Abstract
A 1–2 model configuration is a subset of edges of a hexagonal lattice satisfying the constraint that each vertex is incident to 1 or 2 edges. We introduce Markov chains to sample the 1–2 model configurations on the 2D hexagonal lattice and prove that the mixing time of these chains is polynomial in the sizes of the graphs for a large class of probability measures.
Similar content being viewed by others
References
Aldous, D., Fill, J.: Reversible Markov chains and random walks on graphs. http://www.stat.berkeley.edu/~aldous/RWG/book.html (1999)
Chen, M.F.: Trilogy of couplings and general formulas for lower bound of spectral gap. In: Probability Towards 2000, Lecture Notes in Statistics, pp. 123–136. Springer, New York (1998)
Dobrushin, R.L., Shlosman, S.B.: Constructive criterion for the uniqueness of a Gibbs field. In: Fritz, J., Jaffe, A., Szász, D. (eds.) Statistical Mechanics and Dynamical Systems, pp. 371–403. Birkhauser, Boston (1985)
Dyer, M., Sinclair, A., Vigoda, E., Weitz, D.: Mixing in time and space for lattice spin systems: a combinatoria view. Random Struct. Algorithm. 24, 461–479 (2004)
Grimmett, G., Li, Z.: The 1-2 model. In: In the Tradition of Ahlfors-Bers VII, Contemporary Mathematics, pp. 139–152. American Mathematical Society, Providence, RI (2017)
Grimmett, G., Li, Z.: Critical surface of the 1-2 model. Int. Math. Res. Not. 2018, 6617–6672 (2018)
Häggström, O.: Finite Markov Chains and Algorithmic Applications. London Mathematical Society Student Texts, vol. 52. Cambridge University Press, Cambridge (2002)
Häggström, O.: Counting, Sampling and Integrating: Algorithms and Complexity. Lectures in Mathematics. ETH Zürich, Birkhäuser, Basel (2003)
Kasteleyn, P.W.: The statistics of dimers on a lattice, I. The number of dimer arrangements on a quadratic lattice. Physica 27, 1209–25 (1961)
Kenyon, R.: Local statistics of lattice dimers. Ann. de l’Institut Henri Poincaré B 33, 591–618 (1997)
Kenyon, R., Okounkov, A., Sheffield, S.: Dimers and amoebae. Ann. Math. 163, 1019–56 (2006)
Levin, D.A., Peres, Y., Wilmer, E.: Markov Chains and Mixing Times. American Mathematical Society, Providence, RI (2008)
Li, Z.: Local statistics of realizable vertex models. Commun. Math. Phys. 304, 723–763 (2011)
Li, Z.: 1-2 model, dimers and clusters. Electon. J. Probab. 19, 1–28 (2014)
Martinelli, F.: Lectures on Glauber dynamics for discrete spin models. In: Lectures on Probability Theory and Statistics (Saint-Flour, 1997), Lecture Notes in Mathematics, pp. 93–191. Springer, Berlin (1999)
Martinelli, F., Olivieri, E., Schonmann, R.: For 2-D lattice spin systems weak mixing implies strong mixing. Commun. Math. Phys. 165, 33–47 (1994)
Montenegro, R., Tetali, P.: Mathematical aspects of mixing times in Markov chains. Found. Trends® Theor. Comput. Sci. 1, 237–354 (2006)
Norris, J.R.: Markov Chains, Cambridge Series in Statistical and Probabilisitic Mathematics. Cambridge University Press, Cambridge (1998)
Schwartz, M., Bruck, J.: Constrained codes as network of relations. IEEE Trans. Inf. Theory 54, 2179–2195 (2008)
Temperley, H.N.V., Fisher, M.E.: Dimer problem in statistical mechanics-an exact result. Philos. Mag. 6, 1061–63 (1961)
Valiant, L.G.: Holographic algorithms. SIAM J. Comput. 37, 1565–1594 (2008)
van den Berg, J.: A constructive mixing condition for 2-D Gibbs measures with random interactions. Ann. Probab. 25, 1316–1333 (1997)
Acknowledgements
The author thanks Richard Kenyon for suggesting the problem solved in this paper, and Yuval Peres for suggesting the path method and comparison with block dynamics. The author acknowledges support from National Science Foundation under Grant 1608896. The author is grateful to anonymous reviewers for suggestions to improve the readability of this paper.
Author information
Authors and Affiliations
Corresponding author
Additional information
Communicated by Giulio Biroli.
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Appendix: How to Check the Condition \(F(\ell ,\nu ^{-1})\)
Appendix: How to Check the Condition \(F(\ell ,\nu ^{-1})\)
By Theorem 10, in order to prove the strong mixing condition for Gibbs measures of the 1–2 model on all the sufficiently large boxes, it suffices to show that \(F(\ell ,\nu ^{-1})\) holds for some fixed positive integer \(\ell \). In this section, we investigate efficient algorithms to check the condition \(F(\ell ,\nu ^{-1})\).
From the definition of \(F(\ell ,\nu ^{-1})\), in order to check the condition \(F(\ell ,\nu ^{-1})\), we need to compute the total variation differences of probability measures of 1–2 model configurations on finite graphs of \({{\mathbb {H}}}\) given different boundary conditions. The idea is to apply the measure-preserving correspondence of 1–2 model configurations on \({{\mathbb {H}}}\) and dimer configurations on \({{\mathbb {H}}}_{{\varDelta }}\), and to compute the total variation differences of probability measures for dimer configurations on finite subgraphs of \({{\mathbb {H}}}_{{\varDelta }}\) instead, which is known to be computable by determinants or Pfaffians; see [5, 6, 9,10,11, 14, 20].
