Connection probabilities of multiple FK-Ising interfaces

IF 1.5 1区 数学 Q2 STATISTICS & PROBABILITY Probability Theory and Related Fields Pub Date : 2024-03-26 DOI:10.1007/s00440-024-01269-1
Yu Feng, Eveliina Peltola, Hao Wu
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Abstract

We find the scaling limits of a general class of boundary-to-boundary connection probabilities and multiple interfaces in the critical planar FK-Ising model, thus verifying predictions from the physics literature. We also discuss conjectural formulas using Coulomb gas integrals for the corresponding quantities in general critical planar random-cluster models with cluster-weight \({q \in [1,4)}\). Thus far, proofs for convergence, including ours, rely on discrete complex analysis techniques and are beyond reach for other values of q than the FK-Ising model (\(q=2\)). Given the convergence of interfaces, the conjectural formulas for other values of q could be verified similarly with relatively minor technical work. The limit interfaces are variants of \(\text {SLE}_\kappa \) curves (with \(\kappa = 16/3\) for \(q=2\)). Their partition functions, that give the connection probabilities, also satisfy properties predicted for correlation functions in conformal field theory (CFT), expected to describe scaling limits of critical random-cluster models. We verify these properties for all \(q \in [1,4)\), thus providing further evidence of the expected CFT description of these models.

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多个 FK-Ising 接口的连接概率
我们发现了临界平面 FK-Ising 模型中边界到边界连接概率和多界面的一般类别的缩放极限,从而验证了物理学文献的预测。我们还讨论了在一般临界平面随机簇模型中使用库仑气体积分计算相应量的猜想公式,该模型具有簇重({q \ in [1,4)}/)。到目前为止,包括我们在内的收敛性证明都依赖于离散复分析技术,对于 FK-Ising 模型((q=2))之外的其他 q 值是无法实现的。鉴于界面的收敛性,其他 q 值的猜想公式同样可以通过相对较少的技术工作得到验证。极限界面是\(\text {SLE}_\kappa \)曲线的变体(在\(q=2\)时,\(\kappa = 16/3\))。它们的分区函数给出了连接概率,也满足共形场论(CFT)中相关函数的预测性质,有望描述临界随机簇模型的缩放极限。我们验证了所有 \(q \in [1,4)\)的这些性质,从而为这些模型预期的共相场理论描述提供了进一步的证据。
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来源期刊
Probability Theory and Related Fields
Probability Theory and Related Fields 数学-统计学与概率论
CiteScore
3.70
自引率
5.00%
发文量
71
审稿时长
6-12 weeks
期刊介绍: Probability Theory and Related Fields publishes research papers in modern probability theory and its various fields of application. Thus, subjects of interest include: mathematical statistical physics, mathematical statistics, mathematical biology, theoretical computer science, and applications of probability theory to other areas of mathematics such as combinatorics, analysis, ergodic theory and geometry. Survey papers on emerging areas of importance may be considered for publication. The main languages of publication are English, French and German.
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