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Communications in Mathematical Physics
Article . 2022 . Peer-reviewed
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https://dx.doi.org/10.48550/ar...
Article . 2021
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Generating Diffusions with Fractional Brownian Motion

Generating diffusions with fractional Brownian motion
Authors: Martin Hairer; Xue-Mei Li;

Generating Diffusions with Fractional Brownian Motion

Abstract

AbstractWe study fast/slow systems driven by a fractional Brownian motion B with Hurst parameter $$H\in (\frac{1}{3}, 1]$$ H ∈ ( 1 3 , 1 ] . Surprisingly, the slow dynamic converges on suitable timescales to a limiting Markov process and we describe its generator. More precisely, if $$Y^\varepsilon $$ Y ε denotes a Markov process with sufficiently good mixing properties evolving on a fast timescale $$\varepsilon \ll 1$$ ε ≪ 1 , the solutions of the equation $$\begin{aligned} dX^\varepsilon = {\varepsilon }^{\frac{1}{2}-H} F(X^\varepsilon ,Y^\varepsilon )\,dB+F_0(X^\varepsilon ,Y^{\varepsilon })\,dt\; \end{aligned}$$ d X ε = ε 1 2 - H F ( X ε , Y ε ) d B + F 0 ( X ε , Y ε ) d t converge to a regular diffusion without having to assume that F averages to 0, provided that $$H< \frac{1}{2}$$ H < 1 2 . For $$H > \frac{1}{2}$$ H > 1 2 , a similar result holds, but this time it does require F to average to 0. We also prove that the n-point motions converge to those of a Kunita type SDE. One nice interpretation of this result is that it provides a continuous interpolation between the time homogenisation theorem for random ODEs with rapidly oscillating right-hand sides ($$H=1$$ H = 1 ) and the averaging of diffusion processes ($$H= \frac{1}{2}$$ H = 1 2 ).

Related Organizations
Keywords

Probability (math.PR), fractional Brownian motion, Fractional processes, including fractional Brownian motion, FOS: Physical sciences, Mathematical Physics (math-ph), Stochastic ordinary differential equations (aspects of stochastic analysis), Hurst parameter, Rough paths, FOS: Mathematics, 60G22, 60L20, 60H10, Mathematics - Probability, Mathematical Physics

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
5
Average
Average
Top 10%
Green
hybrid