NetworkDynamics.jl -- Composing and simulating complex networks in Julia
| Autor: | Hans Würfel, Michael Lindner, Fenja Drauschke, Frank Hellmann, Lucas Lincoln, Julia Monika Koulen, Anton Plietzsch |
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| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
FOS: Computer and information sciences
G.4 Physics - Physics and Society Dynamical systems theory Artificial neural network Automatic differentiation Computer science Applied Mathematics General Physics and Astronomy FOS: Physical sciences Statistical and Nonlinear Physics Parallel computing Physics and Society (physics.soc-ph) Complex network Solver Symbolic computation Data structure 01 natural sciences 010305 fluids & plasmas Dynamic programming 0103 physical sciences Computer Science - Mathematical Software 010306 general physics Mathematical Software (cs.MS) Mathematical Physics |
| Popis: | NetworkDynamics.jl is an easy-to-use and computationally efficient package for working with heterogeneous dynamical systems on complex networks, written in Julia, a high-level, high-performance, dynamic programming language. By combining state of the art solver algorithms from DifferentialEquations.jl with efficient data structures, NetworkDynamics.jl achieves top performance while supporting advanced features like events, algebraic constraints, time-delays, noise terms and automatic differentiation. This article may be downloaded for personal use only. Any other use requires prior permission of the author and AIP Publishing. This article appeared in Chaos 31, 063133 (2021) and may be found at https://aip.scitation.org/doi/10.1063/5.0051387 |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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