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Sur la concentration de certaines fonctions additives

Published online by Cambridge University Press:  22 September 2011

R. DE LA BRETÈCHE
Affiliation:
Institut de Mathématiques de Jussieu, Université Paris Diderot-Paris 7, UFR de Mathématiques, Case 7012, Bâtiment Chevaleret, 75205 Paris Cedex 13, France. e-mail: [email protected]
G. TENENBAUM
Affiliation:
Institut Élie Cartan, Université de Nancy 1, BP 239, 54506 Vandœuvre Cedex, France. e-mail: [email protected]

Abstract

Improving on estimates of Erdős, Halász and Ruzsa, we provide new upper and lower bounds for the concentration function of the limit law of certain additive arithmetic functions under hypotheses involving only their average behaviour on the primes. In particular we partially confirm a conjecture of Erdős and Kátai. The upper bound is derived via a reappraisal of the method of Diamond and Rhoads, resting upon the theory of functions with bounded mean oscillation.

Type
Research Article
Copyright
Copyright © Cambridge Philosophical Society 2011

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References

BIBLIOGRAPHIE

[1]Babu, G. J.Absolutely continuous distribution functions of additive functions f(p) = (log p)a, a > 0. Acta Arith. 26, no. 4 (1974/75), 401403.CrossRefGoogle Scholar
[2]Diamond, H. G. and Rhoads, D.The modulus of continuity of the distribution function of ϕ(n)/n. Topics in classical number theory, Vol. I, II (Budapest, 1981), 335353, Colloq. Math. Soc. János Bolyai, 34 (North-Holland, Amsterdam, 1984).Google Scholar
[3]Elliott, P. D. T. A.Probabilistic number theory I: mean value theorems. Grundlehren der Math. Wiss. 239 (Springer-Verlag, 1979).CrossRefGoogle Scholar
[4]Elliott, P. D. T. A.Probabilistic number theory II: central limit theorems. Grundlehren der Math. Wiss. 240 (Springer-Verlag, 1980).CrossRefGoogle Scholar
[5]Erdős, P.On the distribution function of additive functions. Ann. of Math. 47 (1946), 120.CrossRefGoogle Scholar
[6]Erdős, P.On the distribution of numbers of the form σ(n)/n and on some related questions. Pacific J. Math. 52 (1974), 5965.CrossRefGoogle Scholar
[7]Erdős, P. and Kátai, I.On the concentration of distribution of additive functions. Acta Sci. Math. (Szeged) 41 (1979), no. 3–4, 295305.Google Scholar
[8]Gallagher, P. X.A large sieve density estimate near σ =1. Invent. Math. 11 (1970), 329339.CrossRefGoogle Scholar
[9]Halász, G.On the distribution function of additive arithmetical functions. Acta Arith. 27 (1975), 143152.CrossRefGoogle Scholar
[10]Montgomery, H. L. and Vaughan, R. C.Hilbert's inequality. J. London Math. Soc. (2) 8 (1974), 7382.CrossRefGoogle Scholar
[11]John, F. and Nirenberg, L.On functions of bounded mean oscillation. Comm. Pure Appl. Math. 14 (1961), 415426.CrossRefGoogle Scholar
[12]Ruzsa, I. Z.On the concentration of additive functions. Acta Math. Acad. Sci. Hungar. 36 (1980), no. 34, 215–232.CrossRefGoogle Scholar
[13]Tenenbaum, G.Introduction à la théorie analytique et probabiliste des nombres, troisième édition. (coll. Échelles, Belin, 2008).Google Scholar
[14]Tenenbaum, G. avec la collaboration de J. Wu. Exercices corrigés de théorie analytique et probabiliste des nombres. Cours spécialisés, no. 2. Société Mathématique de France (1996), xiv + 251 pp.Google Scholar