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The random graph process is globally synchronizing

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arxiv 2501.12205 v1 pith:G32CQ6FN submitted 2025-01-21 math.CO math.PR

classification math.COmath.PR
keywords graphgloballysynchronizingconditioneveryhomogeneouskuramotomodel
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abstract

The homogeneous Kuramoto model on a graph $G = (V,E)$ is a network of $|V|$ identical oscillators, one at each vertex, where every oscillator is coupled bidirectionally (with unit strength) to its neighbors in the graph. A graph $G$ is said to be globally synchronizing if, for almost every initial condition, the homogeneous Kuramoto model converges to the all-in-phase synchronous state. Confirming a conjecture of Abdalla, Bandeira, Kassabov, Souza, Strogatz, and Townsend, we show that with high probability, the random graph process becomes globally synchronizing as soon as it is connected. This is best possible, since connectivity is a necessary condition for global synchronization.

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Cited by 3 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Spectra of high-dimensional sparse random geometric graphs

    math.PR 2025-07 conditional novelty 8.0 of 10

    Under mild dimension conditions, the empirical spectral distribution of sparse high-dimensional random geometric graphs matches the semicircle law or the Erdős-Renyi limit.

  2. Synchronization of mean-field models on the circle

    math.DS 2025-07 conditional novelty 7.0 of 10

    A new criterion based on the L1 norm of the third derivative of the interaction function establishes global synchronization for circle mean-field models, resolving the self-attention synchronization question for β ≥ -0.16.

  3. Critical attention scaling in long-context transformers

    cs.LG 2025-10 conditional novelty 6.0 of 10

    In a simplified attention model with normalized tokens, the phase boundary between token collapse and identity attention occurs when the attention-temperature scaling factor β_n is of order log n, with constant 1/(1−ρ).

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