Nested critical points for a directed polymer on a disordered diamond lattice

TL;DR

This paper investigates the phase transition behavior of a directed polymer model on a hierarchical diamond lattice, identifying critical points where the variance of the normalized partition function shifts from vanishing to diverging, and establishing a central limit theorem in subcritical regimes.

Contribution

It introduces a detailed analysis of nested critical points for the variance of the partition function in a hierarchical directed polymer model, revealing complex phase transition structures.

Findings

Existence of a cutoff value for inverse temperature scaling as 7/70n where variance transitions occur.

Identification of a second cutoff involving 7/70n + ext7 ( ext7 n - 7 7 7 7 n)/n^{3/2} with nested critical points.

Proof of a central limit theorem for fluctuations in subcritical regimes.

Abstract

We consider a model for a directed polymer in a random environment defined on a hierarchical diamond lattice in which i.i.d. random variables are attached to the lattice bonds. Our focus is on scaling schemes in which a size parameter $n$, counting the number of hierarchical layers of the system, becomes large as the inverse temperature $\beta$ vanishes. When $\beta$ has the form $\widehat{\beta}/\sqrt{n}$ for a parameter $\widehat{\beta}>0$, we show that there is a cutoff value $0 < \kappa < \infty$ such that as $n \to \infty$ the variance of the normalized partition function tends to zero for $\widehat{\beta}\leq \kappa $ and grows without bound for $\widehat{\beta} > \kappa $. We obtain a more refined description of the border between these two regimes by setting the inverse temperature to $\kappa/\sqrt{n} + \alpha_n$ where $0 < \alpha_n \ll 1/\sqrt{n}$ and analyzing the asymptotic behavior of the variance. We show that when $\alpha_n = \alpha (\log n-\log \log n)/n^{3/2}$ (with a small modification to deal with non-zero third moment) there is a similar cutoff value $\eta$ for the parameter $\alpha$ such that when $\alpha < \eta$ the variance goes to zero and grows without bound when $\alpha > \eta$. Extending the analysis yet again by probing around the inverse temperature $\kappa/\sqrt{n} + \eta (\log n-\log \log n)/n^{3/2}$ we find an infinite sequence of nested critical points for the variance behavior of the normalized partition function. In the subcritical cases $\widehat{\beta} \leq \kappa$ and $\alpha \leq \eta$ this analysis is extended to a central limit theorem result for the fluctuations of the normalized partition function.