| Project/Area Number |
24740266
|
|---|
| Research Category |
Grant-in-Aid for Young Scientists (B)
|
| Allocation Type | Multi-year Fund |
|---|
| Research Field |
Mathematical physics/Fundamental condensed matter physics
|
|---|
| Research Institution | Kagawa University |
|---|
Principal Investigator |
Aoki Takaaki 香川大学, 教育学部, 准教授 (30553284)
|
|---|
| Project Period (FY) |
2012-04-01 – 2016-03-31
|
| Project Status |
Completed (Fiscal Year 2015)
|
| Budget Amount *help |
¥4,420,000 (Direct Cost: ¥3,400,000、Indirect Cost: ¥1,020,000)
Fiscal Year 2015: ¥780,000 (Direct Cost: ¥600,000、Indirect Cost: ¥180,000)
Fiscal Year 2014: ¥780,000 (Direct Cost: ¥600,000、Indirect Cost: ¥180,000)
Fiscal Year 2013: ¥780,000 (Direct Cost: ¥600,000、Indirect Cost: ¥180,000)
Fiscal Year 2012: ¥2,080,000 (Direct Cost: ¥1,600,000、Indirect Cost: ¥480,000)
|
|---|
| Keywords | ネットワーク科学 / Adaptive network / complex network / adaptive network / complex nework / temporal network / 複雑ネットワーク / ネットワークの力学モデル / 自己組織化 / ネットワークの動的構造 / 反応拡散系 / ネットワーク / 複雑系 |
|---|
| Outline of Final Research Achievements |
Real-world networks are not static, but continuously change to meet the evolving needs of society. To know where the networks will change, we need to understand the nature of changing networks, in which the reformation of the networks and the dynamical processes occurring on the network are interdependent. To understand the mechanisms governing such dynamical organization, we proposed a simple model of co-evolving network dynamics, combining the dynamics of random walkers and the dynamics of the weighted network. We found that under suitable conditions, the density of walkers and the link weights converge to stationary power-law distributions at the macroscopic level, but they continue to change with time at the microscopic level, even though the dynamics of the proposed model is completely deterministic. We numerically and theoretically analyzed the equilibrium states from perspective of the dynamical system and found that the system has multi-stability including chaotic states.
|
