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On optimal autocorrelation inequalities on the real line

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  • We study autocorrelation inequalities, in the spirit of Barnard and Steinerberger's work [1]. In particular, we obtain improvements on the sharp constants in some of the inequalities previously considered by these authors, and also prove existence of extremizers to these inequalities in certain specific settings. Our methods consist of relating the inequalities in question to other classical sharp inequalities in Fourier analysis, such as the sharp Hausdorff–Young inequality, and employing functional analysis as well as measure theory tools in connection to a suitable dual version of the problem to identify and impose conditions on extremizers.

    Mathematics Subject Classification: 42A05, 42A85, 28A12, 42A82.

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  • [1] R.C. Barnard and S. Steinerberger, Three convolution inequalities on the real line with connection to additive combinatorics, J. Number Theory, 207 (2020), 42-55.  doi: 10.1016/j.jnt.2019.07.001.
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    [7] H. Cohn and F. Gonçalves, An optimal uncertainty principle in twelve dimensions via modular forms, Inventionnes Mathematicae, 217 (2019), 799-831.  doi: 10.1007/s00222-019-00875-4.
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    [12] F. GonçalvesD. Oliveira e Silva and S. Steinerberger, Hermite polynomials, linear flows on the torus, and an uncertainty principle for roots, J. Math. Anal. Appl., 451 (2017), 678-711.  doi: 10.1016/j.jmaa.2017.02.030.
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    [16] M. Matolcsi and C. Vinuesa, Improved bounds on the supremum of autoconvolutions, J. Math. Anal. Appl., 372 (2010), 439-447.  doi: 10.1016/j.jmaa.2010.07.030.
    [17] G. Yu, An upper bound for $B2[g]$ sets, J. Number Theory, 122 (2007), 211-220.  doi: 10.1016/j.jnt.2006.04.008.
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