Pre-Made Systems and Parameters

There will be a list of all pre-made systems and parameters here.

MCBB.DEParametersType
DEParameters

Abstract type for all parameter types. If you define your own systems the parameters have to have this as a supertype.

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MCBB.logisticFunction
logistic(u_next, u, p::logistic_parameters, t)

Logistic Map: $x_{n+1} = rx_n (1 - x_n)$

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MCBB.henonFunction
henon(u_next, u, p::henon_parameters, t)

Henon map. $x_{n+1} = 1 - a x_{n}^2 + y_{n}$ $y_{n+1} = b x_{n}$

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MCBB.kuramotoFunction
kuramoto(du, u, p::kuramoto_parameters, t)

First order Kuramoto system with all-to-all coupling. $\dot{\theta}_i = w_i + K/N \sum_{i} \sin(\theta_j - \theta_i)$

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MCBB.kuramoto_parametersType
kuramoto_parameters

Parameters of a first order Kuramoto system with all-to-all coupling. Fields:

  • K::Number: Coupling Strength
  • w::Array{Float64}: Eigenfrequencies
  • N::Int: Number of Oscillators
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MCBB.kuramoto_networkFunction
kuramoto_network(du, u, p::kuramoto_parameters, t)

First order Kuramoto system on a network. $\dot{\theta}_i = w_i + K/N \sum_{i} A_{ij}\sin(\theta_j - \theta_i)$

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MCBB.kuramoto_network_parametersType
kuramoto_network_parameters

Parameters of a first order Kuramoto system on a network. Fields:

  • K::Number: Coupling Strength
  • w::Array{Float64}: Eigenfrequencies
  • N::Int: Number of Oscillators
  • A: Adjacency matrix
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MCBB.second_order_kuramotoFunction
second_order_kuramoto(du, u, p::second_order_kuramoto_parameters, t)

Second order Kuramoto system on the adjacency matrix $A_{ij} = E'_{ie} E_{ej}$.

$\dot{\theta}_i = w_i$ $\dot{\omega} = \Omega_i - \alpha\omega + \lambda\sum_{j=1}^N A_{ij} sin(\theta_j - \theta_i)$

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MCBB.second_order_kuramoto_parametersType
second_order_kuramoto_parameters

Fields:

  • systemsize::Int, number of oscillators
  • damping::Float64, Damping, also referred to as $\alpha$
  • coupling::Float64, Coupling strength, also referred to as $\lambda$
  • incidence, oriented incidence matix of the network, also referred to as $\E_{ei}$

indicating if a vertex $i$ belongs to an edge $e$. Following the conventions of LightGraphs

  • drive::Array{Float64}, external driving, also referred to as $\Omega$
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MCBB.second_order_kuramoto_chainFunction
second_order_kuramoto_chain(du, u, p::kuramoto_parameters, t)

Second order Kuramoto system on a chain.

$\dot{\theta}_i = w_i$ $\dot{\omega} = \Omega_i - \alpha\omega + \lambda\sum_{j=1}^N A_{ij} sin(\theta_j - \theta_i)$

$A_{ij} = 1$ if and only if $|i-j|=1$, otherwise $A_{ij}=0$

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MCBB.second_order_kuramoto_chain_parametersType
second_order_kuramoto_chain_parameters

Fields:

  • systemsize::Int, number of oscillators
  • damping::Float64, Damping, also referred to as $\alpha$
  • coupling::Float64, Coupling strength, also referred to as $\lambda$
  • drive::Array{Float64}, external driving, also referred to as $\Omega$
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MCBB.non_local_kuramoto_ringFunction
non_local_kuramoto_ring(du, u, p::non_local_kuramoto_ring_parameters, t)

First order Kuramoto oscillators on a ring with non-local coupling.

$\frac{\theta_k}{dt} = \omega_0 - \sum_{j=1}^N G_1\left(\frac{2\pi}{N}(k-j)\right)\sin\left(\theta_k(t) - \theta_j(k) + \alpha\right)$

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MCBB.non_local_kuramoto_ring_parametersType
non_local_kuramoto_ring_parameters <: DEParameters
  • N::Integer: Number of Oscillators
  • fak::Float64: $\frac{2\pi}{n}$
  • omega_0::Number: eigenfrequency of all oscillators
  • phase_delay: Phase Delay $\alpha$
  • coupling_function: Coupling function $G(x)$, signature (x::Number)-> value::Number
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MCBB.roessler_parametersType
roessler_parameters <: DEParameters

Parameters of a Roessler network

  • a::Array{Float64}: a Parameters of all oscillators.

  • b::Array{Float64}: b Parameters of all oscillators.

  • c::Array{Float64}: c Parameters of all oscillators.

  • K::Float64: Coupling Strength

  • L::Array{Float64}: Laplacian matrix of the network

  • N::Int: Number of nodes/oscilattors

    roessler_parameters(a, b, c, K, k::Int64, p::Float64, N)

Generates a set of roessler_parameters with a Watts Strogatz random Network with mean degreee k and rewiring probability p

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MCBB.roessler_networkFunction
roessler_network(du, u, p::roessler_parameters, t)

N Roessler Parameters coupled on their x-component

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