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Diagonalize [-2, 1; 1, -2]

Step by step, with the reason for every step · Diagonalizing a matrix · Linear Algebra

Step by step

The question

Question: diagonalize A.

A = [−2, 1; 1, −2]

Diagonalizing means writing A as P times D times P inverse.

The columns of P are eigenvectors.

D is diagonal: the eigenvalues down the diagonal, 0s elsewhere.

A = P D P−1
P: eigenvectors as columns
D: their λs down the diagonal

1 Find the eigenvalues

As in the eigenvalue lesson: take λ off the diagonal of A.

A − λI = [−2 − λ, 1; 1, −2 − λ]

Its determinant, down minus up, must be 0.

So (−2 − λ)(−2 − λ) − 1 × 1 = 0.

(−2 − λ)(−2 − λ) − 1 × 1 = 0

Multiply out the brackets, and 1 × 1 = 1.

4 + 2λ + 2λ + λ2 − 1 = 0

Like terms together, the highest power first: λ² + 4λ + 3 = 0.

λ2 + 4λ + 3 = 0

It factors, as in the factoring lesson.

(λ + 3)(λ + 1) = 0

So λ = −3 or λ = −1.

λ = −3 or λ = −1

2 Eigenvector for λ = −3

We take −3 off the diagonal: −2 − (−3) = 1 and −2 − (−3) = 1.

A − (−3)I = [1, 1; 1, 1]
→ [1, 1; 0, 0]

A row of 0s: the letter y is free.

That is why there are eigenvectors.

Row 1 as an equation: x + y = 0.

x + y = 0

We want x alone.

To remove + y, we take away y on both sides.

x + y − y = −y

They cancel on the left.

So x = −y.

x = −y

We pick y = 1.

So an eigenvector for λ = −3 is (−1, 1).

v = [−1; 1]

3 Eigenvector for λ = −1

We take −1 off the diagonal: −2 − (−1) = −1 and −2 − (−1) = −1.

A − (−1)I = [−1, 1; 1, −1]
→ [1, −1; −1, 1]
→ [1, −1; 0, 0]

A row of 0s: the letter y is free.

That is why there are eigenvectors.

Row 1 as an equation: x − y = 0.

x − y = 0

We want x alone.

To remove − y, we add y on both sides.

x − y + y = y

They cancel on the left.

So x = y.

x = y

We pick y = 1.

So an eigenvector for λ = −1 is (1, 1).

v = [1; 1]

4 Build P and D

P: the eigenvector for λ = −3 is column 1, the one for λ = −1 is column 2.

D: −3 first, then −1, in the same order.

P = [−1, 1; 1, 1], D = [−3, 0; 0, −1]

Careful!

The order matters.

The first λ in D goes with the first column of P.

Careful: D in the same order as the columns of P

So A = P D P⁻¹, with this P and D.

A = P D P−1

5 Check

Let's check without the inverse: A = P D P⁻¹ means A P = P D.

We work out both sides.

First A times P.

A P = [−2, 1; 1, −2] × [−1, 1; 1, 1]
A P = [−2 × (−1) + 1 × 1, −2 × 1 + 1 × 1; 1 × (−1) + (−2) × 1, 1 × 1 + (−2) × 1]
A P = [3, −1; −3, −1]

Now P times D.

P D = [−1, 1; 1, 1] × [−3, 0; 0, −1]
P D = [−1 × (−3) + 1 × 0, −1 × 0 + 1 × (−1); 1 × (−3) + 1 × 0, 1 × 0 + 1 × (−1)]
P D = [3, −1; −3, −1]

Both give rows 3, −1 and −3, −1.

So A P = P D, and the answer is right!

Let's look back.

First: find the eigenvalues.

Then: eigenvector for λ = −3.

Then: eigenvector for λ = −1.

Then: build P and D.

Last: check.

Answer
A = P D P−1

Your turn

Try this one yourself, then check:

Diagonalize [−4, 2; 1, −3]
Show the answer
P = [−2, 1; 1, 1], D = [−5, 0; 0, −2]

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