Abstract
This paper introduces a small-world (SW) network with a power-law distance distribution that differs from conventional models in that it uses completely random shortcuts. By incorporating spatial constraints, we analyze the divergence of the proposed model from conventional models in terms of fundamental network properties such as clustering coefficient, average path length, and degree distribution. We find that when the spatial constraint more strongly prohibits a long shortcut, the clustering coefficient is improved and the average path length increases. We also analyze the spatial prisoner's dilemma (SPD) games played on our new SW network in order to understand its dynamical characteristics. Depending on the basis graph, i.e., whether it is a one-dimensional ring or a two-dimensional lattice, and the parameter controlling the prohibition of long-distance shortcuts, the emergent results can vastly differ.
| Original language | English |
|---|---|
| Pages (from-to) | 408-415 |
| Number of pages | 8 |
| Journal | Physica A: Statistical Mechanics and its Applications |
| Volume | 486 |
| DOIs | |
| Publication status | Published - Nov 15 2017 |
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All Science Journal Classification (ASJC) codes
- Statistics and Probability
- Condensed Matter Physics
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Properties of a new small-world network with spatially biased random shortcuts. / Matsuzawa, Ryo; Tanimoto, Jun; Fukuda, Eriko.
In: Physica A: Statistical Mechanics and its Applications, Vol. 486, 15.11.2017, p. 408-415.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Properties of a new small-world network with spatially biased random shortcuts
AU - Matsuzawa, Ryo
AU - Tanimoto, Jun
AU - Fukuda, Eriko
PY - 2017/11/15
Y1 - 2017/11/15
N2 - This paper introduces a small-world (SW) network with a power-law distance distribution that differs from conventional models in that it uses completely random shortcuts. By incorporating spatial constraints, we analyze the divergence of the proposed model from conventional models in terms of fundamental network properties such as clustering coefficient, average path length, and degree distribution. We find that when the spatial constraint more strongly prohibits a long shortcut, the clustering coefficient is improved and the average path length increases. We also analyze the spatial prisoner's dilemma (SPD) games played on our new SW network in order to understand its dynamical characteristics. Depending on the basis graph, i.e., whether it is a one-dimensional ring or a two-dimensional lattice, and the parameter controlling the prohibition of long-distance shortcuts, the emergent results can vastly differ.
AB - This paper introduces a small-world (SW) network with a power-law distance distribution that differs from conventional models in that it uses completely random shortcuts. By incorporating spatial constraints, we analyze the divergence of the proposed model from conventional models in terms of fundamental network properties such as clustering coefficient, average path length, and degree distribution. We find that when the spatial constraint more strongly prohibits a long shortcut, the clustering coefficient is improved and the average path length increases. We also analyze the spatial prisoner's dilemma (SPD) games played on our new SW network in order to understand its dynamical characteristics. Depending on the basis graph, i.e., whether it is a one-dimensional ring or a two-dimensional lattice, and the parameter controlling the prohibition of long-distance shortcuts, the emergent results can vastly differ.
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UR - http://www.scopus.com/inward/citedby.url?scp=85020793905&partnerID=8YFLogxK
U2 - 10.1016/j.physa.2017.05.031
DO - 10.1016/j.physa.2017.05.031
M3 - Article
AN - SCOPUS:85020793905
VL - 486
SP - 408
EP - 415
JO - Physica A: Statistical Mechanics and its Applications
JF - Physica A: Statistical Mechanics and its Applications
SN - 0378-4371
ER -