Gamma-to-cumulant conjecture for iterated Malliavin Gamma operators

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Let F∞F_\infty be the target random variable in the second Wiener chaos of the form referenced in the source, and let F=Iq(f)F=I_q(f) be a chaotic random variable in the qqth Wiener chaos, where q≥2q\geq2. Let ara_r, Γr\Gamma_r, and Δ(F)\Delta(F) denote the coefficients, iterated Malliavin Gamma operators, and discrepancy quantity used in the estimate. Gamma-to-cumulant conjecture. There exists a constant CC, possibly depending on qq and dd, such that

Var⁡(∑r=1d+1arΓr−1(F))≤CΔ(F).\operatorname{Var}\left(\sum_{r=1}^{d+1}a_r\Gamma_{r-1}(F)\right)\leq C\Delta(F).

In the particular case d=2d=2 and α∞,1=−α∞,2=1/2\alpha_{\infty,1}=-\alpha_{\infty,2}=1/2, so that F∞=N1N2F_\infty=N_1N_2 for independent standard normal variables N1,N2N_1,N_2, this becomes

Var⁡(Γ2(F)−F)≤C{κ6(F)5!−2κ4(F)3!+κ2(F)}.\operatorname{Var}\left(\Gamma_2(F)-F\right)\leq C\left\{\frac{\kappa_6(F)}{5!}-2\frac{\kappa_4(F)}{3!}+\kappa_2(F)\right\}.

The conjecture seeks to control the iterated Gamma operators in the Kolmogorov-distance bound using finitely many cumulants; the source suggests that proving the displayed estimate would be a possible route, while no resolution is supplied.

References

Primary source

Ehsan Azmoodeh, Giovanni Peccati and Xiaochuan Yang, “Malliavin-Stein Method: a Survey of Recent Developments”, arXiv:1809.01912 (2021).

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