Sharp Lower bound estimates for vector-valued and matrix-valued multipliers in L^p
classification
🧮 math.CA
math.PR
keywords
operatormultipliersahlfors-beurlingboundconsidergeneralizelowermatrix-valued
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We generalize the idea of a multiplier in two different ways and generalize a recent result of Geiss, Montomery-Smith and Saksman. First of all, we consider multipliers in the form of a vector acting on a scalar function. Using this technique we compute the sharp lower bound estimate for $L^p$ operator norm of a quadratic perturbation of the real part of the Ahlfors-Beurling operator. Secondly, we consider matrix-valued multipliers to obtain a new proof showing that the $L^p$ operator norm of the Ahlfors-Beurling operator is bounded below by p^*-1.
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