Hostname: page-component-cd9895bd7-gbm5v Total loading time: 0 Render date: 2024-12-27T21:29:59.213Z Has data issue: false hasContentIssue false

More on zeros and approximation of the Ising partition function

Published online by Cambridge University Press:  07 June 2021

Alexander Barvinok
Affiliation:
Department of Mathematics, University of Michigan, Ann Arbor, MI48109-1043, USA; E-mail: barvinok@umich.edu
Nicholas Barvinok
Affiliation:
School of Mathematics, Georgia Institute of Technology, Atlanta, GA30332, USA; E-mail: nbarvinok3@gatech.edu

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

We consider the problem of computing the partition function $\sum _x e^{f(x)}$ , where $f: \{-1, 1\}^n \longrightarrow {\mathbb R}$ is a quadratic or cubic polynomial on the Boolean cube $\{-1, 1\}^n$ . In the case of a quadratic polynomial f, we show that the partition function can be approximated within relative error $0 < \epsilon < 1$ in quasi-polynomial $n^{O(\ln n - \ln \epsilon )}$ time if the Lipschitz constant of the non-linear part of f with respect to the $\ell ^1$ metric on the Boolean cube does not exceed $1-\delta $ , for any $\delta>0$ , fixed in advance. For a cubic polynomial f, we get the same result under a somewhat stronger condition. We apply the method of polynomial interpolation, for which we prove that $\sum _x e^{\tilde {f}(x)} \ne 0$ for complex-valued polynomials $\tilde {f}$ in a neighborhood of a real-valued f satisfying the above mentioned conditions. The bounds are asymptotically optimal. Results on the zero-free region are interpreted as the absence of a phase transition in the Lee–Yang sense in the corresponding Ising model. The novel feature of the bounds is that they control the total interaction of each vertex but not every single interaction of sets of vertices.

Type
Discrete Mathematics
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright
© The Author(s), 2021. Published by Cambridge University Press

References

Barata, J.C.A. and Goldbaum, P.S., ‘On the distribution and gap structure of Lee-Yang zeros for the Ising model: periodic and aperiodic couplings’, Journal of Statistical Physics 103 (2001), no. 5-6, 857891.CrossRefGoogle Scholar
Barata, J.C.A. and Marchetti, D.H.U., ‘Griffiths’ singularities in diluted Ising models on the Cayley tree’, Journal of Statistical Physics 88 (1997), no. 1-2, 231268.CrossRefGoogle Scholar
Barvinok, A., Combinatorics and Complexity of Partition Functions , Algorithms and Combinatorics, 30 (Springer, Cham, 2016).CrossRefGoogle Scholar
Barvinok, A., Computing the partition function of a polynomial on the Boolean cube, in A Journey through Discrete Mathematics (Springer, Cham, 2017), 135164.Google Scholar
Barvinok, A., ‘Approximating real-rooted and stable polynomials, with combinatorial applications’, Online Journal of Analytic Combinatorics Issue 14 $\#$ 8 (2019), 13 pp.Google Scholar
Bencs, F., Buys, P., Guerini, L. and Peters, H., ‘Lee - Yang zeros of the antiferromagnetic Ising Model’, preprint arXiv:1907.07479 (2019).Google Scholar
Friedli, S. and Velenik, Y., Statistical Mechanics of Lattice Systems. A concrete mathematical introduction (Cambridge University Press, Cambridge, 2018).Google Scholar
Galanis, A., Štefankovič, D. and Vigoda, E., ‘Inapproximability of the partition function for the antiferromagnetic Ising and hard-core models’, Combinatorics, Probability and Computing 25 (2016), no. 4, 500559.CrossRefGoogle Scholar
Guo, H., Liu, J. and Lu, P., ‘Zeros of ferromagnetic 2-spin systems’, preprint arXiv:1907.06156 (2019).CrossRefGoogle Scholar
Jain, V., Risteski, A. and Koehler, F., Mean-field approximation, convex hierarchies, and the optimality of correlation rounding: a unified perspective, in STOC’19–Proceedings of the 51st Annual ACM SIGACT Symposium on Theory of Computing (ACM, New York, 2019), 12261236.CrossRefGoogle Scholar
Jerrum, M. and Sinclair, A., ‘Polynomial-time approximation algorithms for the Ising model’, SIAM Journal on Computing 22 (1993), no. 5, 10871116.CrossRefGoogle Scholar
Lee, T.D. and Yang, C.N., ‘Statistical theory of equations of state and phase transitions. II. Lattice gas and Ising model’, Physical Review (2) 87 (1952), 410419.CrossRefGoogle Scholar
Li, L., Lu, P. and Yin, Y., Correlation decay up to uniqueness in spin systems, in Proceedings of the Twenty-Fourth Annual ACM-SIAM Symposium on Discrete Algorithms (SIAM, Philadelphia, PA, 2012), 6784.Google Scholar
Liu, J., Sinclair, A. and Srivastava, P., ‘Fisher zeros and correlation decay in the Ising model’, Journal of Mathematical Physics 60 (2019), no. 10, 103304, 12 pp.CrossRefGoogle Scholar
Liu, J., Sinclair, A. and Srivastava, P., ‘The Ising partition function: zeros and deterministic approximation’, Journal of Statistical Physics 174 (2019), no. 2, 287315.CrossRefGoogle Scholar
Lu, P., Yang, K. and Zhang, C., FPTAS for hardcore and Ising models on hypergraphs, in 33rd Symposium on Theoretical Aspects of Computer Science, LIPIcs. Leibniz International Proceedings in Informatics (Schloss Dagstuhl. Leibniz-Zent. Inform. Wadern, 2016), 47, Art. No. 51, 14 pp.Google Scholar
Patel, V. and Regts, G., ‘Deterministic polynomial-time approximation algorithms for partition functions and graph polynomials’, SIAM Journal on Computing 46 (2017), no. 6, 18931919.CrossRefGoogle Scholar
Peters, H. and Regts, G., ‘Location of zeros for the partition function of the Ising model on bounded degree graphs’, Journal of the London Mathematical Society 101 (2020), Issue 2, 765785.CrossRefGoogle Scholar
Sinclair, A., Srivastava, P. and Thurley, M., ‘Approximation algorithms for two-state anti-ferromagnetic spin systems on bounded degree graphs’, Journal of Statistical Physics 155 (2014), no. 4, 666686.CrossRefGoogle Scholar
Sly, A. and Sun, N., ‘Counting in two-spin models on $d$ -regular graphs’, The Annals of Probability 42 (2014), no. 6, 23832416.CrossRefGoogle Scholar
Yang, C.N. and Lee, T.D., ‘Statistical theory of equations of state and phase transitions. I. Theory of condensation’, Physical Review (2) 87 (1952), 404409.CrossRefGoogle Scholar
Zhang, J., Liang, H. and Bai, F., ‘Approximating partition functions of the two-state spin system’, Information Processing Letters 111 (2011), no. 14, 702710.CrossRefGoogle Scholar