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Diagonalize [1, 4; 2, -1]

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

Step by step

The question

Question: diagonalize A.

A = [1, 4; 2, −1]

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 = [1 − λ, 4; 2, −1 − λ]

Its determinant, down minus up, must be 0.

So (1 − λ)(−1 − λ) − 2 × 4 = 0.

(1 − λ)(−1 − λ) − 2 × 4 = 0

Multiply out the brackets, and 2 × 4 = 8.

−1 − λ + λ + λ2 − 8 = 0

Like terms together, the highest power first: λ² − 9 = 0.

λ2 − 9 = 0

It factors, as in the factoring lesson.

(λ + 3)(λ − 3) = 0

So λ = −3 or λ = 3.

λ = −3 or λ = 3

2 Eigenvector for λ = −3

We take −3 off the diagonal: 1 − (−3) = 4 and −1 − (−3) = 2.

A − (−3)I = [4, 4; 2, 2]
→ [1, 1; 2, 2]
→ [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 = 3

We take 3 off the diagonal: 1 − 3 = −2 and −1 − 3 = −4.

A − 3I = [−2, 4; 2, −4]
→ [1, −2; 2, −4]
→ [1, −2; 0, 0]

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

That is why there are eigenvectors.

Row 1 as an equation: x − 2y = 0.

x − 2y = 0

We want x alone.

To remove − 2y, we add 2y on both sides.

x − 2y + 2y = 2y

They cancel on the left.

So x = 2y.

x = 2y

We pick y = 1.

So an eigenvector for λ = 3 is (2, 1).

v = [2; 1]

4 Build P and D

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

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

P = [−1, 2; 1, 1], D = [−3, 0; 0, 3]

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 = [1, 4; 2, −1] × [−1, 2; 1, 1]
A P = [1 × (−1) + 4 × 1, 1 × 2 + 4 × 1; 2 × (−1) + (−1) × 1, 2 × 2 + (−1) × 1]
A P = [3, 6; −3, 3]

Now P times D.

P D = [−1, 2; 1, 1] × [−3, 0; 0, 3]
P D = [−1 × (−3) + 2 × 0, −1 × 0 + 2 × 3; 1 × (−3) + 1 × 0, 1 × 0 + 1 × 3]
P D = [3, 6; −3, 3]

Both give rows 3, 6 and −3, 3.

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 = 3.

Then: build P and D.

Last: check.

Answer
A = P D P−1

Your turn

Try this one yourself, then check:

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

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