The sums-of-squares conjecture for Gaussian product polynomials

From papers

Let n3n\ge 3, let m1,,mnNm_1,\dots,m_n\in\mathbb{N}, and let U1,,UnU_1,\dots,U_n be independent standard Gaussian random variables. Define the polynomial HH on Rn(n1)/2\mathbb{R}^{n(n-1)/2} by

H(x21,x31,x32,,xn1,,xn,n1)=E[U12m1i=2n(j=1i1xijUj+Ui)2mi](2m11)!!i=2nE[(j=1i1xijUj+Ui)2mi].\begin{aligned} H(x_{21},x_{31},x_{32},\dots,x_{n1},\dots,x_{n,n-1})={}&E\left[U_1^{2m_1}\prod_{i=2}^{n}\left(\sum_{j=1}^{i-1}x_{ij}U_j+U_i\right)^{2m_i}\right]\\ &-(2m_1-1)!!\prod_{i=2}^{n}E\left[\left(\sum_{j=1}^{i-1}x_{ij}U_j+U_i\right)^{2m_i}\right]. \end{aligned}

The sums-of-squares conjecture for Gaussian product polynomials states that HH has a sums-of-squares representation. This proposed stronger formulation would imply the corresponding even Gaussian product inequalities. The authors motivate it as a route to proving the GPI and report exact sums-of-squares verifications for numerous cases, but do not establish the assertion for all nn and mjm_j; it remains open.

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Sources & referencesView supporting material

Primary source

Oliver Russell and Wei Sun, “Using Sums-of-Squares to Prove Gaussian Product Inequalities”, arXiv:2205.02127 (2022).

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