The Computational Complexity of Factored Graphs
<|reference_start|>The Computational Complexity of Factored Graphs: While graphs and abstract data structures can be large and complex, practical instances are often regular or highly structured. If the instance has sufficient structure, we might hope to compress the object into a more succinct representation. An efficient algorithm (with respect to the compressed input size) could then lead to more efficient computations than algorithms taking the explicit, uncompressed object as input. This leads to a natural question: when does knowing the input instance has a more succinct representation make computation easier?   We initiate the study of the computational complexity of problems on factored graphs: graphs that are given as a formula of products and unions on smaller graphs. For any graph problem, we define a parameterized version that takes factored graphs as input, parameterized by the number of smaller graphs used to construct the factored graph. In this setting, we characterize the parameterized complexity of several natural graph problems, exhibiting a variety of complexities. We show that a decision version of lexicographically first maximal independent set is unconditionally XP-complete, and therefore not fixed parameter tractable (FPT). On the other hand, we show that clique counting is FPT. Finally, we show that reachability is FPT if and only if $\mathbf{NL}$ is in some fixed polynomial time.<|reference_end|>
@article{gupta2024the,
    title={The Computational Complexity of Factored Graphs},
    author={Shreya Gupta, Boyang Huang, Russell Impagliazzo, Stanley Woo,
  Christopher Ye},
    journal={arXiv preprint arXiv:2407.19102},
    year={2024},
    archivePrefix={arXiv},
    eprint={2407.19102},
    primaryClass={cs.CC}
}