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Random tensors, propagation of randomness, and nonlinear dispersive equations

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arxiv 2006.09285 v1 pith:4MJ76T76 submitted 2020-06-16 math.AP math-phmath.MP

classification math.APmath-phmath.MP
keywords equationsrandomscalingdispersiveprobabilistictheoryarxivnatural
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Abstract. The purpose of this paper is twofold. We introduce the theory of random tensors, which naturally extends the method of random averaging operators in our earlier work arXiv:1910.08492, to study the propagation of randomness under nonlinear dispersive equations. By applying this theory we also solve Conjecture 1.7 in arXiv:1910.08492, and establish almost-sure local well-posedness for semilinear Schr\"{o}dinger equations in spaces that are subcritical in the probabilistic scaling. The solution we find has an explicit expansion in terms of multilinear Gaussians with adapted random tensor coefficients. In the random setting, the probabilistic scaling is the natural scaling for dispersive equations, and is different from the natural scaling for parabolic equations. Our theory, which covers the full subcritical regime in the probabilistic scaling, can be viewed as the dispersive counterpart of the existing parabolic theories (regularity structure, para-controlled calculus and renormalization group techniques).

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  1. Intrinsic Gaussian Tensor Geometry and Random Operator Spectra

    math.PR 2026-06 unverdicted novelty 6.0 of 10

    Fixed-order Hilbertian Gaussian chaos operators satisfy ||T_K^{(m)}||_{L^p S_r} ≤ C_m (p+r)^{m/2} max_S ||F_S(K)||_{S_r}, with constants independent of Hilbert dimensions and cutoff ranks.

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