array(14 items) uid => 931 (integer) title => 'Cavity approach for the approximation of spectral density of graphs with het
erogeneous structures' (97 chars) abstract => 'Graphs have become widely used to represent and study social, biological, an
d technological systems. Statistical methods to analyze empirical graphs wer
e proposed based on the graph's spectral density. However, their running tim
e is cubic in the number of vertices, precluding direct application to large
instances. Thus, efficient algorithms to calculate the spectral density bec
ome necessary. For sparse graphs, the cavity method can efficiently approxim
ate the spectral density of locally treelike undirected and directed graphs.
However, it does not apply to most empirical graphs because they have heter
ogeneous structures. Thus, we propose methods for undirected and directed gr
aphs with heterogeneous structures using a new vertex's neighborhood definit
ion and the cavity approach. Our methods' time and space complexities are O(
|E|h_{max}^{3}t) and O(|E|h_{max}^{2}t), respectively, where |E| is the numb
er of edges, h_{max} is the size of the largest local neighborhood of a vert
ex, and t is the number of iterations required for convergence. We demonstra
te the practical efficacy by estimating the spectral density of simulated an
d real-world undirected and directed graphs.' (1184 chars) authors => array(3 items) 0 => array(3 items) last_name => 'Guzman' (6 chars) first_name => 'Grover E. C.' (13 chars) sorting => 1 (integer) 1 => array(3 items) last_name => 'Stadler' (7 chars) first_name => 'Peter Florian' (13 chars) sorting => 2 (integer) 2 => array(3 items) last_name => 'Fujita' (6 chars) first_name => 'André' (6 chars) sorting => 3 (integer) type => '0' (1 chars) keywords => '' (0 chars) year => 2024 (integer) affiliation => 1 (integer) link_paper => '' (0 chars) link_supplements => '' (0 chars) file_published => 0 (integer) journal => 'Physical Review E' (17 chars) doi => '10.1103/PhysRevE.109.034303' (27 chars) preprint => '-1' (2 chars)
Cavity approach for the approximation of spectral density of graphs with heterogeneous structures
2024: Grover E. C. Guzman; Peter Florian Stadler; André FujitaIn: Physical Review E DOI: 10.1103/PhysRevE.109.034303
Graphs have become widely used to represent and study social, biological, and technological systems. Statistical methods to analyze empirical graphs were proposed based on the graph's spectral density. However, their running time is cubic in the number of vertices, precluding direct application to large instances. Thus, efficient algorithms to calculate the spectral density become necessary. For sparse graphs, the cavity method can efficiently approximate the spectral density of locally treelike undirected and directed graphs. However, it does not apply to most empirical graphs because they have heterogeneous structures. Thus, we propose methods for undirected and directed graphs with heterogeneous structures using a new vertex's neighborhood definition and the cavity approach. Our methods' time and space complexities are O(|E|h_{max}^{3}t) and O(|E|h_{max}^{2}t), respectively, where |E| is the number of edges, h_{max} is the size of the largest local neighborhood of a vertex, and t is the number of iterations required for convergence. We demonstrate the practical efficacy by estimating the spectral density of simulated and real-world undirected and directed graphs.