Network evolution with mesoscopic delay Article Swipe

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Sayan Banerjee , Shankar Bhamidi , Partha S. Dey , Akshay Sakanaveeti ·

YOU? · · 2024 · Open Access · · DOI: https://doi.org/10.48550/arxiv.2409.10307

Owing to the influence of real-world networks both in science and society, numerous mathematical models have been developed to understand the structure and evolution of these systems, particularly in a temporal context. Recent advancements in fields like distributed cyber-security and social networks have spurred the creation of probabilistic models of evolution, where individuals make decisions based on only partial information about the network's current state. This paper seeks to explore models incorporating network delay, where new participants receive information from a time-lagged snapshot of the system. In the context of mesoscopic network delays, we develop probabilistic tools built on stochastic approximation to understand asymptotics of both local functionals, such as local neighborhoods and degree distributions, as well as global properties, such as the evolution of the degree of the network's initial founder. A companion paper explores the regime of macroscopic delays in the evolution of the network.

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Computer Science

Physics

Condensed Matter Physics

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Mesoscopic physics Computer science Physics Condensed matter physics

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Type: preprint
Language: en
Landing Page: http://arxiv.org/abs/2409.10307
PDF: https://arxiv.org/pdf/2409.10307
OA Status: green
Related Works: 10
OpenAlex ID: https://openalex.org/W4403702709

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OpenAlex ID: https://openalex.org/W4403702709

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DOI: https://doi.org/10.48550/arxiv.2409.10307

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Title: Network evolution with mesoscopic delay

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Type: preprint

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Language: en

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Publication year: 2024

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Publication date: 2024-09-16

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Authors: Sayan Banerjee, Shankar Bhamidi, Partha S. Dey, Akshay Sakanaveeti

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Landing page: https://arxiv.org/abs/2409.10307

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PDF URL: https://arxiv.org/pdf/2409.10307

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Open access: Yes

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OA status: green

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OA URL: https://arxiv.org/pdf/2409.10307

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Concepts: Mesoscopic physics, Computer science, Physics, Condensed matter physics

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Cited by: 0

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Related works (count): 10

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