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College prep🔤Algebra●●●●○· 7 min

Diagonalize a 2×2 matrix in 60 seconds

Trace, determinant, discriminant. Three calculations and boom, your eigenvalues. Then eigenvectors in three lines each.

The method in 4 steps

Let A=(abcd)A = \begin{pmatrix} a & b \\ c & d \end{pmatrix}.

Step 1 — Eigenvalues. Solutions of λ2tλ+det=0\lambda^2 - t\lambda + \det = 0 where:

  • t=tr(A)=a+dt = \text{tr}(A) = a + d (trace)
  • det=adbc\det = ad - bc (determinant)

Step 2 — Diagonalizability test. If Δ=t24det>0\Delta = t^2 - 4\det > 0 (two distinct eigenvalues), then AA is diagonalizable over R\mathbb{R}.

Step 3 — Eigenvectors. For each λ\lambda, solve (AλI)v=0(A - \lambda I) v = 0.

Step 4 — Diagonal form. A=PDP1A = P D P^{-1} with D=(λ100λ2)D = \begin{pmatrix} \lambda_1 & 0 \\ 0 & \lambda_2 \end{pmatrix} and PP having the eigenvectors as columns.

Complete example: A=(3102)A = \begin{pmatrix} 3 & 1 \\ 0 & 2 \end{pmatrix}

  • Trace: t=5t = 5. Det: det=6\det = 6.
  • Characteristic polynomial: λ25λ+6=0\lambda^2 - 5\lambda + 6 = 0λ1=2,λ2=3\lambda_1 = 2, \lambda_2 = 3.
  • Eigenvector for λ1=2\lambda_1 = 2: solve (1100)v=0\begin{pmatrix} 1 & 1 \\ 0 & 0 \end{pmatrix} v = 0v1=(11)v_1 = \begin{pmatrix} 1 \\ -1 \end{pmatrix}.
  • Eigenvector for λ2=3\lambda_2 = 3: solve (0101)v=0\begin{pmatrix} 0 & 1 \\ 0 & -1 \end{pmatrix} v = 0v2=(10)v_2 = \begin{pmatrix} 1 \\ 0 \end{pmatrix}.
  • D=(2003)D = \begin{pmatrix} 2 & 0 \\ 0 & 3 \end{pmatrix}, P=(1110)P = \begin{pmatrix} 1 & 1 \\ -1 & 0 \end{pmatrix}.

Case Δ=0\Delta = 0: watch out

Single double eigenvalue. Matrix is diagonalizable iff the eigenspace has dimension 2. Otherwise, only triangularizable.

Case Δ<0\Delta < 0

No real eigenvalues → not diagonalizable over R\mathbb{R}, but is over C\mathbb{C}.

?Your turn

Eigenvalues of A = ((4, 1), (2, 3)) are:

#diagonalization#matrix#eigenvalue#linear algebra#prep

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