Multiple Fractional Cohomological Equations and Quantitative Mixing on Nilmanifolds
Zhenqi Jenny Wang

TL;DR
This paper introduces a new analytic approach using fractional cohomological equations to prove super-exponential mixing rates for automorphisms on nilmanifolds, extending mixing results beyond tori.
Contribution
It develops a novel method based on fractional cohomological equations to establish super-exponential mixing of all orders on nilmanifolds, a first in the field.
Findings
Proves solvability of multiple fractional cohomological equations in a specific spectral range.
Establishes exponential decay of second-order correlations with partial regularity.
Demonstrates super-exponential mixing of all orders for irrational automorphisms.
Abstract
We develop a new analytic method for quantitative mixing of automorphisms on nilmanifolds. The method is based on the introduction and solvability of \emph{multiple fractional cohomological equations of Type~} (sum type). We prove that these equations are solvable in a cohomology-free range governed by the spectral behavior at the edge \(0\), with estimates in partial Sobolev/H\"older norms along (weak) stable/unstable subgroup directions only. As consequences, we obtain exponential decay of order-two correlations under partial regularity, without transverse derivatives, and quantitative mixing of all orders (a quantitative Rokhlin theorem) with rates explicit in the dynamical data. In particular, we show that irrational automorphisms exhibit super-exponential mixing of all orders for observables. To our knowledge, these are the first examples of super-exponential mixing…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsMathematical Dynamics and Fractals · Nonlinear Differential Equations Analysis · Advanced Differential Equations and Dynamical Systems
