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University of Birmingham > Talks@bham > Data Science and Computational Statistics Seminar > Disorder relevance for non-convex random gradient Gibbs measures in d=2
Disorder relevance for non-convex random gradient Gibbs measures in d=2Add to your list(s) Download to your calendar using vCal
If you have a question about this talk, please contact Hong Duong. It is a famous result of statistical mechanics that, at low enough temperature, the random field Ising model is disorder relevant for d=2, i.e. the phase transition between uniqueness/non-uniqueness of Gibbs measures disappears, and disorder irrelevant otherwise (Aizenman-Wehr 1990). Generally speaking, adding disorder to a model tends to destroy the non-uniqueness of Gibbs measures. In this talk we consider - in non-convex potential regime – a random gradient model with disorder in which the interface feels like a bulk term of random fields. We show that this model is disorder relevant with respect to the question of uniqueness of gradient Gibbs measures for a class of non-convex potentials and disorders. We also discuss the question of decay of covariances for the model. No previous knowledge of gradient models will be assumed in the talk. This is joint work with Simon Buchholz. This talk is part of the Data Science and Computational Statistics Seminar series. This talk is included in these lists:
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