Abstract
Now that we have discussed several families of models as motivation (and because they are interesting in their own right), we present some general considerations for studying dynamical systems on networks. We alluded to several of these ideas in our prior discussions.
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Notes
- 1.
Note that we previously used the notation \(\lambda\) in Sec. 3.2.1 to represent the transmission rate in the SI model. In this section, we use \(\lambda\) with appropriate subscripts to represent the eigenvalues of A.
- 2.
Although we were able to separate the dependence on structure and dynamics in our example, note that the analysis is more complicated when the equilibrium points are different for different nodes and when considering other types of behavior (e.g., periodic or chaotic dynamics) [244].
- 3.
See [175] for a discussion of tensors.
- 4.
When calculating a sample mean using numerical simulations of a dynamical system on a network (or a family of networks), there are several possible sources of stochasticity: (1) choice of initial condition, (2) choice of which nodes to update (when considering asynchronous updating), (3) the update rule itself, (4) parameter values that are used in an update rule, and (5) selection of particular networks from a random-graph ensemble. Some or all of these sources of randomness can be present when studying dynamical systems on networks, and (when possible) it is also desirable to compare the sample means to ensemble averages (i.e., expectations over a suitable probability distribution).
- 5.
It may also be useful to develop analogous class-based approximations that use structural characteristics other than degree.
References
A. Arenas, A. DÃaz-Guilera, J. Kurths, Y. Moreno, C. Zhou, Synchronization in complex networks. Phys. Rep. 469(3), 93–153 (2008)
M. Barahona, L. Pecora, Synchronization in small world systems. Phys. Rev. Lett. 89(5), 054101 (2002)
V.N. Belykh, I.V. Belykh, M. Hasler, Connection graph stability method for synchronized coupled chaotic systems. Physica D 195(1–2), 159–187 (2004)
I.V. Belykh, V.N. Belykh, M. Hasler, Blinking model and synchronization in small-world networks with a time-varying coupling. Physica D 195(1–2), 188–206 (2004)
S. Boccaletti, G. Bianconi, R. Criado, C.I. del Genio, J. Gómez-Gardeñes, M. Romance, I. Sendiña-Nadal, Z. Wang, M. Zanin, The structure and dynamics of multilayer networks. Phys. Rep. 544(1), 1–122 (2014)
M. Boguñá, R. Pastor-Satorras, Epidemic spreading in correlated complex networks. Phys. Rev. E 66(4), 047104 (2002)
G.A. Böhme, T. Gross, Analytical calculation of fragmentation transitions in adaptive networks. Phys. Rev. E 83(3), 35101 (2011)
K.A. Bold, K. Rajendran, B. Ráth, I.G. Kevrekidis, An equation-free approach to coarse-graining the dynamics of networks. J. Comput. Dyn. 1(1), 111–134 (2014)
F. Brauer, C. Castillo-Chavez, Mathematical Models in Population Biology and Epidemiology, 2nd edn. (Springer, New York, 2012)
L.A. Bunimovich, B.Z. Webb, Isospectral compression and other useful isospectral transformations of dynamical networks. Chaos 22(3), 033118 (2012)
L.A. Bunimovich, B.Z. Webb, Isospectral graph transformations, spectral equivalence, and global stability of dynamical networks. Nonlinearity 25(1), 211–254 (2012)
G. Craciun, M. Feinberg, Multiple equilibria in complex chemical reaction networks. I. The injectivity property. SIAM J. Appl. Math. 65(5), 1526–1546 (2005)
G. Craciun, M. Feinberg, Multiple equilibria in complex chemical reaction networks. II. The species-reaction graph. SIAM J. Appl. Math. 66(4), 1321–1338 (2006)
