Description
TL;DR: A mathematical consensus algorithm designed to reach agreement in fewer neighbor-to-neighbor iterations than standard linear updates.
About This Document
Eduardo Montijano, Juan I. Montijano, and Carlos Sagues build a distributed update rule from the second-order recurrence of first-kind Chebyshev polynomials. Agents exchange only their current state with neighbors, while spectral bounds and numerical experiments characterize convergence speed and robustness across network graphs.
Why Bitcoin People May Care
This is not Bitcoin or blockchain consensus. The agents converge on numeric values in a graph; they do not validate transactions or withstand permissionless economic attack. The paper is relevant distributed-systems background because topology, spectral properties, and message rounds also influence decentralized networks. Results apply to its linear consensus model and assumptions.
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Document Details
- Title: Chebyshev Polynomials in Distributed Consensus
- Author / organization: Eduardo Montijano, Juan I. Montijano, and Carlos Sagues
- Year: 2012
- Language: English
- Document type: Distributed-consensus research paper
- Pages: 31
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