Linear Systems via Eigenvectors
Ch 7 — Part I — Explicit & Qualitative Methods
A homogeneous linear system \(\mathbf{x}' = A\mathbf{x}\) (with \(A\) an \(n\times n\) constant matrix) has solutions constructed from eigenvalues and eigenvectors of \(A\).
Building solutions from eigenpairs
If \(A\mathbf{v} = \lambda \mathbf{v}\), then \(\mathbf{x}(t) = e^{\lambda t}\mathbf{v}\) solves \(\mathbf{x}' = A\mathbf{x}\). If \(A\) has \(n\) linearly independent eigenvectors \(\mathbf{v}_1, \ldots, \mathbf{v}_n\) with eigenvalues \(\lambda_1, \ldots, \lambda_n\), the general solution is $$\mathbf{x}(t) = c_1 e^{\lambda_1 t}\mathbf{v}_1 + \cdots + c_n e^{\lambda_n t}\mathbf{v}_n.$$
Finding eigenpairs
Solve \(\det(A - \lambda I) = 0\) for \(\lambda\) (characteristic equation of the matrix), then solve \((A - \lambda I)\mathbf{v} = 0\) for a nonzero \(\mathbf{v}\).
Complex eigenvalues
If \(\lambda = r + is\) has eigenvector \(\mathbf{v}\), the real-valued general solution is $$c_1 \operatorname{Re}(e^{\lambda t}\mathbf{v}) + c_2 \operatorname{Im}(e^{\lambda t}\mathbf{v}).$$
Companion system
Any higher-order linear ODE or system of ODEs can be rewritten as a first-order system \(\mathbf{x}' = A\mathbf{x} + \mathbf{f}(t)\); introduce variables for each derivative.
Practice Problems
Hint
Solution
Roots \(\lambda = 3, -1\). For \(\lambda = 3\): \((A-3I)\mathbf{v}=0\) gives \(\mathbf{v} = (1,1)^T\). For \(\lambda = -1\): \(\mathbf{v} = (1,-1)^T\).
Answer: \(\mathbf{x}(t) = c_1 e^{3t}\binom{1}{1} + c_2 e^{-t}\binom{1}{-1}.\)
Hint
Solution
Take the eigenpair \(\lambda = i,\; \mathbf{v} = \binom{1}{-i}\). Then \(e^{it}\mathbf{v} = \binom{\cos t + i\sin t}{\sin t - i\cos t}\). Its real and imaginary parts give two real solutions: \(\binom{\cos t}{\sin t}\) and \(\binom{\sin t}{-\cos t}\). So \(\mathbf{x}(t) = c_1\binom{\cos t}{\sin t} + c_2\binom{\sin t}{-\cos t}\). The IC \((1,0)\) gives \(c_1 = 1,\; c_2 = 0\).
Answer: \(\mathbf{x}(t) = \binom{\cos t}{\sin t}.\)
Hint
Solution
Then \(x_1' = x_2\) and \(x_2' = -2x_1 - 3x_2\). So \(A = \begin{pmatrix}0 & 1 \\ -2 & -3\end{pmatrix}\).
Answer: See solution.