A metric discrepancy estimate for a real sequence
A general metrical result of discrepancy estimate related to uniform distribution is proved in this paper. It has been proven by J.W.S Cassel and P.Erdos \& Koksma in [2] under a general hypothesis of $(g_n (x))_{n = 1}^\infty$ that for every $\varepsilon > 0$, $$D(N,x) = O(N^{\frac{{ - 1}}...
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| Format: | Article |
| Language: | English |
| Published: |
2006
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| Online Access: | http://eprints.utm.my/id/eprint/60/1/A_Metric_Discrepancy_Estimate_for_A_Real_Sequence.pdf http://eprints.utm.my/id/eprint/60/ http://161.139.72.2/oldfs/images/stories/matematika/20062213.pdf |
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| Summary: | A general metrical result of discrepancy estimate related to uniform distribution is proved in this paper. It has been proven by J.W.S Cassel and P.Erdos \& Koksma in [2] under a general hypothesis of $(g_n (x))_{n = 1}^\infty$ that for every $\varepsilon > 0$,
$$D(N,x) = O(N^{\frac{{ - 1}}{2}} (\log N)^{\frac{5}{2} + \varepsilon } )$$
for almost all $x$ with respect to Lebesgue measure. This discrepancy estimate was improved by R.C. Baker [5] who showed that the exponent $\frac{5}{2} + \varepsilon$ can be reduced to $\frac{3}{2} + \varepsilon$ in a special case where $g_n (x) = a_n x$ for a sequence of integers $(a_n )_{n = 1}^\infty$. This paper extends this result to the case where the sequence $(a_n )_{n = 1}^\infty$ can be assumed to be real. The lighter version of this theorem is also shown in this paper. |
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