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arxiv: 2501.17657 · v2 · pith:SOMMCTNRnew · submitted 2025-01-29 · 🧮 math.CO · cs.DM

Belief Propagation Guided Decimation on Random k-XORSAT

classification 🧮 math.CO cs.DM
keywords algorithmdecimationanalysebeliefguidedperformancephaseprobability
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We analyse the performance of Belief Propagation Guided Decimation, a physics-inspired message passing algorithm, on the random $k$-XORSAT problem. Specifically, we derive an explicit threshold up to which the algorithm succeeds with a strictly positive probability $\Omega(1)$ that we compute explicitly, but beyond which the algorithm with high probability fails to find a satisfying assignment. In addition, we analyse a thought experiment called the decimation process for which we identify a (non-) reconstruction and a condensation phase transition. The main results of the present work confirm physics predictions from [RTS: J. Stat. Mech. 2009] that link the phase transitions of the decimation process with the performance of the algorithm, and improve over partial results from a recent article [Yung: Proc. ICALP 2024].

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