Point-hyperplane incidence geometry and the log-rank conjecture


Abstract in English

We study the log-rank conjecture from the perspective of point-hyperplane incidence geometry. We formulate the following conjecture: Given a point set in $mathbb{R}^d$ that is covered by constant-sized sets of parallel hyperplanes, there exists an affine subspace that accounts for a large (i.e., $2^{-{operatorname{polylog}(d)}}$) fraction of the incidences. Alternatively, our conjecture may be interpreted linear-algebraically as follows: Any rank-$d$ matrix containing at most $O(1)$ distinct entries in each column contains a submatrix of fractional size $2^{-{operatorname{polylog}(d)}}$, in which each column contains one distinct entry. We prove that our conjecture is equivalent to the log-rank conjecture. Motivated by the connections above, we revisit well-studied questions in point-hyperplane incidence geometry without structural assumptions (i.e., the existence of partitions). We give an elementary argument for the existence of complete bipartite subgraphs of density $Omega(epsilon^{2d}/d)$ in any $d$-dimensional configuration with incidence density $epsilon$. We also improve an upper-bound construction of Apfelbaum and Sharir (SIAM J. Discrete Math. 07), yielding a configuration whose complete bipartite subgraphs are exponentially small and whose incidence density is $Omega(1/sqrt d)$. Finally, we discuss various constructions (due to others) which yield configurations with incidence density $Omega(1)$ and bipartite subgraph density $2^{-Omega(sqrt d)}$. Our framework and results may help shed light on the difficulty of improving Lovetts $tilde{O}(sqrt{operatorname{rank}(f)})$ bound (J. ACM 16) for the log-rank conjecture; in particular, any improvement on this bound would imply the first bipartite subgraph size bounds for parallel $3$-partitioned configurations which beat our generic bounds for unstructured configurations.

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