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SUMMARY:Markovian approximation for Brownian particles driven by coloured 
 noise - Yongjoo Baek\, DAMTP
DTSTART:20190226T130000Z
DTEND:20190226T140000Z
UID:TALK116911@talks.cam.ac.uk
CONTACT:Etienne Fodor
DESCRIPTION:Self-propelled particles form a class of nonequilibrium system
 s with constant injection of energy on a microscopic scale. Given sufficie
 nt time-scale separation\, the dynamics of such particles can be modelled 
 as Brownian motion violating the fluctuation-dissipation relation\, namely
  Langevin dynamics with an instantaneous damping force and a Gaussian colo
 red noise with rapidly decaying correlations. To make the model analytical
 ly tractable\, previous studies have proposed various Markovian approximat
 ion schemes which replace the coloured noise with a multiplicative Gaussia
 n white noise\; however\, these approaches are not systematic and may rest
 ore equilibrium-like steady-state behaviours\, failing to capture the none
 quilibrium aspects of the steady state. In this talk\, I present a systema
 tic Markovian approximation\, which yields a Langevin equation with a mult
 iplicative non-Gaussian white noise. The nonzero skewness of the noise is 
 shown to be essential for correctly predicting the evolution of the probab
 ility distribution function. The approach provides a convenient and reliab
 le method for predicting nonequilibrium currents\, forces\, and first-pass
 age time statistics associated with self-propelled particles.
LOCATION:MR11\, CMS
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