English

Finding and Counting Patterns in Sparse Graphs

Data Structures and Algorithms 2023-01-09 v1 Computational Complexity

Abstract

We consider algorithms for finding and counting small, fixed graphs in sparse host graphs. In the non-sparse setting, the parameters treedepth and treewidth play a crucial role in fast, constant-space and polynomial-space algorithms respectively. We discover two new parameters that we call matched treedepth and matched treewidth. We show that finding and counting patterns with low matched treedepth and low matched treewidth can be done asymptotically faster than the existing algorithms when the host graphs are sparse for many patterns. As an application to finding and counting fixed-size patterns, we discover \otilde(m3)\otilde(m^3)-time \footnote{\otilde\otilde hides factors that are logarithmic in the input size.}, constant-space algorithms for cycles of length at most 1111 and \otilde(m2)\otilde(m^2)-time, polynomial-space algorithms for paths of length at most 1010.

Keywords

Cite

@article{arxiv.2301.02569,
  title  = {Finding and Counting Patterns in Sparse Graphs},
  author = {Balagopal Komarath and Anant Kumar and Suchismita Mishra and Aditi Sethia},
  journal= {arXiv preprint arXiv:2301.02569},
  year   = {2023}
}