Skip to main content

Counting Independent Sets in Graphs with Bounded Bipartite Pathwidth

  • Conference paper
  • First Online:
Graph-Theoretic Concepts in Computer Science (WG 2019)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 11789))

Included in the following conference series:

Abstract

The Glauber dynamics can efficiently sample independent sets almost uniformly at random in polynomial time for graphs in a certain class. The class is determined by boundedness of a new graph parameter called bipartite pathwidth. This result, which we prove for the more general hardcore distribution with fugacity \(\lambda \), can be viewed as a strong generalisation of Jerrum and Sinclair’s work on approximately counting matchings. The class of graphs with bounded bipartite pathwidth includes line graphs and claw-free graphs, which generalise line graphs. We consider two further generalisations of claw-free graphs and prove that these classes have bounded bipartite pathwidth.

M. Dyer and H. Müller—Research supported by EPSRC grant EP/S016562/1.

C. Greenhill—Research supported by Australian Research Council grant DP19010097.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 59.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 74.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Alekseev, V.E.: Polynomial algorithm for finding the largest independent sets in graphs without forks. Discrete Appl. Math. 135, 3–16 (2004)

    Article  MathSciNet  Google Scholar 

  2. Barvinok, A.: Computing the partition function of a polynomial on the Boolean cube. In: Loebl, M., Nešetřil, J., Thomas, R. (eds.) A Journey Through Discrete Mathematics, pp. 135–164. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-44479-6_7

    Chapter  MATH  Google Scholar 

  3. Bayati, M., Gamarnik, D., Katz, D., Nair, C., Tetali, P.: Simple deterministic approximation algorithms for counting matchings. In: Proceedings of the STOC, pp. 122–127 (2007)

    Google Scholar 

  4. Beineke, L.: Characterizations of derived graphs. J. Comb. Theory 9, 129–135 (1970)

    Article  MathSciNet  Google Scholar 

  5. Bodlaender, H.L.: A linear time algorithm for finding tree-decompositions of small treewidth. SIAM J. Comput. 25, 1305–1317 (1996)

    Article  MathSciNet  Google Scholar 

  6. Bodlander, H.L.: A partial \(k\)-arboretum of graphs with bounded treewidth. Theor. Comput. Sci. 209, 1–45 (1998)

    Article  MathSciNet  Google Scholar 

  7. Chudnovsky, M., Seymour, P.: The roots of the independence polynomial of a clawfree graph. J. Comb. Theory ( Ser. B) 97, 350–357 (2007)

    Article  MathSciNet  Google Scholar 

  8. Diaconis, P., Saloff-Coste, L.: Comparison theorems for reversible Markov chains. Ann. Appl. Probab. 3, 696–730 (1993)

    Article  MathSciNet  Google Scholar 

  9. Diaconis, P., Stroock, D.: Geometric bounds for eigenvalues of Markov chains. Ann. Appl. Probab. 1, 36–61 (1991)

    Article  MathSciNet  Google Scholar 

  10. Diestel, R.: Graph Theory. Graduate Texts in Mathematics, vol. 173. Springer, Heidelberg (2017). https://doi.org/10.1007/978-3-662-53622-3

    Book  MATH  Google Scholar 

  11. Dyer, M., Goldberg, L.A., Greenhill, C., Jerrum, M.: On the relative complexity of approximate counting problems. Algorithmica 38, 471–500 (2003)

    Article  MathSciNet  Google Scholar 

  12. Dyer, M., Greenhill, C.: On Markov chains for independent sets. J. Algorithms 35, 17–49 (2000)

    Article  MathSciNet  Google Scholar 

  13. Dyer, M., Greenhill, C., Müller, H.: Counting independent sets in graphs with bounded bipartite pathwidth. Preprint: arXiv:1812.03195 (2018)

  14. Efthymiou, C., Hayes, T., Stefankovic, D., Vigoda, E., Yin, Y.: Convergence of MCMC and loopy BP in the tree uniqueness region for the hard-core model. In: Proceedings of the FOCS 2016, pp. 704–713. IEEE (2016)

