A new kth derivative estimate for exponential sums via Vinogradov’s mean value

A new kth derivative estimate for exponential sums via Vinogradov’s mean value
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通过维诺格拉多夫平均值对指数和进行新的 k 阶导数估计

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发表时间:
2016
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通讯作者:
D. R. Heath
D. R. Heath
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作者:
D. R. Heath

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我们给一个轻微的改进过程中,估计指数和提取的维诺格拉多夫的平均值的界限。再加上最近的作品伍利,和布尔甘,德米特和古斯,提供最佳的维诺格拉多夫平均值的界限,我们产生了一个强大的新的k阶导数估计。粗略地说,这改进了k ≥ 4时的货车德尔科尔普特估计。给出了各种推论,例如显示$$zeta left({sigma + it} {left({1-sigma})}{left({1 - sigma } 8)}^{3/2}}/2 + vareps}}$$(σ+it)<$εt(1−σ)3/2/2+ε,对于t ≥ 2且0 ≤ σ ≤ 1,对于任何固定的ε > 0。
We give a slight refinement to the process by which estimates for exponential sums are extracted from bounds for Vinogradov’s mean value. Coupling this with the recent works of Wooley, and of Bourgain, Demeter and Guth, providing optimal bounds for the Vinogradov mean value, we produce a powerful new kth derivative estimate. Roughly speaking, this improves the van der Corput estimate for k ≥ 4. Various corollaries are given, showing for example that $$zeta left( {sigma + it} ight){ ll _varepsilon }{t^{{{left( {1 - sigma } ight)}^{3/2}}/2 + varepsilon }}$$ζ(σ+it)≪εt(1−σ)3/2/2+ε for t ≥ 2 and 0 ≤ σ ≤ 1, for any fixed ε > 0.