G. Demirel, F. Vázquez, G.A. Bhöme, T. Gross, Moment-closure approximations for discrete adaptive networks. Physica D 267(1), 68–80 (2014)
A.-L. Do, S. Boccaletti, T. Gross, Graphical notation reveals topological stability criteria for collective dynamics in complex networks. Phys. Rev. Lett. 108(19), 194102 (2012)
P.S. Dodds, K.D. Harris, C.M. Danforth, Limited imitation contagion on random networks: Chaos, universality, and unpredictability. Phys. Rev. Lett. 110(15), 158701 (2013)
J. Epperlain, A.-L. Do, T. Gross, S. Siegmund, Meso-scale obstructions to stability of 1D center manifolds for networks of coupled differential equations with symmetric Jacobian. Physica D 261(3), 1–7 (2013)
K.S. Fink, G. Johnson, T. Carroll, D. Mar, L. Pecora, Three coupled oscillators as a universal probe of synchronization stability in coupled oscillator arrays. Phys. Rev. E 61(5), 5080–5090 (2000)
T. Gedeon, S. Harker, H. Kokubu, K. Mischaikow, H. Ok, Global dynamics for steep sigmoidal nonlinearities in two dimensions (2015). arXiv:1508.02438
J.P. Gleeson, High-accuracy approximation of binary-state dynamics on networks. Phys. Rev. Lett. 107(6), 068701 (2011)
J.P. Gleeson, Binary-state dynamics on complex networks: Pair approximation and beyond. Phys. Rev. X 3(2), 021004 (2013)
J.P. Gleeson, S. Melnik, J.A. Ward, M.A. Porter, P.J. Mucha, Accuracy of mean-field theory for dynamics on real-world networks. Phys. Rev. E 85(2), 026106 (2012)
M. Golubitsky, R. Lauterbach, Bifurcations from synchrony in homogeneous networks: Linear theory. SIAM J. Appl. Dyn. Syst. 8(1), 40–75 (2009)
M. Golubitsky, I. Stewart, Patterns of synchrony in coupled cell networks with multiple arrows. SIAM J. Appl. Dyn. Syst. 4(1), 78–100 (2005)
E. Gross, H.A. Harrington, Z. Rosen, B. Sturmfels, Algebraic systems biology: A case study for the Wnt pathway (2015). arXiv:1502.03188
J. Guckenheimer, P. Holmes, Nonlinear Oscillations, Dynamical Systems, and Bifurcations of Vector Fields. Number 42 in Applied Mathematical Sciences (Springer, New York, 1983)
H.A. Harrington, K.L. Ho, T. Thorne, M.P.H. Stumpf, Parameter-free model discrimination criterion based on steady-state coplanarity. Proc. Natl. Acad. Sci. U. S. A. 109(39), 15746–15751 (2012)
T. House, Algebraic moment closure for population dynamics on discrete structures. Bull. Math. Biol. 77(4), 646–659 (2015)
T. Ichinomiya, Frequency synchronization in a random oscillator network. Phys. Rev. E 70(2), 026116 (2004)
B. Joshi, A. Shiu, A survey of methods for deciding whether a reaction network is multistationary. Math. Model. Nat. Phenom. 10(5), 47–67 (2015)
M. Kivelä, A. Arenas, M. Barthelemy, J.P. Gleeson, Y. Moreno, M.A. Porter. Multilayer networks. J. Complex Networks 2(3), 203–271 (2014)
T.G. Kolda, B.W. Bader, Tensor decompositions and applications. SIAM Rev. 51(3), 455–500 (2009)
C. Kuehn, Moment closure — A brief review (2015). arXiv:1505.02190,
J. Li, W.-X. Wang, Y.-C. Lai, C. Grebogi, Reconstructing complex networks with binary-state dynamics (2015). arXiv:1511.06852
J. Lindquist, J. Ma, P. van den Driessche, F.H. Willeboordse, Effective degree network disease models. J. Math. Biol. 62(2), 143–164 (2011)
A.L. MacLean, Z. Rosen, H. Byrne, H.A. Harrington, Parameter-free methods distinguish Wnt pathway models and guide design of experiments. Proc. Natl. Acad. Sci. U.S.A. 112(9), 2652–2657 (2015)
V. Marceau, P.-A. Noël, L. Hébert-Dufresne, A. Allard, L.J. Dubé, Adaptive networks: Coevolution of disease and topology. Phys. Rev. E 82(3), 036116 (2010)
