How Many Queries Will Resolve Common Randomness?

A set of m terminals, observing correlated signals, communicate interactively to generate common randomness for a given subset of them. Knowing only the communication, how many direct queries of the value of the common randomness will resolve it? A general upper bound, valid for arbitrary signal alphabets, is developed for the number of such queries by using a query strategy that applies to all common randomness and associated communication. When the underlying signals are independent and identically distributed repetitions of m correlated random variables, the number of queries can be exponential in signal length. For this case, the mentioned upper bound is tight and leads to a single-letter formula for the largest query exponent, which coincides with the secret key capacity of a corresponding multiterminal source model. In fact, the upper bound constitutes a strong converse for the optimum query exponent, and implies also a new strong converse for secret key capacity. A key tool, estimating the size of a large probability set in terms of Rényi entropy, is interpreted separately, too, as a lossless block coding result for general sources. As a particularization, it yields the classic result for a discrete memoryless source.