  There are many cases in collider physics and elsewhere where a calibration
dataset is used to predict the known physics and / or noise of a target region
of phase space. This calibration dataset usually cannot be used out-of-the-box
but must be tweaked, often with conditional importance weights, to be maximally
realistic. Using resonant anomaly detection as an example, we compare a number
of alternative approaches based on transporting events with normalizing flows
instead of reweighting them. We find that the accuracy of the morphed
calibration dataset depends on the degree to which the transport task is set up
to carry out optimal transport, which motivates future research into this area.
