The Energy Landscape of the Kuramoto Model in Random Geometric Graphs in a Circle

被引:0
作者
De Vita, Cecilia [1 ,2 ]
Bonder, Julian Fernandez [1 ,3 ]
Groisman, Pablo [1 ,2 ]
机构
[1] Univ Buenos Aires, Fac Ciencias Exactas & Nat, Dept Matemat, Buenos Aires, Argentina
[2] UBA, CONICET, IMAS, Buenos Aires, Argentina
[3] UBA, Inst Calculo, CONICET, Buenos Aires, Argentina
关键词
interacting dynamical systems; Kuramoto model; geometric random graphs; twisted states; energy landscape; nonconvex optimization; synchronization; TWISTED STATES; SYNCHRONIZATION; POPULATIONS; STABILITY; NETWORKS;
D O I
10.1137/24M1642111
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
We study the energy function of the Kuramoto model in random geometric graphs defined in the unit circle as the number of nodes diverges. We prove the existence of at least one local minimum for each winding number q \in \BbbZ with high probability, hence providing a large family of graphs that support patterns that are generic. These states are in correspondence with the explicit twisted states found in WSG and other highly symmetric networks, but in our situation there is no explicit formula due to the lack of symmetry. The method of proof is simple and robust. It allows other types of graphs like knn graphs or the boolean model and holds also for graphs defined in any simple closed curve or even a small neighborhood of the curve and for weighted graphs. It seems plausible that the method can be extended also to higher dimensions, but a more careful analysis is required.
引用
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页码:1 / 15
页数:15
相关论文
共 28 条
[1]  
Abdalla P, 2024, SIAM J APPL DYN SYST, V23, P779, DOI 10.1137/23M1559270
[2]  
Abdalla P, 2024, Arxiv, DOI arXiv:2210.12788
[3]   The Kuramoto model:: A simple paradigm for synchronization phenomena [J].
Acebrón, JA ;
Bonilla, LL ;
Vicente, CJP ;
Ritort, F ;
Spigler, R .
REVIEWS OF MODERN PHYSICS, 2005, 77 (01) :137-185
[4]   Synchronization in complex networks [J].
Arenas, Alex ;
Diaz-Guilera, Albert ;
Kurths, Jurgen ;
Moreno, Yamir ;
Zhou, Changsong .
PHYSICS REPORTS-REVIEW SECTION OF PHYSICS LETTERS, 2008, 469 (03) :93-153
[5]   The loss surfaces of neural networks with general activation functions [J].
Baskerville, Nicholas P. ;
Keating, Jonathan P. ;
Mezzadri, Francesco ;
Najnudel, Joseph .
JOURNAL OF STATISTICAL MECHANICS-THEORY AND EXPERIMENT, 2021, 2021 (06)
[6]   Fit without fear: remarkable mathematical phenomena of deep learning through the prism of interpolation [J].
Belkin, Mikhail .
ACTA NUMERICA, 2021, 30 :203-248
[7]   Reconciling modern machine-learning practice and the classical bias-variance trade-off [J].
Belkin, Mikhail ;
Hsu, Daniel ;
Ma, Siyuan ;
Mandal, Soumik .
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2019, 116 (32) :15849-15854
[8]   Synchronization and random long time dynamics for mean-field plane rotators [J].
Bertini, Lorenzo ;
Giacomin, Giambattista ;
Poquet, Christophe .
PROBABILITY THEORY AND RELATED FIELDS, 2014, 160 (3-4) :593-653
[9]  
Bullo F., 2022, Lectures on Network Systems, V1st
[10]   THE MEAN FIELD ANALYSIS OF THE KURAMOTO MODEL ON GRAPHS I. THE MEAN FIELD EQUATION AND TRANSITION POINT FORMULAS [J].
Chiba, Hayato ;
Medvedev, Georgi S. .
DISCRETE AND CONTINUOUS DYNAMICAL SYSTEMS, 2019, 39 (01) :131-155