Module 1 of 1 · Lesson 12 of 14

Complex Numbers

The field where every polynomial splits, and the pairing that governs a real matrix spectrum.

What you will be able to do

Given complex numbers in rectangular or polar form, the learner can add, multiply and divide them, take conjugates and moduli, convert between forms, apply De Moivre's theorem to powers and roots, and explain why the non-real eigenvalues of a real matrix arrive in conjugate pairs.

Orientation

The eigenvalue unit reported that a quarter-turn rotation has eigenvalues ± i , and that a real matrix's non-real eigenvalues arrive in conjugate pairs. Both claims were used before the numbers involved had been defined.

This unit supplies them. Adjoining a single solution of x 2 = − 1 produces a field in which every polynomial factors completely, so a characteristic polynomial always splits, and an n × n matrix always has n eigenvalues counted with multiplicity. Nothing further ever needs adding.

The arithmetic is ordinary once i 2 = − 1 is applied. What repays attention is the second description: a complex number as a point in the plane, with multiplication rotating and scaling. In that reading ± i as the eigenvalues of a rotation stops being a curiosity and becomes a statement of what the matrix does.

Simulation

Multiplication by a unit complex number as rotation

Modulus is distance, argument is angle, multiplication is rotation

z = 3 + 2 i as a point of the plane: its distance from the origin is the modulus 13 , its angle from the real axis the argument.

Turn the control and watch what multiplying by e i φ does: the point travels along the circle, because rotation changes the argument and leaves the modulus alone. Multiplying by a positive real would do the opposite, moving along the ray and fixing the angle. A general product does both, which is exactly why moduli multiply and arguments add.

What the control establishes is the three-line reading the rest of the unit rests on: modulus is distance, argument is angle, and multiplication scales by the one and turns by the other.

Definition

What the parts are, and why division works

The imaginary part is real. For z = 3 + 4 i , Im ⁡ z = 4 , not 4 i . Both Re ⁡ z and Im ⁡ z are real numbers. They are the coordinates of the point z in the plane, and a coordinate is a number rather than a vector. Reporting 4 i makes Im a map from C to C instead of to R , and the type error propagates into every identity built on it.

Why z z ¯ is the key to division. C has no order, so there is no "dividing by the larger part". What makes division possible is that

z z ¯ = ( a + b i ) ( a − b i ) = a 2 − ( b i ) 2 = a 2 + b 2

is always a nonnegative real. Multiplying a quotient above and below by w ¯ therefore converts the denominator into a real number, after which dividing is ordinary:

z w = z w ¯ w w ¯ = z w ¯ | w | 2 .

This is the same manoeuvre as rationalising 1 1 + 2 , and the conjugate plays the same role.

Conjugation is a field homomorphism. z + w ― = z ¯ + w ¯ and z w ― = z ¯ w ¯ . It respects both operations, and it fixes exactly the real numbers. That combination is what forces conjugate pairing later: a polynomial with real coefficients is unchanged by conjugating its coefficients, so conjugating a root produces another root.

Geometrically it is reflection across the real axis, which is why | z ¯ | = | z | and arg ⁡ z ¯ = − arg ⁡ z .

No order. z < w is undefined for non-real numbers. Any ordering compatible with the arithmetic would have to place i on one side of 0, and squaring gives a contradiction either way. Only moduli, which are real, can be compared, so "larger complex number" is never a well-formed phrase.

The argument is not unique. arg ⁡ z is determined only up to multiples of 2 π , so 1 + i has argument π / 4 , 9 π / 4 , − 7 π / 4 and so on. Conventions fix a principal value in ( − π , π ] , and computing n th roots requires deliberately using several representatives, which is why the roots come out distinct.

Procedure

Computing in both forms

Multiply by expanding and replacing i 2 with − 1 :

( a + b i ) ( c + d i ) = a c + a d i + b c i + b d i 2 = ( a c − b d ) + ( a d + b c ) i .

Collect the real terms and the i terms separately. The sign flip on b d is the only place i 2 enters, and missing it is the commonest slip.

Divide by multiplying above and below by the conjugate of the denominator, then dividing each part by the resulting real number:

z w = z w ¯ | w | 2 .

