Shreya Gupta, Boyang Huang, Russell Impagliazzo, Stanley Woo, Christopher Ye
{"title":"因子图的计算复杂性","authors":"Shreya Gupta, Boyang Huang, Russell Impagliazzo, Stanley Woo, Christopher Ye","doi":"arxiv-2407.19102","DOIUrl":null,"url":null,"abstract":"Computational complexity is traditionally measured with respect to input\nsize. For graphs, this is typically the number of vertices (or edges) of the\ngraph. However, for large graphs even explicitly representing the graph could\nbe prohibitively expensive. Instead, graphs with enough structure could admit\nmore succinct representations. A number of previous works have considered\nvarious succinct representations of graphs, such as small circuits [Galperin,\nWigderson '83]. We initiate the study of the computational complexity of problems on factored\ngraphs: graphs that are given as a formula of products and union on smaller\ngraphs. For any graph problem, we define a parameterized version by the number\nof operations used to construct the graph. For different graph problems, we\nshow that the corresponding parameterized problems have a wide range of\ncomplexities that are also quite different from most parameterized problems. We\ngive a natural example of a parameterized problem that is unconditionally not\nfixed parameter tractable (FPT). On the other hand, we show that subgraph\ncounting is FPT. Finally, we show that reachability for factored graphs is FPT\nif and only if $\\mathbf{NL}$ is in some fixed polynomial time.","PeriodicalId":501024,"journal":{"name":"arXiv - CS - Computational Complexity","volume":"28 11 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The Computational Complexity of Factored Graphs\",\"authors\":\"Shreya Gupta, Boyang Huang, Russell Impagliazzo, Stanley Woo, Christopher Ye\",\"doi\":\"arxiv-2407.19102\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Computational complexity is traditionally measured with respect to input\\nsize. For graphs, this is typically the number of vertices (or edges) of the\\ngraph. However, for large graphs even explicitly representing the graph could\\nbe prohibitively expensive. Instead, graphs with enough structure could admit\\nmore succinct representations. A number of previous works have considered\\nvarious succinct representations of graphs, such as small circuits [Galperin,\\nWigderson '83]. We initiate the study of the computational complexity of problems on factored\\ngraphs: graphs that are given as a formula of products and union on smaller\\ngraphs. For any graph problem, we define a parameterized version by the number\\nof operations used to construct the graph. For different graph problems, we\\nshow that the corresponding parameterized problems have a wide range of\\ncomplexities that are also quite different from most parameterized problems. We\\ngive a natural example of a parameterized problem that is unconditionally not\\nfixed parameter tractable (FPT). On the other hand, we show that subgraph\\ncounting is FPT. Finally, we show that reachability for factored graphs is FPT\\nif and only if $\\\\mathbf{NL}$ is in some fixed polynomial time.\",\"PeriodicalId\":501024,\"journal\":{\"name\":\"arXiv - CS - Computational Complexity\",\"volume\":\"28 11 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-07-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"arXiv - CS - Computational Complexity\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/arxiv-2407.19102\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - CS - Computational Complexity","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2407.19102","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Computational complexity is traditionally measured with respect to input
size. For graphs, this is typically the number of vertices (or edges) of the
graph. However, for large graphs even explicitly representing the graph could
be prohibitively expensive. Instead, graphs with enough structure could admit
more succinct representations. A number of previous works have considered
various succinct representations of graphs, such as small circuits [Galperin,
Wigderson '83]. We initiate the study of the computational complexity of problems on factored
graphs: graphs that are given as a formula of products and union on smaller
graphs. For any graph problem, we define a parameterized version by the number
of operations used to construct the graph. For different graph problems, we
show that the corresponding parameterized problems have a wide range of
complexities that are also quite different from most parameterized problems. We
give a natural example of a parameterized problem that is unconditionally not
fixed parameter tractable (FPT). On the other hand, we show that subgraph
counting is FPT. Finally, we show that reachability for factored graphs is FPT
if and only if $\mathbf{NL}$ is in some fixed polynomial time.