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Diagonalize [4, -1; 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 = [4, −1; 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 = [4 − λ, −1; 2, 1 − λ]

Its determinant, down minus up, must be 0.

So (4 − λ)(1 − λ) − 2 × (−1) = 0.

(4 − λ)(1 − λ) − 2 × (−1) = 0

Multiply out the brackets, and 2 × (−1) = −2.

4 − 4λ − λ + λ2 + 2 = 0

Like terms together, the highest power first: λ² − 5λ + 6 = 0.

λ2 − 5λ + 6 = 0

It factors, as in the factoring lesson.

(λ − 2)(λ − 3) = 0

So λ = 2 or λ = 3.

λ = 2 or λ = 3

2 Eigenvector for λ = 2

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

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

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

That is why there are eigenvectors.

Row 1 as an equation: x − y/2 = 0.

x − y2 = 0

We want x alone.

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

x − y2 + y2 = y2

They cancel on the left.

So x = y/2.

x = y2

We pick y = 2 to keep whole numbers.

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

v = [1; 2]

3 Eigenvector for λ = 3

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

A − 3I = [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 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 = 3 is (1, 1).

v = [1; 1]

4 Build P and D

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

D: 2 first, then 3, in the same order.

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

Now P times D.

P D = [1, 1; 2, 1] × [2, 0; 0, 3]
P D = [1 × 2 + 1 × 0, 1 × 0 + 1 × 3; 2 × 2 + 1 × 0, 2 × 0 + 1 × 3]
P D = [2, 3; 4, 3]

Both give rows 2, 3 and 4, 3.

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

Let's look back.

First: find the eigenvalues.

Then: eigenvector for λ = 2.

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 [6, −1; 4, 1]
Show the answer
P = [1, 1; 4, 1], D = [2, 0; 0, 5]

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