Polynomial-time approximation algorithms for the antiferromagnetic Ising model on line graphs

We present a polynomial-time Markov chain Monte Carlo algorithm for estimating the partition function of the antiferromagnetic Ising model on any line graph. The analysis of the algorithm exploits the ‘winding’ technology devised by McQuillan [CoRR abs/1301.2880 (2013)] and developed by Huang, Lu an...

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Vydáno v:Combinatorics, probability & computing Ročník 30; číslo 6; s. 905 - 921
Hlavní autoři: Dyer, Martin, Heinrich, Marc, Jerrum, Mark, Müller, Haiko
Médium: Journal Article
Jazyk:angličtina
Vydáno: Cambridge Cambridge University Press 01.11.2021
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ISSN:0963-5483, 1469-2163
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Shrnutí:We present a polynomial-time Markov chain Monte Carlo algorithm for estimating the partition function of the antiferromagnetic Ising model on any line graph. The analysis of the algorithm exploits the ‘winding’ technology devised by McQuillan [CoRR abs/1301.2880 (2013)] and developed by Huang, Lu and Zhang [Proc. 27th Symp. on Disc. Algorithms (SODA16), 514–527]. We show that exact computation of the partition function is #P-hard, even for line graphs, indicating that an approximation algorithm is the best that can be expected. We also show that Glauber dynamics for the Ising model is rapidly mixing on line graphs, an example being the kagome lattice.
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content type line 14
ISSN:0963-5483
1469-2163
DOI:10.1017/S0963548321000080