Mean value conjecture for the moment curve

From papers

For integers n2n\geq 2, parameters 0βn10\leq \beta\leq n-1, and s1s\geq 1, let e(t)=e2πite(t)=e^{2\pi i t} and integrate over [0,1]n1×[0,Nβ][0,1]^{n-1}\times[0,N^{-\beta}]. Mean value conjecture for the moment curve. One has

[0,1]n1×[0,1Nβ]k=1Ne(kx1+k2x2++knxn)2sdxϵNϵ(Nsβ+N2sn(n+1)2).\int_{[0,1]^{n-1}\times [0,\frac1{N^\beta}]}\left|\sum_{k=1}^N e(kx_1+k^2x_2+\ldots+k^nx_n)\right|^{2s}dx\lesssim_\epsilon N^\epsilon\left(N^{s-\beta}+N^{2s-\frac{n(n+1)}2}\right).

This is a moment estimate for exponential sums along the moment curve, reflecting the expected balance between the diagonal contribution and the higher-order Vinogradov-type contribution; its resolution is not supplied in the given text.

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Sources & referencesView supporting material

Primary source

Ciprian Demeter, Larry Guth and Hong Wang, “Small cap decouplings”, arXiv:1908.09166 (2020).

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