1. Introduction
There exist two kinds of “catastrophe”. One is a statical model. Corresponding multi variable scalar functions are classified from the Hessian matrix on non-degenerate critical points. See [1] [2] [3] and [4] . The other one is a dynamical model. It is induced from the slow-fast system with parameters, which has the singular limit orbit. The aim of this paper is to describe the relation between “statical model” and “dynamical model”. It becomes clear that the 4-dimensional slow-fast system with co-dimension 2 gives us a new structure. In section 2, we give standard assumptions as a preliminary, and “remark 4” and “remark 5” are important to realize the framework. Inserting a bifurcation parameter “b” newly, see [5] , it causes to explore for the potential. In section 3, the slow-fast system having bifurcation parameters for all slow/fast vectors will be described. Then, it will be shown how to construct another potential via projection changing the coordinates R4 to R2. In section 4, a neuron system [6] will be given as a concrete system.
2. Preliminary
Now, let us consider the following slow-fast system:
(1)
where
is infinitesimal, and
Then, assume that the origin is a singular point.
Furthermore, we assume that the system (1) satisfies the following conditions (A1) - (A6), they are the same as describing our previous paper.
(A1) h is of class
and g is of class
.
(A2) The slow manifold
is a two-dimensional differential manifold and intersects the set
(2)
transversely, where
(3)
Then, the pli set
(4)
is a one-dimensional differentiable manifold.
(A3) Either the value of
or that of
is nonzero at any point of PL.
Note that the pli set PL divides the slow manifolds S\PL into three parts
depending on the signs of the two eigenvalues of
.
First, consider the following reduced system which is obtained from (1) with
:
(5)
By differentiating
with respect to t, we have
(6)
Then (4) becomes the following:
(7)
where
. To avoid degeneracy in (6), we consider the time-scaled-reduced system:
(8)
The phase portrait of the system (8) is the same as that of (7) except the region
where
, but only the orientation of the orbit is different.
Definition 1 A singular point of (8), which is on PL, is called a pseudo singular point of (1). The set of pseudo singular points is denoted by PS.
(A4)
,
for any
.
From (A4), the implicit function theorem guarantees the existence of a unique function
such that
. By using
, we obtain the following system:
(9)
(A5) All singular points of (8) are non-degenerate, that is, the linearization of (8) at a singular point has two nonzero eigenvalues.
Now, let us introduce a definition of “symmetry”. It is a key word through this paper.
Definition 2 If
, and
, then the system is “symmetric” for the subspace
.
(A6) I intersects PL transversely.
Definition 3 Let
be two eigenvalues of the linearization of (8) at a pseudo singular point. The pseudo singular point with real eigenvalues is called a pseudo singular saddle point if
and a pseudo singular node point if
or
.
The following Theorems 1 is established in [7] , [8] and [9] respectively.
Theorem 1 Let
be a pseudo singular saddle or node point. If
, then there exists a solution which first follows the
attractive part and the repulsive part after crossing PL near the pseudo singular point.
Remark 1 The solution in Theorem 1 is called “canard”.
Remark 2 The condition
implies that one of eigenvalues of
is equal to zero and the other one is negative. Notice
that the system has two kinds of vector fields: one is 2-dimensional slow and the other is 2-dimensional fast one. The condition provides the state of the fast vector field.
Remark 3 The singular solution in Theorem 1 is called a canard in R4 with 2-dimensional slow manifold. As a result, it causes a delayed jumping. The study of canards requires still more precise topological analysis on the slow vector field.
Remark 4 On the subspace I, the following system is established for some b. I is an invariant manifold.
(10)
Remark 5 On the set PL,
is satisfied and at
the
following equation is established:
(11)
Note that there exists
because of assuming
.
3. Bifurcation on Slow/Fast Vectors
From now on, let us consider the following system extended having parameters for slow/fast vectors:
(12)
where
,
,
and
.
On the other hand,
(13)
In fact,
(14)
Lemma 1
(15)
It does not depend on bifurcation parameter
.
Theorem 2 If the system having parameters for slow/fast vectors is “symmetric”, then it has a potential classified by R. Thom.
Proof. Under the rank condition (A4), proceeding a projection (changing the co-ordinates):
(16)
like as
, then, the potentials are obtained as “elementary catastrophe” under the following conditions.
At around
,
(i)
.
(ii)
.
(iii)
and
.
(iv)
.
(v)
and
.
(vi)
.
(vii)
.
Remark 6 As the system is “symmetric”, the conditions are described exclusively, for example, the condition (1) is as the following,
Remark 7 It is called “Hyper Catastrophe”, which is composed of the potential reduced from the slow manifold (
). Although it is using non-standard analysis, for example
is infinitesimal, “Transfer Principle” ensures that it is established in standard analysis. Then, the slow manifold is obtained as the singular limit (
tends to zero). They are “dynamical catastrophe” but not “statical one”. See [10] [11] .
4. Concrete Example
Consider the equation,
(17)
where
are bifurcation parameters.
Changing the coordinates like as
(18)
then on the axis X, getting the function
(19)
This potential function is “hyperbolic umbilic” classified by R. Thom.
Using variables
, when satisfying
,
(20)
Corollary 1 If
or
takes nearly equal 0, there exists “hyperbolic
umbilic”. Changing the coordinates, it is “fold” catastrophe.
Remark 8 In the concrete example, the values corresponding partial derivatives are at around the origin. For the simplicity, it is not at the pseudo singular point.
5. Conclusion
In general, the advanced system having parameters for slow/fast vectors looks like very complicated aspects geometrically. It is sure on 4-dimensional, however, changing coordinates makes their appearance. Note that “changing coordinates” implies proceeding “projection” to the lower dimension. Remember that the original constrained surface is 2-dimensional manifold in R4. It is “dynamical” catastrophe but not “statical” one. In the beginning of “bifurcation problem”, many people used the word “structural stability” for the original differential equations. Under being the stability, the statical model is applied. In this paper, it is used for the bifurcation parameter on the pseudo-singular point. It might be needed to emphasize again in order to avoid giving somehow confusions. In practice, recently, people need a new tool to analyze economics and to do brain mechanism. Dynamical catastrophe describes fundamental structure through these potentials.
Acknowledgements
The second author is supported in part by Grant-in-Aid Scientific Research (C), No.18K03431, Ministry of Education, Science and Culture, Japan.