Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash 97 tok/s
Gemini 2.5 Pro 53 tok/s Pro
GPT-5 Medium 36 tok/s
GPT-5 High 34 tok/s Pro
GPT-4o 91 tok/s
GPT OSS 120B 462 tok/s Pro
Kimi K2 217 tok/s Pro
2000 character limit reached

Pinning model in random correlated environment: appearance of an infinite disorder regime (1303.2990v2)

Published 12 Mar 2013 in math.PR

Abstract: We study the influence of a correlated disorder on the localization phase transition in the pinning model. When correlations are strong enough, a strong disorder regime arises: large and frequent attractive regions appear in the environment. We present here a pinning model in random binary ({-1,1}-valued) environment. Defining strong disorder via the requirement that the probability of the occurrence of a large attractive region is sub-exponential in its size, we prove that it coincides with the fact that the critical point is equal to its minimal possible value. We also stress that in the strong disorder regime, the phase transition is smoother than in the homogeneous case, whatever the critical exponent of the homogeneous model is: disorder is therefore always relevant. We illustrate these results with the example of an environment based on the sign of a Gaussian correlated sequence, in which we show that the phase transition is of infinite order in presence of strong disorder. Our results contrast with results known in the literature, in particular in the case of an IID disorder, where the question of the influence of disorder on the critical properties is answered via the so-called Harris criterion, and where a conventional relevance/irrelevance picture holds.

List To Do Tasks Checklist Streamline Icon: https://streamlinehq.com

Collections

Sign up for free to add this paper to one or more collections.

Summary

We haven't generated a summary for this paper yet.

Ai Generate Text Spark Streamline Icon: https://streamlinehq.com

Paper Prompts

Sign up for free to create and run prompts on this paper using GPT-5.

Dice Question Streamline Icon: https://streamlinehq.com

Follow-up Questions

We haven't generated follow-up questions for this paper yet.

Authors (1)