Approximate Ultrametricity for Random Measures and Applications to Spin Glasses

作者:Jagannath Aukosh
来源:Communications on Pure and Applied Mathematics, 2017, 70(4): 611-664.
DOI:10.1002/cpa.21685

摘要

In this paper, we introduce a notion called "approximate ultrametricity," which encapsulates the phenomenology of a sequence of random probability measures having supports that behave like ultrametric spaces insofar as they decompose into nested balls. We provide a sufficient condition for a sequence of random probability measures on the unit ball of an infinite-dimensional separable Hilbert space to admit such a decomposition, whose elements we call clusters. We also characterize the laws of the measures of the clusters by showing that they converge in law to the weights of a Ruelle probability cascade. These results apply to a large class of classical models in mean field spin glasses. We illustrate the notion of approximate ultrametricity by proving a conjecture of Talagrand regarding mixed p-spin glasses that is known to imply a prediction of DotsenkoFranz-Mezard.

  • 出版日期2017-4