The Large Deviation Principle for Interacting Dynamical Systems on Random Graphs

The Large Deviation Principle for Interacting Dynamical Systems on Random Graphs
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随机图上相互作用动力系统的大偏差原理

DOI:
10.1007/s00220-022-04312-1
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发表时间:
2022
影响因子:
2.4
通讯作者:
Medvedev, Georgi S.
Medvedev, Georgi S.
中科院分区:
物理与天体物理2区
文献类型:
--
作者:
Dupuis, Paul;Medvedev, Georgi S.

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利用大偏差的弱收敛方法,给出并证明了割范数拓扑下W-随机图的大偏差原理。这推广了Chatterjee和Varadhan关于Erdös-Rényi随机图的LDP。此外,我们翻译的随机图的LDP一类相互作用的动力系统,这样的图。为此,我们证明了动力学模型的解决方案连续依赖于基本图形的切割规范和应用收缩原理。
Using the weak convergence approach to large deviations, we formulate and prove the large deviation principle (LDP) for W-random graphs in the cut-norm topology. This generalizes the LDP for Erdős–Rényi random graphs by Chatterjee and Varadhan. Furthermore, we translate the LDP for random graphs to a class of interacting dynamical systems on such graphs. To this end, we demonstrate that the solutions of the dynamical models depend continuously on the underlying graphs with respect to the cut-norm and apply the contraction principle.
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DOI: 10.4310/cms.2019.v17.n4.a1
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