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Besicovitch covering theorem

In mathematical analysis, a Besicovitch cover, named after Abram Samoilovitch Besicovitch, is an open cover of a subset E of the Euclidean space RN by balls such that each point of E is the center of some ball in the cover.

Application to maximal functions and maximal inequalities
Let μ be a Borel non-negative measure on RN, finite on compact subsets and let f be a \mu-integrable function. Define the maximal function f^* by setting for every x (using the convention \infty \times 0 = 0) :f^*(x) = \sup_{r > 0} \Bigl( \mu(B(x, r))^{-1} \int_{B(x, r)} |f(y)| \, d\mu(y) \Bigr). This maximal function is lower semicontinuous, hence measurable. The following maximal inequality is satisfied for every λ > 0: :\lambda \, \mu \bigl( \{ x : f^*(x) > \lambda \} \bigr) \le b_N \, \int |f| \, d\mu. ;Proof. The set Eλ of the points x such that f^*(x) > \lambda clearly admits a Besicovitch cover Fλ by balls B such that :\int \mathbf{1}_B \, |f| \ d\mu = \int_{B} |f(y)| \, d\mu(y) > \lambda \, \mu(B). For every bounded Borel subset E´ of Eλ, one can find a subcollection G extracted from Fλ that covers E´ and such that SG ≤ bN, hence :\begin{align} \lambda \, \mu(E') &\le \lambda \, \sum_{B \in \mathbf{G}} \mu(B)\\ &\le \sum_{B \in \mathbf{G}} \int \mathbf{1}_B \, |f| \, d\mu = \int S_{\mathbf {G}} \, |f| \, d\mu \le b_N \, \int |f| \, d\mu, \end{align} which implies the inequality above. When dealing with the Lebesgue measure on RN, it is more customary to use the easier (and older) Vitali covering lemma in order to derive the previous maximal inequality (with a different constant). ==See also==
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