Every case
Distinct, repeated and complex eigenvalues, including defective matrices.
Enter the four entries of a 2x2 matrix to get its eigenvalues and eigenvectors, with every step of the working and a plot that shows how the matrix stretches the plane.
| Eigenvalue | Eigenvector | Unit eigenvector | Check A·v = λ·v |
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Plot: grey is the unit circle, purple is its image under A, and the coloured lines are the real eigenvector directions, which A only stretches or flips.
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Distinct, repeated and complex eigenvalues, including defective matrices.
Characteristic equation, discriminant and eigenvector steps.
A plot shows how the matrix stretches the unit circle.
For A = [[a, b], [c, d]], the eigenvalues solve det(A − λI) = 0, which for a 2x2 matrix is the quadratic λ² − (a + d)λ + (ad − bc) = 0. The trace a + d equals the sum of the eigenvalues and the determinant ad − bc equals their product.
The discriminant Δ = (a + d)² − 4(ad − bc) decides the case. If Δ > 0 there are two real eigenvalues, if Δ = 0 there is one repeated eigenvalue, and if Δ < 0 the eigenvalues are complex conjugates, which happens for rotations. Each eigenvector is any non-zero vector perpendicular to a non-zero row of A − λI.
Always have real eigenvalues and perpendicular eigenvectors.
Have complex eigenvalues because no direction stays fixed.
A repeated eigenvalue with only one eigenvector, like a shear.
The two eigenvalues must add up to the trace a + d and multiply to the determinant ad − bc.
Any non-zero multiple of an eigenvector is also an eigenvector. The calculator shows a simple version and the unit-length version.
The matrix rotates every direction, so no real vector keeps its direction. The real part controls growth or decay and the imaginary part the rotation speed.
One with a repeated eigenvalue but only one independent eigenvector, such as [[3, 1], [0, 3]]. It cannot be diagonalised.
For the system of differential equations x' = Ax, the eigenvalues decide whether the origin is a node, saddle, spiral or centre and whether it is stable.
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