Remarks on localized sharp functions on certain sets in \({\mathbb {R}}^n\)
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Abstract
The aim of this note is to define localized sharp functions on certain domains in \({\mathbb {R}}^n\) and prove \(L^p\) estimates analogue to that of Fefferman–Stein. The proofs go by modifications of the good lambda inequality.
Keywords
Local maximal function Sharp function Good lambda inequality Whitney decompositionMathematics Subject Classification
42B25 42B351 Introduction
2 Localized sharp function on \({\mathbb {R}}^n{\setminus } \{0\}\)
Cubes from three k-layers of \(\mathcal {L}\) for \(n=2\) which are contained in \((0,\infty )^n\)
Theorem 2.1
Corollary 2.2
Corollary 2.3
Proposition 2.4
Proof of Theorem 2.1
The remaining part of the section is devoted to proving Proposition 2.4. The following two lemmas will play a crucial role in the proof.
Lemma 2.5
Proof
Complementary neighborhoods for \(n=2\)
Case 2 \(S'f(x)\le f_M\). The proof in this case is similar to that in Case 1. The only difference is that we diminish the area of integration to \(Q_2\) instead of \(Q_1\). We omit the details. If \(n=1\), then \(M=\emptyset \). In this case we set \(f_M=0\) and proceed as in Case 1. \(\square \)
Remark 2.6
Lemma 2.7
Proof
Using Lemma 2.5 to |f| we get \( Sf(x) \le Sf(2x)+ 2^{-n}\cdot 3^{2n}|f|^{\#}_{\mathrm{loc},\,\varOmega }(2x)\). The inequality (2.5) holds because \(|f|^{\#}_{\mathrm{loc},\,\varOmega }(2x)\le 2 f^{\#}_{\mathrm{loc},\,\varOmega }(2x)\). \(\square \)
Iterating the inequality (2.5) we obtain the following corollary.
Corollary 2.8
Proof of Proposition 2.4
Case 1 \(Q_j\in {\mathcal {L}}\). Then \(b\alpha < |f|_{Q_j}=Sf(y)\le \mathbb Sf(y)\) for every \(y\in Q_j\), where in the last inequality we have used Corollary 2.8. Thus \(Q_j\subset \{x \in \varOmega :{\mathbb {S}}f(x)>b\alpha \}\) and (2.7) holds in this case.
3 Localized sharp function for \((0,\infty )^n\)
A part of the partition \({\widetilde{\mathcal {L}}}\) for \(n=2\) with the five layers \({\widetilde{L}}_{-1}\), \({\widetilde{L}}_0\),...,\({\widetilde{L}}_{3}\)
It turns out that the following theorem analogue to Theorem 2.1 holds.
Theorem 3.1
Corollary 3.2
The remaining part of this section is devoted to proving Theorem 3.1.
Lemma 3.3
Proof
Cubes which contain points \(x,F(x),F(F(x)),\ldots \) for \(n=2\)
Corollary 3.4
Proof
Remark 3.5
Let us note that \(\lim _{m\rightarrow \infty } {\widetilde{S}} f(F^m( x))=0\) for \(f\in L^p({\widetilde{\varOmega }})\). This is a consequence of the fact that \({\widetilde{\rho }}(F^m( x), \partial {\widetilde{\varOmega }}) \rightarrow \infty \) and \(\ell (Q^m)\rightarrow \infty \), where \(Q^m\) is the unique cube from \({\widetilde{{\mathcal {L}}}}\) such that \(F^m( x)\in Q^m\).
Lemma 3.6
Proof
Proposition 3.7
4 Localized sharp function for cube
Cubes from the set \({\widetilde{\mathcal {L}}}''\) for \(n=2\) (the picture presents cubes from the layers \({\widetilde{L}}_{1}\), \({\widetilde{L}}_{2}\),...,\({\widetilde{L}}_{5}\))
Our aim of this section is to prove the following theorem.
Theorem 4.1
The proof requires preparations.
For each \(K\in {\widetilde{{\mathcal {L}}}}''\) there is a unique \(\sigma \in G\) such that \(\sigma (K)\subset [0,1]^n\). Therefore in our considerations we shall deal with cubes contained in \([0,1]^n\) and then use the group action for other cubes.
From now on, let \(Q_1=\frac{1}{2}Q_0+\frac{1}{2}{} \mathbf 1 \).
Cubes K and \(\bigcup \text {Pre} (K)\) for \(n=2\)
Lemma 4.2
Proof
Corollary 4.3
Proof
Corollary 4.4
Proof
Proposition 4.5
Proof
Proof of Theorem 4.1
Notes
Acknowledgements
The authors want to thank Carlos Pérez and Krzysztof Stempak for conversations to the subject of the paper.
References
- 1.Duoandikoetxea, J.: Fourier Analysis. American Mathematical Society, Providence (2001)MATHGoogle Scholar
- 2.Fefferman, C., Stein, E.M.: \(H^p\) spaces of several variables. Acta Math. 129, 137–195 (1972)MathSciNetCrossRefMATHGoogle Scholar
- 3.Grafakos, L.: Modern Fourier Analysis. Graduate Texts in Mathematics, vol. 250, 3rd edn. Springer, New York (2014)MATHGoogle Scholar
- 4.Stein, E.M.: Harmonic Analysis Real-Variable Methods, Orthogonality, and Oscillatory Integrals. Princeton University Press, Princeton (1993)MATHGoogle Scholar
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