
Revised: December 11, 2020
Published: September 27, 2021
Abstract: [Plain Text Version]
In communication complexity the Arthur-Merlin (\AM) model is the most natural one that allows both randomness and nondeterminism. Presently we do not have any super-logarithmic lower bound for the \AM-complexity of an explicit function. Obtaining such a bound is a fundamental challenge to our understanding of communication phenomena.
In this article we explore the gap between the known techniques and the complexity class \AM. In the first part we define a new natural class, Small-advantage Layered Arthur-Merlin (\SLAM), that has the following properties:
- \SLAM is (strictly) included in \AM and includes all previously known subclasses of \AM with non-trivial lower bounds: \NP, \MA, \SBP, \UAM \subseteq \SLAM \subset \AM Note that \NP\subset\MA\subset\SBP, while \SBP and \UAM are known to be incomparable.
- \SLAM is qualitatively stronger than the union of those classes: f\in\SLAM\setminus(\SBP\cup\UAM) holds for an (explicit) partial function f.
- \SLAM is subject to the discrepancy bound: for any f \SLAM(f) \in \Omega\left(\sqrt{\log{\frac1{disc(f)}}}\right)\,. In particular, the inner product function does not have an efficient \SLAM-protocol.
In the second part we ask why proving a lower bound of \omega(\sqrt n) on the \MA-complexity of an explicit function seems to be difficult. We show that such a bound either must explore certain “uniformity” of \MA (which would require a rather unusual argument), or would imply a non-trivial lower bound on the \AM-complexity of the same function.
Both of these results are related to the notion of layer complexity, which is, informally, the number of “layers of nondeterminism” used by a protocol.