AI & ML
On statistical inference for non-linear dynamical systems evolving in their global attractor
arXiv stat.TH0 views
arXiv:2606.06018v2 Announce Type: replace Abstract: We consider a periodic scalar reaction-diffusion system over a two-dimensional domain under natural conditions on the reaction function and with initial condition $\theta$. We show that on the global attractor $\mathcal A$ of the resulting dynamical system $(u_\theta(t):t>0)$, a reverse Poincar\'e inequality holds true, and that as a consequence the map $\theta \mapsto u_\theta(t)$ satisfies an $L^2(\Om)$-Lipschitz stability estimate on $\mathcal A$ for any $t>0$ fixed. We then show that statistical recovery of an initial condition $\theta$ in the attractor $\mathcal A$, as well as prediction of the states $u_\theta$, is possible from discrete measurements of the system at parametric $1/\sqrt N$ convergence rates.
Source:https://arxiv.org/abs/2606.06018PreviousSecond-order PACF asymptotics and discrimination between fractional Gaussian noise and $\FARIMA(0,d,0)$NextU-centering as subset ANOVA: edge regression and higher-order theory
Related posts

How Akai and Moog are embracing vibe-coded mods
0The Verge

Big Tech lost big in the 2026 election
0The Verge
How to keep shared short links and QR codes working when a campaign destination changes
0dev.to
Microsoft Entra ID Security: Why Revoking Sessions Isn't Enough
0dev.to
AI Companies Really, Really Want to Buy Your Work Files and Emails
0Wired
Ramp data shows AI spending stalling just as Anthropic nears its IPO
0TechCrunch