Fractional free convolution powers
Dimitri Shlyakhtenko, Terence Tao
Abstract
The extension k → µ ⊞k of the concept of a free convolution power to the case of non-integer k ≥ 1 was introduced by Bercovici-Voiculescu and Nica-Speicher, and related to the minor process in random matrix theory.In this paper we give two proofs of the monotonicity of the free entropy and free Fisher information of the (normalized) free convolution power in this continuous setting, and also establish an intriguing variational description of this process.*Using this relation, Voiculescu [31] established the free central limit theorem: if µ is a compactly supported probability measure of mean zero and variance one, then the normalized free convolutions k -1/2
Topics & Concepts
MathematicsConvolution (computer science)Pure mathematicsConvolution powerMathematical analysisFourier transformFourier analysisFractional Fourier transformComputer scienceMachine learningArtificial neural networkRandom Matrices and ApplicationsAdvanced Combinatorial MathematicsMathematical Inequalities and Applications