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SUMMARY:Some approximation results for mild solutions of stochastic fracti
 onal order evolution equations driven by Gaussian noise - Mihaly Kovacs (P
 ázmány Péter Catholic University\, Chalmers University of Technology)
DTSTART:20220222T093000Z
DTEND:20220222T100000Z
UID:TALK167735@talks.cam.ac.uk
DESCRIPTION:We investigate the quality of space approximations of a class 
 of stochastic integral equations of convolution type with Gaussian noise. 
 Such equations arise\, for example\, when considering mild solutions of st
 ochastic fractional order partial differential equations but also when con
 sidering mild solutions of classical stochastic partial differential equat
 ions. The key requirement for the equations is a smoothing property of the
  deterministic evolution operator which is typical in parabolic type probl
 ems. We show that if one has access to nonsmooth data estimates for the de
 terministic error operator together with its derivative of a space discret
 ization procedure\, then one obtains error estimates in pathwise H\\"older
  norms with rates that can be read off the deterministic error rates.\nThi
 s is a joint work with Erika Hausenblas (Montanuniversit&auml\;t Leoben) a
 nd Kistosil Fahim (Institut Teknologi Sepuluh Nopember).
LOCATION:Seminar Room 1\, Newton Institute
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