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If $\mu \in \mathcal{M}(\mathbb{T})$ is nontrivial and singular with respect to lebesgue measure, then $$|\{\theta \in \mathbb{T} : M\mu(\theta) >\lambda\}| \ge \frac C\lambda \|\mu\|$$ where $| \cdot | $ denotes Lebesgue measure, $|\lambda| > \|\mu\|$, which is the total variation norm, and $C$ is an absolute constant.

That is the problem statement. I'm looking for advice on how to establish a weak 1-1 inequality going the other way. The standard tools (Besicovitch, Vitali) don't seem readily applicable.

The maximal function $M\mu(x) = \displaystyle\sup_{I \supset x} \frac{\mu(I)}{|I|}$ where the sup is taken over all intervals $I$ containing $x$.

David Bowman
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  • What is $M$? Some version of the Hardy-Littlewood maximal for measures? – Adrián González Pérez Apr 20 '18 at 09:46
  • Also (correct me if I am wrong) your difficulty is to prove the result for singular measures, for absolutely continuous ones this is a well-known result in Stein's "A note on the class $L \log L$" in which he uses Calderon-Zygmund decomposition the reverse inequality. – Adrián González Pérez Apr 20 '18 at 09:56
  • @AdriánGonzález-Pérez Hi, I edited to define the Hardy-Littlewood maximal function. I do indeed need to prove this for singular measures, although I looked at the paper you referenced and couldn't actually find the result for absolutely continuous measures. Can you say which proposition it is? – David Bowman Apr 20 '18 at 14:25
  • The proof to theorem $1$ establishes the result $|M\mu > \lambda| \ge \frac{C}{\lambda}\int_{|f|>c\lambda} |f| \ dx$, but I believe I would somehow need to replace that integral with just $\int |f|$. – David Bowman Apr 20 '18 at 14:32
  • You are right, i was recalling the paper by memory. – Adrián González Pérez Apr 20 '18 at 14:50
  • In any case if you don't modify the statement it will always be false. Take $\lambda \rightarrow 0^+$, the left hand side will be eventually $1$ but the right hand side will blow up, giving a contradiction. – Adrián González Pérez Apr 20 '18 at 15:04
  • Well we are proving this inequality for $\lambda > |\mu|$ so that shouldn’t be a problem – David Bowman Apr 20 '18 at 15:08

1 Answers1

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I think I have a proof. Assume that $\mu$ is positive and let $\mu = \mu_d + \mu_s$ be the Lebesgue decomposition, where $\mu_d$ is the discrete part and $\mu_s$ the absolutely singular.

Case 1: $\mu_d \neq 0$. The result can be proved as follows. Note that $M(\mu_1) \leq M(\mu_2)$, if $\mu_1 \leq \mu_2$. We have that $$\mu_d = \sum_{j} a_j \, \delta_{\theta_j}$$, choose one $j$, with $a_j > 0$, then $a_j \, M(\delta_{\theta_j}) \leq M(\mu)$. Therefore: \begin{eqnarray} |\{ \theta : M(\mu) > \lambda \}| & \geq & |\{ \theta : a_j \, M(\delta_{\theta_j}) > \lambda \}|\\ & = & \frac{2 \, a_j}{\lambda}. \end{eqnarray} In the second equality we have used that $M(\delta_{\theta_j}) = 1/|\theta -\theta_j|$.

Case 2: $\mu_d = 0$. This case is much more subtle. We have that $\mu = \mu_s$ s absolutely singular and so its support $S$ is a set of measure zero (without isolated points). By inner regularity we can pick a compact set $K \subset S$ such that $1- \epsilon \leq \mu(K)$. We can work with $d \nu = \mathbf{1}_K \, d \mu$, since $\nu \leq \mu$ and after a normalization we can consider $\nu$ to be a probability measure. Since the support of $\nu$ is a compact we have $$ K = \mathbb{T} \setminus \coprod_{j = 1}^\infty I_j, $$ where $I_j$ are a family of disjoint open intervals. Fix an integer $N > 1$, to be determined latex in terms of $\lambda$. Define \begin{eqnarray} K_N & = & \mathbb{T} \setminus \coprod_{j = 1}^N I_j \\ L_N & = & |K_N| \rightarrow 0^+. \end{eqnarray} Note that $K_N = \coprod_{j=1}^N J_j$, where $J_j$ are closed intervals. Define $q_j = \nu(J_j)$ and $p_j = |J_j|$. We have that $$ \begin{eqnarray} \sum_{j=1}^N p_j & = & |K_N| \\ \sum_{j=1}^N q_j & = & 1. \end{eqnarray} $$ Now, for each $N$ we define a function $\varphi_N: K_N^c \rightarrow \mathbb{R}_+$ such that $(M\nu)(\theta) \geq \varphi_N(\theta)$ given by $$ \varphi_N(\theta) = \frac{q_j}{|\theta - b_j| + p_j}, $$ where $\theta \in I_j$ and $J_j = [a_j, b_j]$, $I_j = (a_j, c_j)$ are contiguous intervals. To see that $\varphi_N(\theta) \leq M(\nu)(\theta)$ for $\theta \in K_N^c$ just notice that it is equal to $$ \varphi_N(\theta) = \frac{\nu((a_j,\theta))}{|(a_j,\theta)|}. $$ Now \begin{eqnarray} |\{ \theta \in \mathbb{T} : M(\nu) > \lambda \}| & \geq & |\{ \theta \in K_N^c : M(\nu) > \lambda \}|\\ & \geq & |\{ \theta \in K_N^c : \varphi_N(\theta) > \lambda \}| \\ & = & \sum_{j=1}^N \frac{q_j}{\lambda} - p_j = \frac{1}{\lambda} - |K_N|, \end{eqnarray} takings $N$ large enough so that $|K_N| < (\lambda^{-1})/2$ gives the result.