优惠附件图),我们说,如果在输入(a)中计算美元($H)复制件的线性时间算法是容易的。当输入($G$)被捆绑定的解算时,我们集中解决这个问题。85年的Chiba和Nishizizeki的原始结果显示,每4个旋转1美元就很容易。Bera、Pashanasanangi和Seshadrihri最近将这一问题扩大到5H美元,并进一步证明,每折价中的每一美元就必然有5美元。我们不断计算一个硬面值($-hex-$)的解算出一个硬的硬度,这在图表中也很容易。