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Research PaperResearchia:202609.02034

Pointwise Majorization for sub-Weibull and Mixed Tail Processes with Applications in Quadratic Chaos and Ergodic Diffusions

Haichen Hu

Abstract

Classical chaining controls an indexed stochastic process through a single worst-case bound, which can obscure substantial variation across the index set. We establish the first simultaneous pointwise majorization theory for Banach-valued processes with sub-Weibull or two-metric mixed-tail increments. For an anchored sub-Weibull process on a separable index space, write $v(t):=d(t,t_0)$. Given a reference measure $μ$, the envelope at $t$ is governed by the pointwise Fernique-Talagrand functional...

Submitted: September 2, 2026Subjects: Statistics; Data Science

Description / Details

Classical chaining controls an indexed stochastic process through a single worst-case bound, which can obscure substantial variation across the index set. We establish the first simultaneous pointwise majorization theory for Banach-valued processes with sub-Weibull or two-metric mixed-tail increments. For an anchored sub-Weibull process on a separable index space, write v(t):=d(t,t0)v(t):=d(t,t_0). Given a reference measure μμ, the envelope at tt is governed by the pointwise Fernique-Talagrand functional of order αα, Φμ,d(α)(t):=04v(t)(log1μ(Bd(t,r)))1/αdrΦ_{μ,d}^{(α)}(t):=\int_0^{4v(t)}(\log\frac{1}{μ(B_d(t,r))})^{1/α}dr. δ(0,1)\forall δ\in(0,1), we obtain that P(Zt{Φμ,d(α)(t)+v(t)(log(e/δ))1/α},t)1δ.\mathbb{P}(\|Z_t\|\lesssim\{Φ_{μ,d}^{(α)}(t)+v(t)(\log(e/δ))^{1/α}\},\forall t)\ge 1-δ. Our bound is determined by the pointwise complexity Φμ,d(α)Φ_{μ,d}^{(α)} rather than a global quantity. The result holds for every α>0α>0 and does not involve dyadic logarithmic terms from peeling. For mixed tail processes, with fixed measures μ1,μ2μ_1,μ_2 and vj(t):=dj(t,t0)v_j(t):=d_j(t,t_0), Φj(t):=04vj(t)(log1μj(Bdj(t,r)))1/αjdr,j=1,2Φ_j(t):=\int_0^{4v_j(t)}(\log\frac{1}{μ_j(B_{d_j}(t,r))})^{1/α_j}dr, j=1,2, for any δ(0,1)δ\in(0,1), we show that P(Ztj=12{Φj(t)+vj(t)(logeδ)1/αj},t)1δ.\mathbb{P}(\|Z_t\|\lesssim\sum_{j=1}^2\{Φ_j(t)+v_j(t)(\log\frac{e}δ)^{1/α_j}\},\forall t)\ge 1-δ. Although the two regimes are coupled in the mixed tail condition, each retains its own pseudo-metric, reference measure, pointwise Fernique-Talagrand functional, and tail exponent. The proof tracks the index-wise costs of measure-generated admissible chains and synchronizes them through a nested common refinement. For applications, we derive matrix-specific bounds for centered quadratic chaos under pseudo-metrics induced by the operator and Frobenius norms, and observable-specific finite-time bounds for diffusion empirical processes.


Source: arXiv:2609.01576v1 - http://arxiv.org/abs/2609.01576v1 PDF: https://arxiv.org/pdf/2609.01576v1 Original Link: http://arxiv.org/abs/2609.01576v1

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Date:
Sep 2, 2026
Topic:
Data Science
Area:
Statistics
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