Consider the linear homogeneous system

In order to find the eigenvalues consider the Characteristic polynomial

In this section, we consider the case when the above quadratic equation has double real root (that is if ) the double root (eigenvalue) is

In this case, we know that the differential system has the straight-line solution

where is an eigenvector associated to the eigenvalue . We also know that the general solution (which describes all the solutions) of the system will be

where is another solution of the system which is linearly
independent from the straight-line solution . Therefore, the problem in this case is to find .

**Search for a second solution.**

Let us use the vector notation. The system will be written as

where *A* is the matrix coefficient of the system. Write

The idea behind finding a second solution , linearly independent from , is to look for it as

where is some vector yet to be found. Since

and

(where we used ), then (because is a solution of the system) we must have

Simplifying, we obtain

or

This equation will help us find the vector . Note that the
vector will automatically be linearly independent from (why?).
This will help establish the linear independence of from
.

**Example.** Find two linearly independent solutions to the linear
system

**Answer.** The matrix coefficient of the system is

In order to find the eigenvalues consider the Characteristic polynomial

Since , we have a repeated eigenvalue equal to 2. Let us find the associated eigenvector . Set

Then we must have which translates into

This reduces to *y*=0. Hence we may take

Next we look for the second vector . The equation giving this vector is which translates into the algebraic system

where

Clearly we have *y*=1 and *x* may be chosen to be any number. So we
take *x*=0 for example to get

Therefore the two independent solutions are

The general solution will then be

**Qualitative Analysis of Systems with Repeated Eigenvalues**

Recall that the general solution in this case has the form

where is the double eigenvalue and is the associated eigenvector. Let us focus on the behavior of the solutions when (meaning the future). We have two cases

- If , then clearly we have
In this case, the equilibrium point (0,0) is a sink. On the other hand, when

*t*is large, we haveSo the solutions tend to the equilibrium point tangent to the straight-line solution. Note that is , then the solution is the straight-line solution which still tends to the equilibrium point.

- If , then
*Y*(*t*) tends to infinity as , except of course the constant solution. Note again that if , then we are moving along the straight-line solution.

Another example of the repeated eigenvalue's case is given by harmonic oscillators.

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