A boundary-preserving semantic-compilation theorem converts known one-way, streaming, and contextuality separations into architecture-independent coordination-width lower bounds for AI state-tracking solvers, with three worked applications including an n-qubit versus Omega(n^2)-bit stabilizer…
Exponential Quantum Space Advantage for Approximating Max-$k$SAT in the Streaming Setting
1 Pith paper cite this work. Polarity classification is still indexing.
abstract
In this paper, we give a one-pass quantum streaming algorithm for Max-$k$SAT that uses $\operatorname{polylog}(n)$ space and achieves a $0.7172$-approximation on instances with $n$ variables. In contrast, prior work by Chou, Golovnev, and Velusamy (FOCS 2020) implies that achieving an approximation ratio better than $\sqrt{2}/2 \approx 0.7071$ for Max-$k$SAT requires $\Omega(\sqrt{n})$ space for any classical streaming algorithm. Therefore, it yields an exponential quantum space advantage for Max-$k$SAT in the streaming setting. We further give a one-pass quantum streaming algorithm for Max-2OR that uses $\operatorname{polylog}(n)$ space and achieves a $0.7425$-approximation on instances with $n$ variables. Combining with the known results, it gives a complete classification of quantum space advantages for all Boolean Max-2CSPs.
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quant-ph 1years
2026 1verdicts
CONDITIONAL 1representative citing papers
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Quantum Coordination Advantages in AI State-Tracking Tasks: Semantic Compilation and Latent Memory
A boundary-preserving semantic-compilation theorem converts known one-way, streaming, and contextuality separations into architecture-independent coordination-width lower bounds for AI state-tracking solvers, with three worked applications including an n-qubit versus Omega(n^2)-bit stabilizer…