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Communication Complexity


Communication complexity measures the number of bits that parties with separately held inputs must exchange to compute a function of their combined input. In the two-party model, Alice knows x, Bob knows y, and their communication must determine f(x,y). Local computation is unrestricted. Deterministic, randomized, and nondeterministic protocols impose different requirements on the communication (Kushilevitz and Nisan 1997).

A nondeterministic protocol accepts a pair of inputs when at least one accepting communication transcript is consistent with them. Zhang (2026) proved that deciding whether an n-vertex graph is connected has nondeterministic communication complexity Theta(nlnn) when Alice and Bob hold disjoint sets of its edges, where Theta denotes big-Theta notation. The upper bound communicates a spanning tree, and the lower bound matches its order of growth. Zhang (2026) credits ChatGPT with a key edge coloring lemma and an optimization using Hölder's inequality.


See also

Computational Complexity, Complexity Theory

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References

Kushilevitz, E. and Nisan, N. Communication Complexity. Cambridge, England: Cambridge University Press, 1997. https://doi.org/10.1017/CBO9780511574948.Zhang, Z. "Settling Nondeterministic Communication Complexity of Graph Connectivity." 23 Oct 2026. https://arxiv.org/abs/2610.32346.

Cite this as:

Weisstein, Eric W. "Communication Complexity." From MathWorld--A Wolfram Resource. https://mathworld.wolfram.com/CommunicationComplexity.html

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