G.S. Medvedev, The nonlinear heat equation on dense graphs and graph limits. SIAM J. Math. Anal. 46(4), 2743–2766 (2014)
G.S. Medvedev, X. Tang, Stability of twisted states in the Kuramoto model on Cayley and random graphs. J. Nonlinear Sci. 25(6), 1169–1208 (2015)
D. Mehta, N. Daleo, F. Dörfler, J.D. Hauenstein, Algebraic geometrization of the Kuramoto model: Equilibria and stability analysis (2014). arXiv:1412.0666
S. Melnik, J.A. Ward, J.P. Gleeson, M.A. Porter, Multi-stage complex contagions. Chaos 23(1), 013124 (2013)
J.C. Miller, A note on a paper by Erik Volz: SIR dynamics in random networks. J. Math. Biol. 62(3), 349–358 (2011)
J.C. Miller, I.Z. Kiss, Epidemic spread in networks: Existing methods and current challenges. Math. Modell. Nat. Phenom. 9(2), 4–42, 1 (2014)
M.E.J. Newman, Networks: An Introduction (Oxford University Press, Oxford, 2010)
T. Nishikawa, A.E. Motter, Y.-C. Lai, F.C. Hoppensteadt, Heterogeneity in oscillator networks: Are smaller worlds easier to synchronize? Phys. Rev. Lett. 91(1), 014101 (2003)
R. Pastor-Satorras, A. Vespignani, Epidemic spreading in scale-free networks. Phys. Rev. Lett. 86(14), 3200 (2001)
R. Pastor-Satorras, C. Castellano, P. Van Mieghem, A. Vespignani, Epidemic processes in complex networks. Rev. Mod. Phys. 87(4), 925–979 (2015)
L.M. Pecora, T.L. Carroll, Master stability functions for synchronized coupled systems. Phys. Rev. Lett. 80(10), 2109–2112 (1998)
L.M. Pecora, T.L. Carroll, Master stability function for globally synchronized systems, in Encyclopedia of Computational Neuroscience, ed. by D. Jaeger, R. Jung (Springer, New York, 2014), pp. 1–13
L.M. Pecora, T.L. Caroll, Synchronization of chaotic systems. Chaos 25(9), 097611 (2015)
M.A. Porter, Small-world network. Scholarpedia 7(2), 1739 (2012)
G.X. Qi, H.B. Huang, C.K. Shen, H.J. Wang, L. Chen, Predicting the synchronization time in coupled-map networks. Phys. Rev. E 77(5), 056205 (2008)
K. Rajendran, I.G. Kevrekidis, Coarse graining the dynamics of heterogeneous oscillators in networks with spectral gaps. Phys. Rev. E 84(3), 036708 (2011)
A. Solé-Ribalta, M. De Domenico, N.E. Kouvaris, A. DÃaz-Guilera, S.Gómez, and A. Arenas. Spectral properties of the Laplacian of multiplex networks. Phys. Rev. E 88(3), 032807 (2013)
I. Stewart, M. Golubitsky, M. Pivato, Symmetry groupoids and patterns of synchrony in coupled cell networks. SIAM J. Appl. Dyn. Syst. 2(4), 609–646 (2003)
S.H. Strogatz, Nonlinear Dynamics and Chaos (Addison-Wesley, Massachusetts, 1994)
J. Sun, E.M. Bollt, T. Nishikawa, Master stability functions for coupled nearly identical dynamical systems. Europhys. Lett. 85(6), 60011 (2011)
T.J. Taylor, I.Z. Kiss, Interdependency and hierarchy of exact and approximate epidemic models on networks. J. Math. Biol. 69(1), 183–211 (2014)
D. Taylor, F. Klimm, H.A. Harrington, M. Kramár, K. Mischaikow, M.A. Porter, P.J. Mucha, Topological data analysis of contagion maps for examining spreading processes on networks. Nat. Commun. 6, 7723 (2015)
P. Van Mieghem, Graph Spectra for Complex Networks (Cambridge University Press, Cambridge, 2013)
A. Vespignani, Modelling dynamical processes in complex socio-technical systems. Nat. Phys. 8(1), 32–39 (2012)
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Porter, M.A., Gleeson, J.P. (2016). General Considerations. In: Dynamical Systems on Networks. Frontiers in Applied Dynamical Systems: Reviews and Tutorials, vol 4. Springer, Cham. https://doi.org/10.1007/978-3-319-26641-1_4
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