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Nearly-Optimal Time-Sample Trade-off in Consensus Dynamics

Oct 29, 2026 Source ↗

Key Insights

How does the number of sampled opinions affect the time required to reach consensus in distributed consensus dynamics? We study the synchronous $h$-\textsf{Majority}, in which every node independently.

Cite this synthesis DOI: 10.48550/arXiv.2610.40562 ↗

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@misc{ acaciadata-research-nearly-optimal-time-sample-trade-off-in-consensus-dynamics,
  title = { Nearly-Optimal Time-Sample Trade-off in Consensus Dynamics },
  author = { Leszek },
  year = { 2026 },
  doi = { 10.48550/arXiv.2610.40562 },
  url = { http://arxiv.org/abs/2610.40562v1 },
  note = {Summarized and classified by AcaciaFund}
}

TY  - GEN
TI  - Nearly-Optimal Time-Sample Trade-off in Consensus Dynamics
AU  - Leszek
PY  - 2026
DO  - 10.48550/arXiv.2610.40562
UR  - http://arxiv.org/abs/2610.40562v1
ER  -

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Overview

How does the number of sampled opinions affect the time required to reach consensus in distributed consensus dynamics? We study the synchronous $h$-\textsf{Majority}, in which every node independently

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Distributed Systems: A theme covered by this item within the data engineering context.

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Article Metadata

Evergreen Synthesized

distributed-systems dataops

DataOps Distributed Systems for Data

SQI 0.750