Under the auspices of the Computational Complexity Foundation (CCF)
While exponential separations are known between quantum and randomized communication complexity for partial functions, e.g. Raz , the best known separation between these measures for a total function is quadratic, witnessed by the disjointness function. We give the first super-quadratic separation between quantum and randomized
communication complexity for a total function, giving an example exhibiting a power $2.5$ gap. We also present a nearly optimal quadratic separation between randomized communication complexity and the logarithm of the partition number, improving upon the previous best power $1.5$ separation due to Göös, Jayram, Pitassi, and Watson .
Our results are the communication analogues of separations in query complexity proved using the recent cheat sheet framework of Aaronson, Ben-David, and Kothari . Our main technical results are randomized communication and information complexity lower bounds for a family of functions, called lookup functions, that generalize and port the cheat sheet framework to communication complexity.