Convert to polar. r = a 2 + b 2 , and θ from tan ⁡ θ = b / a adjusted for the quadrant. A calculator's arctan returns values in ( − π / 2 , π / 2 ) , so for a < 0 add or subtract π . Sketching the point first is the reliable guard.

Convert back. a = r cos ⁡ θ , b = r sin ⁡ θ .

Powers, by De Moivre. z n = r n e i n θ , raise the modulus, multiply the argument. For a large exponent this is far cheaper than repeated multiplication, and it is exact where repeated multiplication accumulates error.

Roots. The n distinct n th roots of r e i θ are

r 1 / n e i ( θ + 2 π k ) / n , k = 0 , 1 , … , n − 1 .

They sit at equal modulus and equal angular spacing 2 π / n . Taking only k = 0 finds one root and misses the rest, which is the standard omission.

Checks worth running.

CheckCatches
| z w | = | z | | w | an arithmetic slip in a product
z z ¯ = | z | 2 , real and nonnegativea sign error in a conjugate
a quotient re-multiplied by the divisora division error
n roots found, not onethe truncated root computation
the polar angle plotted against the point's quadrantthe arctan quadrant error

Worked example

Arithmetic, then the same numbers in polar form

Let z = 3 + 4 i and w = 1 − 2 i .

Product.

z w = ( 3 ) ( 1 ) − ( 4 ) ( − 2 ) + [ ( 3 ) ( − 2 ) + ( 4 ) ( 1 ) ] i = ( 3 + 8 ) + ( − 6 + 4 ) i = 11 − 2 i .

Expanding term by term: 3 − 6 i + 4 i − 8 i 2 = 3 − 2 i + 8 = 11 − 2 i , the + 8 coming from − 8 i 2 .

Check by modulus. | z | = 9 + 16 = 5 and | w | = 1 + 4 = 5 , so | z | | w | = 5 5 ≈ 11.180 . And | z w | = 121 + 4 = 125 = 5 5 .

Quotient. Multiply above and below by w ¯ = 1 + 2 i , noting | w | 2 = 5 :

z w = ( 3 + 4 i ) ( 1 + 2 i ) 5 = 3 + 6 i + 4 i + 8 i 2 5 = − 5 + 10 i 5 = − 1 + 2 i .

Check. ( − 1 + 2 i ) ( 1 − 2 i ) = − 1 + 2 i + 2 i − 4 i 2 = − 1 + 4 i + 4 = 3 + 4 i = z .

Conjugate and modulus. z ¯ = 3 − 4 i , and

z z ¯ = 9 − 12 i + 12 i − 16 i 2 = 9 + 16 = 25 = | z | 2

real and nonnegative, as it must be.

---

Polar form. Take u = 1 + i . Then r = 1 + 1 = 2 and, since u lies in the first quadrant, θ = π / 4 . So

u = 2 e i π / 4 .

Powers by De Moivre. u n = ( 2 ) n e i n π / 4 :

n modulusargumentvalue
2 2 π / 2 2 i
4 4 π − 4
8 16 2 π 16

Check u 2 directly. ( 1 + i ) 2 = 1 + 2 i + i 2 = 2 i . And u 8 = 16 , a positive real, which the polar form predicts without any multiplication, since eight quarter-turns return to the starting direction.

Cube roots of unity. Solving z 3 = 1 means r 3 = 1 and 3 θ = 2 π k , so r = 1 and θ = 0 , 2 π / 3 , 4 π / 3 :

1 , − 1 2 + 3 2 i , − 1 2 − 3 2 i .

Each cubes to 1, they are equally spaced around the unit circle, and they sum to 0. The two non-real ones are conjugates, and their real parts − 1 2 each cancel half of the first root's 1.

A real quadratic with complex roots. x 2 − 2 x + 5 = 0 has discriminant 4 − 20 = − 16 , so

x = 2 ± − 16 2 = 2 ± 4 i 2 = 1 ± 2 i .

The roots are conjugates, as real coefficients require. Checking against the coefficients: their sum is 2 = − b / a and their product is ( 1 + 2 i ) ( 1 − 2 i ) = 1 + 4 = 5 = c / a . Both real, which is the pairing making itself visible.

Theorem

Conjugate pairing, and why it governs real matrices

Theorem. Let p ( x ) = c n x n + ⋯ + c 1 x + c 0 have real coefficients. If p ( λ ) = 0 then p ( λ ¯ ) = 0 .

