Parallel Approximation of Min-max Problems with Applications to Classical and Quantum Zero-Sum Games

This paper presents an efficient parallel algorithm for a new class of min-max problems based on the matrix multiplicative weights update method. Our algorithm can be used to find near-optimal strategies for competitive two-player classical or quantum games in which a referee exchanges any number of messages with one player followed by any number of additional messages with the other. This algorithm considerably extends the class of games which admit parallel solutions, demonstrating for the first time the existence of a parallel algorithm for a game in which one player reacts adaptively to the other. As a consequence, we prove that several competing-provers complexity classes collapse to PSPACE such as QRG(2), SQG and two new classes called DIP and DQIP. A special case of our result is a parallel approximation scheme for a new class of semi definite programs whose feasible region consists of lists of semi definite matrices that satisfy a ``transcript-like´´ consistency condition. Applied to this special case, our algorithm yields a direct polynomial-space simulation of multi-message quantum interactive proofs resulting in a first-principles proof of QIP=PSPACE.