By the measure-preserving correspondence of 1–2 model configurations on \({{\mathbb {H}}}\) and dimer configurations on \({{\mathbb {H}}}_{{\varDelta }}\), as well as the domain Markov property, to consider the boundary condition of an \(n\times n\) box \({\varLambda }_n\) of \({{\mathbb {H}}}\) in the 1–2 model configurations, it suffices to consider dimer configurations in all the hexagons crossing \(\partial {\varLambda }_n\). (For the \(3\times 3\) box \({\varLambda }_3\), \(\partial {\varLambda }_3\) is given by the blue lines in Fig. 15).
Each dimer configuration on \({{\mathbb {H}}}_{{\varDelta }}\) satisfies the following two constraints
-
each vertex of \({{\mathbb {H}}}\) has exactly one incident preset bisector edge in \({{\mathbb {H}}}_{{\varDelta }}\); and
-
around each hexagon of \({{\mathbb {H}}}\), there are an even number of present bisector edges.
Indeed, for any configuration on bisector edges satisfying the above two constraints, the configuration can be uniquely extended to a dimer configuration on \({{\mathbb {H}}}_{{\varDelta }}\). As a result, the influence of boundary conditions to dimer configurations in \({\varLambda }_{\ell }\) depends only on the parity of the number of present bisector edges outside \({\varLambda }_{\ell }\) in each hexagon crossing \(\partial {\varLambda }_{\ell }\). Let \(\ell \ge 3\). All the hexagons crossed by \(\partial {\varLambda }_{\ell }\) can be classified into 3 different types:
-
1.
The hexagon has 5 vertices outside \({\varLambda }_{\ell }\), and 1 vertex inside \({\varLambda }_{\ell }\). The two hexagons on the left and right corners of Fig. 15 are of this type.
-
2.
The hexagon has 4 vertices outside \({\varLambda }_{\ell }\), and 2 vertices inside \({\varLambda }_{\ell }\). The two hexagons on the top and bottom corners of Fig. 15 are of this type.
-
3.
The hexagon has 3 vertices outside \({\varLambda }_{\ell }\) and 3 vertices inside \({\varLambda }_{\ell }\). All the hexagons crossing \(\partial {\varLambda }_{\ell }\) but not on the corners are of this type.
We say a hexagon h crossing \(\partial {\varLambda }_{\ell }\) is positive (resp. negative) with respect to a boundary condition \(\tau \), if in h, an even (resp. odd) number of incident bisector edges to vertices outside \({\varLambda }_{\ell }\) are present in \(\tau \). Note that for an admissible boundary condition, there are an even number of hexagons crossing \(\partial {\varLambda }_{\ell }\) that are negative with respect to the boundary condition.
We will treat different types of hexagons differently.
If a Type (1) hexagon \(h_1\) is positive (resp. negative) with respect to the boundary condition, let e be the bisector edge in \(h_1\) incident to the unique vertex v of \(h_1\) in \({\varLambda }_{\ell }\); then e must be absent (resp. present), in which case we remove e (resp. all the incident edges of v), and treat the two adjacent hexagons of \(h_1\) crossing \(\partial {\varLambda }_{\ell }\) as Type-3 hexagons (Type-2 hexagons).
If a Type (2) hexagon \(h_2\) is positive (resp. negative) with respect to the boundary condition, then we replace the graph \({{\mathbb {H}}}_{{\varDelta }}\) in the hexagon by an edge (resp. a vertex and two edges), see the left graph (resp. the right graph) of Fig. 17.
If a Type (3) hexagon \(h_3\) is positive (resp. negative) with respect to the boundary condition, then we replace the graph \({{\mathbb {H}}}_{{\varDelta }}\) in the hexagon by a gadget in the left graph (resp. the right graph) Fig. 18.
Therefore, to consider the Gibbs measures for dimer configurations on \({\varLambda }_{\ell }\) with different boundary conditions, it suffices to consider Gibbs measures on different finite graphs. More precisely, the condition \(F(\ell ,\nu ^{-1})\) can be checked through the following steps:
-
1.
Construct finite subgraphs of \({{\mathbb {H}}}_{{\varDelta }}\) from the finite subgraphs of \({{\mathbb {H}}}\) with given boundary conditions by the procedure described above;
-
2.
Give a clockwise odd orientation to each constructed finite subgraph of \({{\mathbb {H}}}_{{\varDelta }}\) (i.e., give each edge on the finite subgraph of \({{\mathbb {H}}}_{{\varDelta }}\) an orientation such that each face of the finite subgraph of \({{\mathbb {H}}}_{{\varDelta }}\) has an odd number of edges oriented in the same way as the clockwise orientation; such an orientation always exists on a planar graph, see [9]);
-
3.
Compute the total variational distances of probability measures for dimer configurations on finite subgraphs of \({{\mathbb {H}}}_{{\varDelta }}\) with different boundary conditions; these can be computed by computing determinants and Pfaffians of the corresponding weighted adjacency matrices; see [14].
Rights and permissions
About this article
Cite this article
Li, Z. Mixing Time of Markov Chains for the 1–2 Model. J Stat Phys 176, 1526–1560 (2019). https://doi.org/10.1007/s10955-019-02352-x
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10955-019-02352-x