Proof. Conjugation respects sums and products, so

p ( λ ) ― = ∑ k c k λ k ― = ∑ k c k ― λ ― k = ∑ k c k λ ¯ k = p ( λ ¯ ) ,

where the third equality uses c k ― = c k . The hypothesis that the coefficients are real, and the only place it is used. Since p ( λ ) = 0 and 0 ¯ = 0 , we get p ( λ ¯ ) = 0 . ◼

Corollary (eigenvalues of a real matrix). The characteristic polynomial of a real matrix has real coefficients, so its non-real eigenvalues occur in conjugate pairs λ , λ ¯ , with equal algebraic multiplicities.

Corollary (eigenvectors too). If A v = λ v with A real, conjugating every entry gives A v ¯ = λ ¯ v ¯ , since A ¯ = A . So the conjugate eigenvector belongs to the conjugate eigenvalue, and the pair arrives as a package.

Corollary (odd dimension). A real n × n matrix with n odd has at least one real eigenvalue: the non-real ones pair off, leaving an odd count that cannot be exhausted. This is why every rotation of R 3 has an axis. A real eigenvector with eigenvalue 1.

Fundamental theorem of algebra. Every non-constant polynomial with complex coefficients has a complex root, and hence factors completely into linear factors over C . The field is algebraically closed, which is why adjoining i to R is the last extension needed: solving x 2 = − 1 incidentally solves everything else.

For matrices this is the statement that a characteristic polynomial always splits over C , so an n × n complex matrix always has n eigenvalues with multiplicity. The diagonalization unit's first obstruction, a polynomial that does not split, therefore never arises over C , and only the second obstruction, too few eigenvectors, can survive.

Worked instance. The rotation R = ( 0 − 1 1 0 ) has p ( λ ) = λ 2 + 1 , with roots i and − i . A conjugate pair, as the theorem requires. Their eigenvectors are ( 1 , − i ) and ( 1 , i ) , conjugates of each other. Checking the first: R ( 1 , − i ) T = ( i , 1 ) T and i ( 1 , − i ) T = ( i , − i 2 ) T = ( i , 1 ) T .

And the dimension is even, so no real eigenvalue is forced, consistent with a plane rotation fixing no real direction.

Example

Numbers whose structure is visible in the plane

The unit imaginary. i = e i π / 2 has modulus 1 and argument a quarter turn. Multiplying by it rotates without scaling: 1 ↦ i ↦ − 1 ↦ − i ↦ 1 , returning after four steps. That cycle is i 4 = 1 , and it is why powers of i repeat with period four.

A real number. − 3 = 3 e i π : modulus 3, argument π . Real numbers are the points with argument 0 or π , and multiplying by a negative real scales and reflects through the origin. Conjugation fixes them, which is the defining property of R inside C .

A number on the unit circle. 1 2 ( 1 + i ) = e i π / 4 has modulus 1. Multiplying by it is pure rotation by 45 ° , and its eighth power is e 2 π i = 1 . Every modulus-1 number is a pure rotation, which is exactly the set whose powers stay bounded.

The cube roots of unity. 1 , ω = − 1 2 + 3 2 i and ω ¯ = − 1 2 − 3 2 i sit at 0 ° , 120 ° and 240 ° on the unit circle. Each cubes to 1, and they sum to zero. The two real parts of − 1 2 cancel the 1 exactly.

They illustrate two things at once: that n th roots are equally spaced, and that the non-real ones come in a conjugate pair because z 3 − 1 has real coefficients.

A conjugate pair from a real quadratic. x 2 − 2 x + 5 has roots 1 ± 2 i , at modulus 5 and arguments ± arctan ⁡ 2 . Their sum is 2 and their product is 5 . Both real, which is forced: a conjugate pair always sums and multiplies to real numbers, which is why a real quadratic can have complex roots without any complex coefficient appearing.

Eigenvalues of a rotation. ( 0 − 1 1 0 ) has eigenvalues ± i , on the unit circle at ± 90 ° . The modulus 1 says the map preserves length; the argument π / 2 says it turns by a quarter. For a real matrix a complex eigenvalue r e i θ always reads this way, rotate by θ , scale by r , in some plane.

