Positivity conjecture for the multivariate Bessel addition law

Let θ>0\theta>0, and let \a=(a1aN)\a=(a_1\le\dots\le a_N) and \b=(b1bN)\b=(b_1\le\dots\le b_N) be NN-tuples. The distribution =¸\a+θ\b\c=\a+_\theta\b is defined through the multivariate Bessel identity

EB(c1,,cN)(x1,,xN;θ)=B(a1,,aN)(x1,,xN;θ)B(b1,,bN)(x1,,xN;θ).\mathbb E B_{(c_1,\dots,c_N)}(x_1,\dots,x_N;\,\theta)=B_{(a_1,\dots,a_N)}(x_1,\dots,x_N;\,\theta)B_{(b_1,\dots,b_N)}(x_1,\dots,x_N;\,\theta).

Positivity conjecture. For every such \a\a and \b\b, there exists a probability measure on NN-tuples =¸(c1cN)\c=(c_1\le\dots\le c_N) satisfying the identity for all x1,,xNCx_1,\dots,x_N\in\mathbb C.

The identity is known to define a compactly supported generalized function or distribution of total mass 11, but it is not known in general whether this distribution is positive and hence a probability measure. The conjecture would provide a probabilistic interpretation of the Bessel addition law and is relevant to addition problems for general beta random matrices.

Sources & referencesView supporting material

Primary source

Florent Benaych-Georges, Cesar Cuenca and Vadim Gorin, “Matrix addition and the Dunkl transform at high temperature”, arXiv:2105.03795 (2022).

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