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Journal de Théorie des Nombres de Bordeaux
Article . 2002 . Peer-reviewed
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zbMATH Open
Article . 2002
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Uniform distribution modulo one and binary search trees

Authors: Dekking, Michel; van der Wal, Peter;

Uniform distribution modulo one and binary search trees

Abstract

Any sequence x = ( x k ) k = 1 ∞ of distinct numbers from [0,1] generates a binary tree by storing the numbers consecutively at the nodes according to a left-right algorithm (or equivalently by sorting the numbers according to the Quicksort algorithm). Let H n ( x ) be the height of the tree generated by x 1 , ⋯ , x n . Obviously log n log 2 - 1 ≤ H n ( x ) ≤ n - 1 . If the sequences x are generated by independent random variables having the uniform distribution on [0, 1], then it is well known that there exists c > 0 such that H n ( x ) ∼ c log n as n → ∞ for almost all sequences x . Recently Devroye and Goudjil have shown that if the sequences x are Weyl sequences, i.e., defined by x k = { α k } , k = 1 , 2 , ⋯ , and α is distributed uniformly at random on [ 0 , 1 ] then H n ( x ) ∼ ( 12 / π 2 ) log n log log n as n → ∞ in probability. In this paper we consider the class of all uniformly distributed sequences x , and we show that the only behaviour that is excluded by the equidistribution of x is that of the worst case, i.e., for these x we necessarily have H n ( x ) = o ( n ) as n → ∞ .

Keywords

uniform distribution, Data structures, binary search trees, Metric theory of other algorithms and expansions; measure and Hausdorff dimension, General theory of distribution modulo \(1\), Searching and sorting

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
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