NP-Completeness of Deterministic Communication Complexity via Relaxed Interlacing

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Hauptverfasser: Gaspers, Serge, He, Tao Zixu, Mackenzie, Simon
Format: Preprint
Veröffentlicht: 2025
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author Gaspers, Serge
He, Tao Zixu
Mackenzie, Simon
author_facet Gaspers, Serge
He, Tao Zixu
Mackenzie, Simon
contents We prove that computing the deterministic communication complexity of a Boolean function, given its truth table, is \textsf{NP}-complete in the standard protocol-tree-depth model, addressing a meta-complexity question raised by Yao in 1979. The reduction is from \(\{0,1\}\)-Vector Bin Packing and produces, in polynomial time, a communication matrix whose optimal protocol depth exhibits a one-bit gap between satisfiable and unsatisfiable instances. The main technical contribution is the \emph{relaxed-interlacing} framework that makes this reduction possible. It replaces exponential-size Cartesian products with polynomial-size almost \(t\)-wise independent column sets, a pseudorandom substitute for full products, while preserving the lower-bound and protocol-control statements needed for the reduction. We develop these statements in two stages: first for classical interlacing, where projection arguments give clean lower bounds and separation statements, and then for relaxed interlacing, where a bridge lemma recovers the classical lower-bound and separation statements with controlled density loss. This leads to an extension theorem that lifts the classical lower bound to the relaxed setting and a near-exact separation theorem that lifts the corresponding protocol-control statement, with the present \textsf{NP}-completeness theorem as their main application here.
format Preprint
id arxiv_https___arxiv_org_abs_2508_05597
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle NP-Completeness of Deterministic Communication Complexity via Relaxed Interlacing
Gaspers, Serge
He, Tao Zixu
Mackenzie, Simon
Computational Complexity
Data Structures and Algorithms
Combinatorics
We prove that computing the deterministic communication complexity of a Boolean function, given its truth table, is \textsf{NP}-complete in the standard protocol-tree-depth model, addressing a meta-complexity question raised by Yao in 1979. The reduction is from \(\{0,1\}\)-Vector Bin Packing and produces, in polynomial time, a communication matrix whose optimal protocol depth exhibits a one-bit gap between satisfiable and unsatisfiable instances. The main technical contribution is the \emph{relaxed-interlacing} framework that makes this reduction possible. It replaces exponential-size Cartesian products with polynomial-size almost \(t\)-wise independent column sets, a pseudorandom substitute for full products, while preserving the lower-bound and protocol-control statements needed for the reduction. We develop these statements in two stages: first for classical interlacing, where projection arguments give clean lower bounds and separation statements, and then for relaxed interlacing, where a bridge lemma recovers the classical lower-bound and separation statements with controlled density loss. This leads to an extension theorem that lifts the classical lower bound to the relaxed setting and a near-exact separation theorem that lifts the corresponding protocol-control statement, with the present \textsf{NP}-completeness theorem as their main application here.
title NP-Completeness of Deterministic Communication Complexity via Relaxed Interlacing
topic Computational Complexity
Data Structures and Algorithms
Combinatorics
url https://arxiv.org/abs/2508.05597