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The log-rank conjecture

Is deterministic communication complexity polylogarithmic in the rank of the communication matrix?

Inferred from the community field; finer classification has not been reviewed.

Problem statement

Let f:X×Y→{0,1}f : X \times Y \to \{0,1\} and let MfM_f be its communication matrix over the reals. Conjecture: the deterministic communication complexity satisfies

D(f)=(log⁡rank⁡Mf)O(1).D(f) = (\log \operatorname{rank} M_f)^{O(1)}.

Lean 4

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Background

Posed by Lovász and Saks in 1988. The lower bound D(f)≥log⁡rank⁡MfD(f) \ge \log \operatorname{rank} M_f is immediate; the conjecture asks whether the gap is at most polynomial.

Why it matters

It is a clean test of whether algebraic rank captures communication, and equivalent formulations connect it to the Boolean function analysis programme, to graph colouring of the corresponding rank-bounded structures, and to circuit depth via Karchmer–Wigderson games.

Known partial results

  • Lovett (2016) proved D(f)=O(rlog⁡r)D(f) = O(\sqrt{r}\log r) where r=rank⁡Mfr = \operatorname{rank} M_f; Sudakov and Tomon later removed the log factor, giving O(r)O(\sqrt{r}).
  • The best known separation is D(f)=Ω~((log⁡r)2)D(f) = \tilde{\Omega}((\log r)^{2}), from a construction of Göös, Pitassi and Watson building on Nisan–Wigderson.
  • So the truth lies between (log⁡r)2(\log r)^2 and r\sqrt r, a gap of exponential size.

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