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Let be a measurable transformation of a probability space , preserving the measure. Let be a random variable with law . Call (⋅, ⋅) a regular version of the conditional law of given (). Fix . We first prove that if is reachable from -almost every point for a Markov chain of kernel , then the -orbit of -almost every point visits . We then apply this result to the Lévy transform, which transforms the Brownian motion into the Brownian motion || − , where is the local time at 0 of . This allows...
Let =(, ) be a planar brownian motion, the filtration it generates, anda linear brownian motion in the filtration . One says that(or its filtration) is maximal if no other linear -brownian motion has a filtration strictly bigger than that of. For instance, it is shown in [In 265–278 (2008) Springer] that is maximal if there exists a linear brownian motion independent of and such that the planar brownian motion (, ) generates the same filtration as. We do not know if this sufficient condition...
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