The macroscopic shape of Gelfand-Tsetlin patterns and free probability
Abstract
A Gelfand-Tsetlin function is a real-valued function φ:C R defined on a finite subset C of the lattice Z2 with the property that φ(x) ≤ φ(y) for every edge x,y directed north or east between two elements of C. We study the statistical physics properties of random Gelfand-Tsetlin functions from the perspective of random surfaces, showing in particular that the surface tension of Gelfand-Tsetlin functions at gradient u = (u1,u2) ∈ R>02 is given by align* σ(u1,u2) = - (u1 + u2 ) - (π u1/(u1+u2)) -1 + π. align* A Gelfand-Tsetlin pattern is a Gelfand-Tsetlin function defined on the triangle Tn = \(x1,x2) ∈ Z2 : 1 ≤ x2 ≤ x1 ≤ n \. We show that after rescaling, a sequence of random Gelfand-Tsetlin patterns with fixed diagonal heights approximating a probability measure μ satisfies a large deviation principle with speed n2 and rate functional of the form align* E[] := ∫ σ(∇ )\, ds \,dt - [μ] align* where [μ] is Voiculescu's free entropy. We show that the Euler-Lagrange equations satisfied by the minimiser of the rate functional agree with those governing the free compression operation in free probability, thereby resolving a recent conjecture of Shlyakhtenko and Tao.
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