    Google Scholar 

  15. Greenhill, C.: The complexity of counting colourings and independent sets in sparse graphs and hypergraphs. Comput. Complex. 9, 52–72 (2000)

    Article  MathSciNet  Google Scholar 

  16. Harvey, N.J.A., Srivastava, P., Vondrák, J.: Computing the independence polynomial: from the tree threshold down to the roots. In: Proceedings of the SODA 2018, pp. 1557–1576 (2018)

    Chapter  Google Scholar 

  17. Jerrum, M.: Mathematical foundations of the Markov chain Monte Carlo method. In: Habib, M., McDiarmid, C., Ramirez-Alfonsin, J., Reed, B. (eds.) Probabilistic Methods for Algorithmic Discrete Mathematics. AC, vol. 16, pp. 116–165. Springer, Heidelberg (1998). https://doi.org/10.1007/978-3-662-12788-9_4

    Chapter  Google Scholar 

  18. Jerrum, M.: Counting, Sampling and Integrating: Algorithms and Complexity. Lectures in Mathematics - ETH Zürich. Birkhäuser, Basel (2003)

    Book  Google Scholar 

  19. Jerrum, M., Sinclair, A.: Approximating the permanent. SIAM J. Comput. 18, 1149–1178 (1989)

    Article  MathSciNet  Google Scholar 

  20. Jerrum, M., Sinclair, A., Vigoda, E.: A polynomial-time approximation algorithm for the permanent of a matrix with non-negative entries. J. ACM 51, 671–697 (2004)

    Article  MathSciNet  Google Scholar 

  21. Jerrum, M.R., Valiant, L.G., Vazirani, V.V.: Random generation of combinatorial structures from a uniform distribution. Theoret. Comput. Sci. 43, 169–188 (1986)

    Article  MathSciNet  Google Scholar 

  22. Matthews, J.: Markov chains for sampling matchings, Ph.D. thesis, University of Edinburgh (2008)

    Google Scholar 

  23. Luby, M., Vigoda, E.: Approximately counting up to four. In: Proceedings of the STOC 1995, pp. 150–159. ACM (1995)

    Google Scholar 

  24. Minty, G.J.: On maximal independent sets of vertices in claw-free graphs. J. Comb. Theory Ser. B 28, 284–304 (1980)

    Article  MathSciNet  Google Scholar 

  25. Patel, V., Regts, G.: Deterministic polynomial-time approximation algorithms for partition functions and graph polynomials. SIAM J. Comput. 46, 1893–1919 (2017)

    Article  MathSciNet  Google Scholar 

  26. Provan, J.S., Ball, M.O.: The complexity of counting cuts and of computing the probability that a graph is connected. SIAM J. Comput. 12, 777–788 (1983)

    Article  MathSciNet  Google Scholar 

  27. Robertson, N., Seymour, P.D.: Graph minors I: excluding a forest. J. Comb. Theory Ser. B 35, 39–61 (1983)

    Article  MathSciNet  Google Scholar 

  28. Sinclair, A.: Improved bounds for mixing rates of Markov chains and multicommodity flow. Comb. Probab. Comput. 1, 351–370 (1992)

    Article  MathSciNet  Google Scholar 

  29. Sly, A.: Computational transition at the uniqueness threshold. In: Proceedings of the FOCS 2010, pp. 287–296. IEEE (2010)

    Google Scholar 

  30. Vadhan, S.P.: The complexity of counting in sparse, regular, and planar graphs. SIAM J. Comput. 31, 398–427 (2001)

    Article  MathSciNet  Google Scholar 

  31. Weitz, D.: Counting independent sets up to the tree threshold. In: Proceedings of the STOC 2006, pp. 140–149. ACM (2006)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Haiko Müller .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Dyer, M., Greenhill, C., Müller, H. (2019). Counting Independent Sets in Graphs with Bounded Bipartite Pathwidth. In: Sau, I., Thilikos, D. (eds) Graph-Theoretic Concepts in Computer Science. WG 2019. Lecture Notes in Computer Science(), vol 11789. Springer, Cham. https://doi.org/10.1007/978-3-030-30786-8_23

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-30786-8_23

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-30785-1

  • Online ISBN: 978-3-030-30786-8

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics