May 2021 Additive functionals as rough paths
Jean-Dominique Deuschel, Tal Orenshtein, Nicolas Perkowski
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Ann. Probab. 49(3): 1450-1479 (May 2021). DOI: 10.1214/20-AOP1488


We consider additive functionals of stationary Markov processes and show that under Kipnis–Varadhan type conditions they converge in rough path topology to a Stratonovich Brownian motion, with a correction to the Lévy area that can be described in terms of the asymmetry (nonreversibility) of the underlying Markov process. We apply this abstract result to three model problems: First, we study random walks with random conductances under the annealed law. If we consider the Itô rough path, then we see a correction to the iterated integrals even though the underlying Markov process is reversible. If we consider the Stratonovich rough path, then there is no correction. The second example is a nonreversible Ornstein–Uhlenbeck process, while the last example is a diffusion in a periodic environment.

As a technical step, we prove an estimate for the p-variation of stochastic integrals with respect to martingales that can be viewed as an extension of the rough path Burkholder–Davis–Gundy inequality for local martingale rough paths of (In Séminaire de Probabilités XLI (2008) 421–438 Springer; In Probability and Analysis in Interacting Physical Systems (2019) 17–48 Springer; J. Differential Equations 264 (2018) 6226–6301) to the case where only the integrator is a local martingale.


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Jean-Dominique Deuschel. Tal Orenshtein. Nicolas Perkowski. "Additive functionals as rough paths." Ann. Probab. 49 (3) 1450 - 1479, May 2021.


Received: 1 March 2020; Revised: 1 September 2020; Published: May 2021
First available in Project Euclid: 7 April 2021

Digital Object Identifier: 10.1214/20-AOP1488

Primary: 60F17 , 60K37 , 60L20 , 82B43 , 82C41

Keywords: additive functionals of Markov processes , Homogenization‎ , Lépingle’s Burkholder–Davis–Gundy inequality in p-variation , random walks among random conductances , Rough paths , UCV condition

Rights: Copyright © 2021 Institute of Mathematical Statistics


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Vol.49 • No. 3 • May 2021
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