On the Fourier transform of random Bernoulli convolutions

Abstract

We investigate random Bernoulli convolutions, namely, probability measures given by the infinite convolution \[ μ_ω= \mathop{\circledast}_{k=1}^{\infty} \left( \frac{δ_0 + δ_{λ_1 λ_2 \ldots λ_{k-1} λ_k}}{2} \right), \] where $ω=(λ_k)$ is a sequence of i.i.d. random variables each following the uniform distribution on some fixed interval. We study the regularity of these measures and prove that when $\exp\mathbb{E}\left( \log λ_1\right)>\frac{2}π, $ the Fourier transform $\widehatμ_ω$ is an $L^{1}$ function almost surely. This in turn implies that the corresponding random self-similar set supporting $μ_ω$ has non-empty interior almost surely. This improves upon a previous bound due to Peres, Simon and Solomyak. Furthermore, under no assumptions on the value of $\exp \mathbb{E}(\log λ_1), $ we prove that $\widehat μ_ω$ will decay to zero at a polynomial rate almost surely.