  Hypothesis elimination is a special case of Bayesian updating, where each
piece of new data rules out a set of prior hypotheses. We describe how to use
Grover's algorithm to perform hypothesis elimination for a class of probability
distributions encoded on a register of qubits, and establish a lower bound on
the required computational resources.