What the plane picture supplies. Modulus is distance, argument is angle, conjugation is reflection in the real axis, multiplication is rotate-and-scale. Every fact in this unit is one of those four read off a diagram, which is why sketching the point is the first move when an arctan or a root count is in doubt.

Non-example

Five errors with complex numbers

Reporting the imaginary part with its i . Writing Im ⁡ ( 3 + 4 i ) = 4 i . The imaginary part is the real number 4. A coordinate of the point, like the 3. The error makes Im return complex values, and identities such as z = Re ⁡ z + i Im ⁡ z then double-count the i .

Losing the sign flip in a product. Computing ( 3 + 4 i ) ( 1 − 2 i ) as 3 − 2 i − 8 = − 5 − 2 i by treating i 2 as + 1 , or as 3 − 2 i by dropping the term entirely. The correct value is 11 − 2 i , the + 8 arising because − 8 i 2 = + 8 . The modulus check catches it: | 11 − 2 i | = 125 matches | z | | w | = 5 5 , while the wrong answers do not.

Comparing complex numbers. Writing i > 0 or "the larger root". C carries no order compatible with its arithmetic, if i > 0 then i 2 > 0 , so − 1 > 0 ; if i < 0 then ( − i ) > 0 and squaring gives the same contradiction. Only moduli may be compared, and those are real.

Taking one root instead of n . Solving z 3 = 1 and answering z = 1 . There are three cube roots, at angles 0 , 2 π / 3 and 4 π / 3 ; the other two are − 1 2 ± 3 2 i . Every nonzero complex number has exactly n distinct n th roots, and stopping at the first one found loses the rest.

Expecting an unpaired complex eigenvalue from a real matrix. Reporting that a real matrix has eigenvalues 2 and 3 + i and nothing else. The characteristic polynomial has real coefficients, so 3 − i must also be a root. The pairing is forced. A stated spectrum that omits a conjugate is evidence of an arithmetic error rather than of an unusual matrix.

What unites them. The first two are arithmetic with a conceptual cause: not tracking what i contributes. The middle one imports a property R has and C does not. The last two stop at the first answer when the structure guarantees more. One root of n , one half of a pair.

Optional enrichment (1)

Application

What a complex eigenvalue tells you about a system

Rotation and scaling in a plane. When a real matrix has eigenvalue λ = r e i θ , the conjugate λ ¯ comes with it, and the two together describe the map's action on a real two-dimensional invariant subspace: rotate by θ , scale by r . No real eigenvector exists in that plane because no direction survives a rotation, and the complex pair is how the real structure is encoded.

That reading makes the modulus the quantity that matters for long-run behaviour. Iterating x k + 1 = A x k gives components that grow like r k and spin by θ each step:

| λ | Behaviour under iteration
> 1 spiral outward, unbounded
= 1 rotate on a fixed ellipse, bounded and non-convergent
< 1 spiral inward to the origin

The argument sets the period: a full revolution takes 2 π / θ steps, so ± i gives period 4, which is why the quarter-turn matrix satisfies R 4 = I .

Differential equations. For x ′ = A x the solutions involve e λ t , and e ( a + b i ) t = e a t ( cos ⁡ b t + i sin ⁡ b t ) . So the real part of the eigenvalue governs growth or decay and the imaginary part governs oscillation frequency. A system is stable exactly when every eigenvalue has negative real part, and it oscillates exactly when some eigenvalue is non-real.

The conjugate pairing is what keeps the solutions real: combining e λ t v and its conjugate e λ ¯ t v ¯ with conjugate coefficients produces a real-valued solution of the form e a t ( c 1 cos ⁡ b t + c 2 sin ⁡ b t ) . Complex numbers appear in the working and cancel from the answer.

Where this is used. Control engineering places poles, eigenvalues of a system matrix, in the left half plane for stability, and reads the damping from how close they sit to the real axis. Signal processing represents a sinusoid as the real part of A e i ω t , turning differential equations into algebra. Both rest on the same substitution.

What the pairing does not permit. A real matrix cannot have a lone complex eigenvalue, so a reported spectrum missing a conjugate is an arithmetic error. And a real matrix of odd size must have at least one real eigenvalue, since the non-real ones pair off, which is why every rotation of three-dimensional space has an axis it leaves fixed.

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