Papers
Topics
Authors
Recent
Assistant
AI Research Assistant
Well-researched responses based on relevant abstracts and paper content.
Custom Instructions Pro
Preferences or requirements that you'd like Emergent Mind to consider when generating responses.
Gemini 2.5 Flash
Gemini 2.5 Flash 53 tok/s
Gemini 2.5 Pro 43 tok/s Pro
GPT-5 Medium 13 tok/s Pro
GPT-5 High 14 tok/s Pro
GPT-4o 96 tok/s Pro
Kimi K2 146 tok/s Pro
GPT OSS 120B 439 tok/s Pro
Claude Sonnet 4 37 tok/s Pro
2000 character limit reached

A vector-valued almost sure invariance principle for random expanding on average cocycles (2108.08714v3)

Published 19 Aug 2021 in math.DS and math.PR

Abstract: We obtain a quenched vector-valued almost sure invariance principle (ASIP) for random expanding on average cocycles. This is achieved by combining the adapted version of Gou\"{e}zel's approach for establishing ASIP and the recent construction of the so-called adapted norms, which in some sense eliminate the non-uniformity of the decay of correlations. For real-valued observables, we also show that the martingale approximation technique is applicable in our setup, and that it yields the ASIP with better error rates. Finally, we present an example showing the necessity of a scaling condition, answering a question of the first and third authors.

Summary

We haven't generated a summary for this paper yet.

Lightbulb On Streamline Icon: https://streamlinehq.com

Continue Learning

We haven't generated follow-up questions for this paper yet.

List To Do Tasks Checklist Streamline Icon: https://streamlinehq.com

Collections

Sign up for free to add this paper to one or more collections.