Abstract

We prove several results which, together with prior work, provide a nearly-complete picture of the relationships among classical communication complexity classes between $${\mathsf{P}}$$ and $${\mathsf{PSPACE}}$$ , short of proving lower bounds against classes for which no explicit lower bounds were already known. Our article also serves as an up-to-date survey on the state of structural communication complexity. Among our new results we show that $${\mathsf{MA} \not\subseteq \mathsf{ZPP}^{\mathsf{NP}[1]}}$$ , that is, Merlin–Arthur proof systems cannot be simulated by zero-sided error randomized protocols with one $${\mathsf{NP}}$$ query. Here the class $$\mathsf{ZPP}^{\mathsf{NP}[1]}$$ has the property that generalizing it in the slightest ways would make it contain $${\mathsf{AM} \cap \mathsf{coAM}}$$ , for which it is notoriously open to prove any explicit lower bounds. We also prove that $${\mathsf{US} \not\subseteq \mathsf{ZPP}^{\mathsf{NP}[1]}}$$ , where $${\mathsf{US}}$$ is the class whose canonically complete problem is the variant of set-disjointness where yes-instances are uniquely intersecting. We also prove that $${\mathsf{US} \not\subseteq \mathsf{coDP}}$$ , where $${\mathsf{DP}}$$ is the class of differences of two $${\mathsf{NP}}$$ sets. Finally, we explore an intriguing open issue: Are rank-1 matrices inherently more powerful than rectangles in communication complexity? We prove a new separation concerning $${\mathsf{PP}}$$ that sheds light on this issue and strengthens some previously known separations.

Highlights

  • Complexity classes form the infrastructure of classical complexity theory

  • We summarize the state of affairs by showing a map of known inclusions and non-inclusions between pairs of traditional communication classes, and we provide a comprehensive survey of these results

  • In the full version we provide a catalog of communication complexity class definitions; throughout the text, we provide definitions on a “need-to-know” basis

Read more

Summary

Introduction

Complexity classes form the infrastructure of classical complexity theory. They are used to express the power of models of computation, characterize the complexities of important computational problems, and catalyze proofs of other results. Communication complexity can be viewed as a restricted (but generally less restricted than query complexity) setting for which lower bounds are more difficult to obtain. We summarize the state of affairs (including our new results) by showing a map of known inclusions and non-inclusions between pairs of traditional communication classes, and we provide a comprehensive survey of these results. This updates previous surveys by Babai, Frankl, and Simon [3] and Halstenberg and Reischuk [21]. If C is the name of a model (e.g., P for deterministic or NP for nondeterministic), we follow the convention of using C to denote both a complexity class and the corresponding complexity measure: C(F ) denotes the minimum cost of a correct protocol for the (possibly partial) two-party function F in model C, and C denotes the class of all (families of) partial functions F with C(F ) ≤ poly(log n)

Our Contributions
Open issue
Lower Bounds for Block-Equality and Unique-Set-Intersection
Proof of Theorem 1
Proof of Theorem 2 and Theorem 3
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call