Stability of Differential System When Eigenvalue is Zero – Differential Equations

dynamical systemseigenvalues-eigenvectorsordinary differential equationsstability-in-odesstability-theory

I'm trying to figure out the stability of the origin $O(0,0)$ for the following system of differential equations :
$$x'= -x^2 + 2xy$$
$$y'=-2y+y^2+xy$$
using the following method/theorem/lemma which I found in my notes (it's the only thing that is mentioned about systems which yield an eigenvalue equal to zero) :

Zero Eigenvalue : Stability

Let $f=(f_1,f_2) : \mathbb R^2 \to \mathbb R^2$, where $f\in C^k(\mathbb R^2), k\geq 1, f(0) = 0, Df(0)=0$.

Consider the following system :
$$x'=f_1(x,y)$$
$$y' = -y + f_2(x,y)$$

which can be translated to :

$$\begin{bmatrix} x \\ y \end{bmatrix}'= \begin{bmatrix} 0 & 0 \\ 0 & -1 \end{bmatrix}\begin{bmatrix} x \\ y \end{bmatrix} + f(x,y)$$

Observe that the linearized system has an eigenvalue equal to zero and that the critical point $O(0,0)$ is non-hyperbolic.

Solving the system of equations :
$$\begin{cases} -y(x) + f_2(x,y(x)) = 0 \\ y(0) = y'(0) = 0 \end{cases}$$

the function $y(x)$ can be expressed in terms of $x$.

Finally :
$$f_1(x,y(x))=ax^k+O(|x|^{k+1})$$
which leads to the origin $O(0,0)$ being asymptotically stable if $a<0$ and $k$ odd, else it's unstable.

Attempt/Discussion :

I'll let :

$$f_1(x,y) = -x^2 + 2xy$$
$$f_2(x,y) = y^2 + xy$$

since having $-2$ instead of $-1$ at my system's matrix will not change anything (just a multiplication constant).

Then, it's indeed easy to see that the matrix of the linearized system at the origin describes a non-hyperbolic critical point, as :

$$\det(J(0,0)) = 0$$

and that we have a zero eigenvalue, since $\det(J(0,0)-λI)=0$ yields a solution $λ=0$ (where $J(0,0)$ is the Jacobian at $(0,0)$).

Solving now :

$$-2y(x) + f_2(x,y(x)) = 0 \Rightarrow -2y(x) + y^2(x) + xy(x) = 0 \Rightarrow y^2(x) + (x-2)y(x) = 0 \Rightarrow y(x)[y(x) + x-2] = 0$$

which means that $y(x)=0$ or that $y(x) = 2-x$.

Now, I guess I'll have to check both cases, which means that at first :

$$f_1(x,y(x)=0) = -x^2$$

which, according to the theorem, yields that the origin $O(0,0)$ is unstable.

Checking for the other case :

$$f_1(x,y(x)=2-x)=-(2-x)^2 + 2x(2-x)=-4 + 4x – x^2 + 4x – 2x^2$$
$$=$$
$$-3x^2 + 8x – 4$$

Now, again, the power of $x$ is not odd so it means automatically that the origin is unstable ? Questioning this though, since the form is not the one reported by the theorem. What does the notation $O(|x|^{k+1})$ specifically refers too in such example ?

Also, wanted to ask, is my approach correct ? It seems that this is the only theorem-method we have been taught/expected to study for systems with an eigenvalue being zero, but I found a hard time applying it to more complicated systems (let's say with constants and higher powers).

Best Answer

WolframAlpha with the stream plot command produces the following phase portraît

enter image description here

At $(0,0)$ you found that $y$ is smaller than any power of $x$, the local approximation is given by $\dot x=-x^2$ so that $$x(t)=\frac{x_0}{1+x_0t}$$ and then (again disregarding higher order terms in $y$) $\dot y/y=-2+x$ so that $\ln(y/y_0)=-2t+\ln(1+x_0t)$ or $$ y(t)=y_0e^{-2t}(1+x_0t). $$ This contrast of exponential reduction in $y$ against hyperbolic reduction in $x$ for $x_0>0$ resp. hyperbolic divergence for $x_0<0$ can be seen in the magnification below.

enter image description here

For the stationary point $(0,2)$ one can write the system as \begin{alignat}{2} \dot x &=4x&&-x^2+2x(y-2)\\ \dot y &=2x+2(y-2)&&+(y-2)^2+2x(y-2) \end{alignat} which clearly is in the first order approximation an unstable point, as can also be seen in the magnification.

enter image description here