On distribution functions of sequences generated by scalar and mixed product. (English) Zbl 1061.11042

In the first part of the paper the author is interested in the quantity \(g_s(t)\), the Lebesgue measure of the set \(\{(\mathbf b,x)\in [0,1]^{2s}: \mathbf b \cdot x < t\}\), where \(s\) is an integer, \(s\geq 1\), \(\mathbf b\) and \(x\) are \(s\)-dimensional vectors with components in \([0,1]\), \(\mathbf b \cdot x\) is their scalar product and \(t\) is a real number, \(0\leq t\leq s\). It is known that \[ g_1(t)=t - t \log, t, \quad t\in [0,1]. \] The author calculates \(g_2(t)\) and \(g_3(t)\) for \(0\leq t \leq 1\). To shed some light on the rather complicated formulas, he mentions an unpublished communication by Laurent Habsieger (Lyon 1) relating \(g_s\) to values of the Riemann \(\zeta \) function on positive integers. Nothing is known when \(1\leq t\leq s\).
The author is interested in the \(g_s\) functions for theoretical and practical reasons. If \(\mathbb B = (\mathbf b_n)_{n\geq 1}\) and \(\mathbb X =(x_n)_{n\geq 1}\) are sequences of integers, the asymptotic distribution function of the scalar product is defined by \[ g(t)=\lim _{N\to \infty } \frac {\# \{n\leq N: \mathbf b_n \cdot x_n <t\}} N. \] If the sequences \(\mathbb B\) and \(\mathbb X\) are uniformly distributed in \([0,1]^s\) and statistically independent, then \(g(t)\) is equal to \(g_s(t)\).
In the second part of the paper the author proves analogous results for the distribution function of the sequence of absolute values \(| \bigl (\mathbf b^{(1)}_n \times \mathbf b ^{(2)}_n\bigr ) \cdot x_n| \) of mixed products where again \(\mathbb B^{(1)}, \mathbb B^{(2)}\) and \(X\) are uniformly distributed and statistically independent sequences in \([0,1]^s\), \(s=2\) or 3.
Applications to cryptosystems are presented in the last two sections.


11K31 Special sequences
94A60 Cryptography
Full Text: EuDML


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