Detection of bifurcation points of Equilibria
The bifurcations are detected during a call to br = continuation(prob, alg, contParams::ContinuationPar;kwargs...)
by turning on the following flags:
contParams.detect_bifurcation = 2
The bifurcation points are located by looking at the spectrum e.g. by monitoring the unstable eigenvalues. The eigenvalue λ is declared unstable if real(λ) > contParams.tol_stability
. The located bifurcation points are then returned in br.specialpoint
.
The rightmost eigenvalues are computed by default to detect bifurcations. Hence, the number of eigenvalues with positive real parts must be finite (e.g. small). This might require to consider $-F(x,p)=0$ instead of (E).
Precise detection of bifurcation points using Bisection
Note that the bifurcation points detected when detect_bifurcation = 2
can be rather crude localization of the true bifurcation points. Indeed, we only signal that, in between two continuation steps which can be large, a (several) bifurcation has been detected. Hence, we only have a rough idea of where the bifurcation is located, unless your dsmax
is very small... This can be improved as follows.
If you choose detect_bifurcation = 3
, a bisection algorithm is used to locate the bifurcation points more precisely. It means that we recursively track down the change in stability. Some options in ContinuationPar
control this behavior:
n_inversion
: number of sign inversions in the bisection algorithmmax_bisection_steps
maximum number of bisection stepstol_bisection_eigenvalue
tolerance on real part of eigenvalue to detect bifurcation points in the bisection steps
If this is still not enough, you can use a Newton solver to locate them very precisely. See Fold / Hopf Continuation.
During the bisection, the eigensolvers are called like eil(J, nev; bisection = true)
in order to be able to adapt the solver precision.
Large scale computations
The user must specify the number of eigenvalues to be computed (like nev = 10
) in the parameters ::ContinuationPar
passed to continuation
. Note that nev
is automatically incremented whenever a bifurcation point is detected [1]. Also, there is an option in ::ContinuationPar
to save (or not) the eigenvectors. This can be useful in memory limited environments (like on GPUs).
List of detected bifurcation points
Bifurcation | index used |
---|---|
Fold | fold |
Hopf | hopf |
Bifurcation point (single eigenvalue stability change, Fold or branch point) | bp |
Not documented | nd |
Eigensolver
The user must provide an eigensolver by setting NewtonOptions.eigsolver
where newton_options
is located in the parameter ::ContinuationPar
passed to continuation. See NewtonPar
and ContinuationPar
for more information on the composite type of the options passed to newton
and continuation
.
The eigensolver is highly problem dependent and this is why the user should implement / parametrize its own eigensolver through the abstract type AbstractEigenSolver
or select one among List of implemented eigen solvers.
Generic bifurcation
By this we mean a change in the dimension of the Jacobian kernel. The detection of Branch point is done by analysis of the spectrum of the Jacobian.
The detection is triggered by setting detect_bifurcation > 1
in the parameter ::ContinuationPar
passed to continuation
.
Fold bifurcation
The detection of Fold point is done by monitoring the monotonicity of the parameter.
The detection is triggered by setting detect_fold = true
in the parameter ::ContinuationPar
passed to continuation
. When a Fold is detected on a branch br
, a point is added to br.foldpoint
allowing for later refinement using the function newton_fold
.
Hopf bifurcation
The detection of Hopf point is done by analysis of the spectrum of the Jacobian.
The detection is triggered by setting detect_bifurcation > 1
in the parameter ::ContinuationPar
passed to continuation
. When a Hopf point is detected, a point is added to br.specialpoint
allowing for later refinement using the function newton_hopf
.
- 1In this case, the Krylov dimension is not increased because the eigensolver could be a direct solver. You might want to increase this dimension using the callbacks in
continuation
.