  Emek et al. presented a model of probabilistic single-item second price
auctions where an auctioneer who is informed about the type of an item for
sale, broadcasts a signal about this type to uninformed bidders. They proved
that finding the optimal (for the purpose of generating revenue) {\em pure}
signaling scheme is strongly NP-hard. In contrast, we prove that finding the
optimal {\em mixed} signaling scheme can be done in polynomial time using
linear programming. For the proof, we show that the problem is strongly related
to a problem of optimally bundling divisible goods for auctioning. We also
prove that a mixed signaling scheme can in some cases generate twice as much
revenue as the best pure signaling scheme and we prove a generally applicable
lower bound on the revenue generated by the best mixed signaling scheme.
