Abstract
Let G be an n-node graph with maximum degree Δ. The Glauber dynamics for G, defined by Jerrum, is a Markov chain over the k-colorings of G. Many classes of G on which the Glauber dynamics mixes rapidly have been identified. Recent research efforts focus on the important case that Δ ≥ dlog2 n holds for some sufficiently large constant d. We add the following new results along this direction, where ε can be any constant with 0 < ε < 1.
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Let α ≈ 1.645 be the root of (1 − e − 1/x)2 + 2x e − 1/x = 2. If G is regular and bipartite and k ≥ (α + ε)Δ, then the mixing time of the Glauber dynamics for G is O(nlogn).
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Let β ≈ 1.763 be the root of x = e 1/x. If the number of common neighbors for any two adjacent nodes of G is at most \(\frac{\epsilon^{1.5}\Delta}{360e}\) and k ≥ (1 + ε)βΔ, then the mixing time of the Glauber dynamics is O(nlogn).
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References
Bubley, R., Dyer, M.: Path coupling: a technique for proving rapid mixing in Markov chains. In: Proceedings of the 38th Annual IEEE Symposium on Foundations of Computer Science, pp. 223–231 (1997)
Dyer, M., Frieze, A.: Randomly colouring graphs with lower bounds on girth and maximum degree. In: Proceedings of the 42nd IEEE Symposium on Foundations of Computer Science, pp. 579–587 (2001)
Dyer, M., Frieze, A., Hayes, T.P., Vigoda, E.: Randomly coloring constant degree graphs. In: Proceedings of the 45th Annual IEEE Symposium on Foundations of Computer Science, pp. 582–589 (2004)
Dyer, M., Greenhill, C., Molloy, M.: Very rapid mixing of the Glauber dynamics for proper colorings on bounded-degree graphs. Random Structure and Algorithms 20(1), 98–114 (2002)
Frieze, A., Vera, J.: On randomly colouring locally sparse graphs. Discrete Mathematics and Theoretical Computer Science 8(1), 121–128 (2006)
Frieze, A., Vigoda, E.: A survey on the use of Markov chains to randomly sample colorings. In: Grimmett, G., McDiarmid, C. (eds.) Combinatorics, Complexity, and Chance — A Tribute to Dominic Welsh, ch. 4. Oxford University Press (2007)
Hayes, T., Vigoda, E.: A non-Markovian coupling for randomly sampling colorings. In: Proceedings of the 44th Annual IEEE Symposium on Foundations of Computer Science, pp. 618–627 (2003)
Hayes, T.P.: Local uniformity properties for Glauber dynamics on graph colorings (in submission)
Hayes, T.P.: Randomly coloring graphs of girth at least five. In: Proceedings of the 35th Annual ACM Symposium on Theory of Computing, pp. 269–278 (2003)
Hayes, T.P., Sinclair, A.: A general lower bound for mixing of single site dynamics on graphs. In: Proceedings of the 46th Annual IEEE Symposium on Foundations of Computer Science, pp. 511–520 (2005)
Hayes, T.P., Vera, J.C., Vigoda, E.: Randomly coloring planar graphs with fewer colors than the maximum degree. In: Proceedings of the 39th Annual ACM Symposium on Theory of Computing, pp. 450–458 (2007)
Hayes, T.P., Vigoda, E.: Variable length path coupling. In: Proceedings of the 15th Annual ACM-SIAM Symposium on Discrete Algorithms, pp. 103–110 (2004)
Hayes, T.P., Vigoda, E.: Coupling with stationary distribution and improved sampling for colorings and independent sets. In: Proceedings of the 16th Annual ACM-SIAM Symposium on Discrete Algorithms, pp. 971–979 (2005)
Jerrum, M.: A very simple algorithm for estimating the number of k-colorings of a low-degree graph. Random Structure and Algorithms 7(2), 157–166 (1995)
Jerrum, M., Sinclair, A.: The Markov chain Monte Carlo method: an approach to approximate counting and integration. In: Hochbaum, D.S. (ed.) Approximation Algorithms for NP-hard Problems, pp. 482–520. PWS Publishing Co. (1996)
Jerrum, M., Valiant, L., Vazirani, V.: Random generation of combinatorial structures from a uniform distribution. Theoretical Computer Science 43, 169–188 (1986)
Jerrum, M.R.: Counting, Sampling and Integrating: Algorithms and Complexity. Birkhauser Verlag, Basel (2003)
Kenyon, C., Mossel, E., Peres, Y.: Glauber dynamics on trees and hyperbolic graphs. In: Proceedings of the 42nd Annual IEEE Symposium on Foundations of Computer Science, pp. 568–578 (2001)
Lau, L.C., Molloy, M.: Randomly Colouring Graphs with Girth Five and Large Maximum Degree. In: Correa, J.R., Hevia, A., Kiwi, M. (eds.) LATIN 2006. LNCS, vol. 3887, pp. 665–676. Springer, Heidelberg (2006)
Martinelli, F., Sinclair, A.: Mixing time for the solid-on-solid model. In: Proceedings of the 41st Annual ACM Symposium on Theory of Computing, pp. 571–580 (2009)
Sly, A.: Reconstruction for the Potts model. In: Proceedings of the 41st Annual ACM Symposium on Theory of Computing, pp. 581–590 (2009)
Vigoda, E.: Improved bounds for sampling colorings. Journal of Mathematical Physics 41(3), 1555–1569 (2000)
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Kuo, CC., Lu, HI. (2012). Randomly Coloring Regular Bipartite Graphs and Graphs with Bounded Common Neighbors. In: Chao, KM., Hsu, Ts., Lee, DT. (eds) Algorithms and Computation. ISAAC 2012. Lecture Notes in Computer Science, vol 7676. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35261-4_6
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DOI: https://doi.org/10.1007/978-3-642-35261-4_6
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