For second order linear systems $\bold x'=A\bold x$ with $\det(\bold A-r\bold I)=0$ and $\det \bold A \ne 0$ trajectories follow particular stability patterns and types.
For higher order the cases are essentially combinations of these patterns
For Linear Systems we described the stability properties for the equilibrium solution $\bold x=\bold 0$
For the system $\bold x'=A\bold x$ in which $\det A\ne0$$~~~\bold x=\bold 0$ is the only critical point of the system by definition of invertibility (Linear Algebra Review)
<aside> ▫️ For the critical point $\bold x=0$ of $\bold x' =A\bold x$ where $A$ is $2\times 2$
</aside>
| Description | Eigenvalues | Type of Critical Point | Stability | Notes |
|---|---|---|---|---|
| Distinct, real, positive | $r_1>r_2>0$ | Node | Unstable (source) | |
| Distinct, real, negative | $r_1<r_2<0$ | Node | Asymptotically Stable (sink) | |
| Oppositely Signed, real | $r_2<0<r_1$ | Saddle Point | Unstable | |
| Repeated, positive | $r_1=r_2>0$ | Proper or Improper Node | Unstable | |
| Repeated, negative | $r_1=r_2<0$ | Proper or Improper Node | Asymptotically Stable | |
| Complex conjugates | $r_1,r_2=\lambda\pm i\mu\\~~~\lambda>0\\ |
Unstable
Asymptotically Stable | |
| Imaginary | $r_1,r_2=\pm i \mu$ | Center | Stable | To determine direction plot $A\begin{bmatrix}x_0\\y_o\end{bmatrix}$ |
> Def: When a repeated eigenvalue only gives a single independent eigenvector, the ciritcal point is **improper**
>
## Distinct Real:

## Saddle Point (Opposite Signs):

## Repeated Roots:
### Proper Nodes:

### Improper Nodes:


For improper nodes we find the independent eigenvalue solving $(A-\lambda I)\xi=0$ and the generalized vector $\eta$ that satisfies $(A-\lambda I)\eta=\xi$.
The general solution for improper nodes is:
$$
\bold x=(c_1\xi+c_2\eta+c_2\xi t)e^{rt}
$$
The direction is determined completely by $c_1\xi+c_2\eta+c_2\xi t$ and $e^{rt}$ only effects the magnitude.