For a killed Markov process and a positive harmonic function , its Doob h-transform weights the path law through a stopping time by , with localization when necessary. It describes conditioning on a boundary behaviour of probability zero. In the complex upper half-plane, conditions killed planar Brownian motion to remain in that half-plane.
If is smooth and is the unit-mean density martingale of a locally absolutely continuous probability measure relative to Wiener measure, then . The Itô formula gives when . The true-martingale hypothesis is already supplied by the density process. On each finite horizon the Girsanov theorem makes Brownian under the new measure. Positivity provides local equivalence; global infinite-horizon equivalence and the Novikov condition are not additional requirements.
Killed planar Brownian motion conditioned to exit at a smooth boundary point is the Doob h-transform by its positive Poisson kernel, normalized at the starting point. Its generator is . Conditioning on shrinking boundary arcs yields the same localized laws and specifies a canonical version of an otherwise probability-zero conditioning event.
Consider a path of planar Brownian motion in the unit disc , started at and conditioned to exit at . Let be a simply connected domain containing and agreeing with near . Let be a conformal map normalized by and . Then
The conditional probability is the ratio of the boundary Poisson kernel densities for exit at in and in . The conformal transformation rule for the Poisson kernel contributes the boundary derivative ; the normalized interior image is still , so no additional conformal-radius factor appears. Given avoidance of , the mapped path has the original conditioned law, with the conformal Brownian clock accounting for its time parametrization.

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