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Uniform distribution and algorithmic randomness

Published online by Cambridge University Press:  12 March 2014

Jeremy Avigad*
Affiliation:
Departments of Philosophy and Mathematical Sciences, Carnegie Mellon University, Pittsburgh, PA 15213, USA, E-mail: [email protected]

Abstract

A seminal theorem due to Weyl [14] states that if (an) is any sequence of distinct integers, then, for almost every x ∈ ℝ, the sequence (anx) is uniformly distributed modulo one. In particular, for almost every x in the unit interval, the sequence (anx) is uniformly distributed modulo one for every computable sequence (an) of distinct integers. Call such an x UD random. Here it is shown that every Schnorr random real is UD random, but there are Kurtz random reals that are not UD random. On the other hand, Weyl's theorem still holds relative to a particular effectively closed null set, so there are UD random reals that are not Kurtz random.

Type
Research Article
Copyright
Copyright © Association for Symbolic Logic 2013

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References

REFERENCES

[1]Chazelle, Bernard, The discrepancy method, Cambridge University Press, Cambridge, 2000.CrossRefGoogle Scholar
[2]Davenport, H., Erdős, P., and LeVeque, W. J., On Weyl's criterion for uniform distribution, The Michigan Mathematical Journal, vol. 10 (1963), pp. 311314.CrossRefGoogle Scholar
[3]Downey, Rodney G. and Hirschfeldt, Denis R., Algorithmic randomness and complexity, Springer, New York, 2010.CrossRefGoogle Scholar
[4]Harman, Glyn, Metric number theory, The Clarendon Press, New York, 1998.CrossRefGoogle Scholar
[5]Kuipers, L. and Niederreiter, H., Uniform distribution of sequences, Wiley-Interscience, New York, 1974.Google Scholar
[6]Loève, Michel, Probability theory II, fourth ed., Springer, New York, 1978.CrossRefGoogle Scholar
[7]Lyons, Russell, The measure of nonnormal sets, Inventiones Mathematical vol. 83 (1986), no. 3, pp. 605616.CrossRefGoogle Scholar
[8]Merkle, Wolfgang, The Kolmogorov–Loveland stochastic sequences are not closed under selecting subsequences, this Journal, vol. 68 (2003), no. 4, pp. 13621376.Google Scholar
[9]Nies, André, Computability and randomness, Oxford University Press, Oxford, 2009.CrossRefGoogle Scholar
[10]Parreau, François and Queffélec, Martine, M0 measures for the Walsh system, The Journal of Fourier Analysis and Applications, vol. 15 (2009), no. 4, pp. 502514.CrossRefGoogle Scholar
[11]Rosenblatt, Joseph M. and Wierdl, Máté, Pointwise ergodic theorems via harmonic analysis, Ergodic theory and its connections with harmonic analysis (Alexandria, 1993), Cambridge University Press, Cambridge, 1995, pp. 3151.CrossRefGoogle Scholar
[12]Ville, J., Étude critique de la notion de collectif, Gauthier-Villars, Paris, 1939.Google Scholar
[13]Wang, Y., Randomness and complexity, Ph.D. thesis, Heidelberg, 1996.Google Scholar
[14]Weyl, Hermann, Über die Gleichverteilung von Zahlen mod. Eins, Mathematische Annalen, vol. 77 (1916), no. 3, pp. 313352.CrossRefGoogle Scholar