Chapter 4 - Polynomials (short)

Again, we denote F as R or C. Really, this can be any field, which you look at more in an Abstract Algebra course.

Complex Conjugate and Absolute Value

R(z), I(z)

Suppose z=a+bi where a,b∈R. The real part of z, denoted R(z), is defined by R(z)=a. Similarly, the imaginary part of z, denoted I(z), is defined by I(z)=b.

So then:

z=R(z)+I(z)i
Complex Conjugate z¯, absolute value |z|.

Suppose z∈C.

  • The complex conjugate of z∈C, denoted z¯, is defined by z¯=R(z)−I(z)i.
  • The absolute value of a complex number z, denoted |z|, is defined by |z|=R(z)2+I(z)2.
Properties of C.

  • z+z¯=2R(z);
  • z−z¯=2I(z)i;
  • zz¯=|z|2;
  • w+z¯=w¯+z¯ and wz¯=w¯z¯;
  • z¯¯=z;
  • |R(z)|≤|z| and |I(z)|≤|z|;
  • |z¯|=|z|;
  • |wz|=|w||z|;
  • |w+z|≤|w|+|z| (triangle inequality).

Uniqueness of Coefficients for Polynomials

If p∈P(F) where p=0→ then all ai=0.

Suppose a0,...,am∈F. If:

a0+a1z+⋯+amzm=0

for every z∈F then ai=0 for all 0≤i≤m.

Proof
We'll prove the contrapositive. If not all the coefficients are 0, then by changing m we can assume some am≠0. Let:

z=|a0|+⋯+|am−1||am|+1

Note here that z≥1 and thus zj≤zm−1 for all j=0,...,m−1. Using the triangle inequality:

|a0+a1z+⋯+am−1zm−1|≤(|a0|+|a1|+⋯+|am−1|)zm−1<|amzm|

Thus a0+a1z+⋯+am−1zm−1≠−amzm. Hence a0+a1z+⋯+am−1zm−1+amzm≠0.
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This lemma implies then that the degree of a polynomial is uniquely determined, namely by the first ai≠0. For notation, we say that deg(p)=m for a polynomial like the one above. For simplicity, deg(0)=−∞, using the obvious arithmetic with −∞.

The Division Algorithm for Polynomials

Division Algorithm for Polynomials

Suppose that p,s∈P(F) with s≠0. Then there exist unique polynomials q,r∈P(F) such that:

p=sq+r

where deg(r)<deg(s).

We actually did a proof of this in lecture via Lecture 21 - Polynomial Spaces (4.A)#^79ae01.

Zeros of Polynomials

zero of a polynomial, factor

A number λ∈F is called a zero (or root) of a polynomial p∈P(F) if:

p(λ)=0

On the other hand, a polynomial s∈P(F) is called a factor of p if there exists a polynomial q∈P(F) such that p=sq.

Although zeroes and factors are different concepts, they are related by the following lemma:

Zeroes of a polynomial correspond to degree-1 factors

Suppose p∈P(F) and λ∈F. Then p(λ)=0 iff there is a polynomial q∈P(F) such that:

p(z)=(z−λ)q(z)

for every z∈F.

Really, this is saying that if you know there's a zero, then you can factor it out, and if you have a factor, then it's a valid zero.

Proof
Going ← is obvious, since if p(z)=(z−λ)q(z) then p(λ)=(λ−λ)q(λ)=0q(λ)=0.

Going →, suppose that p(λ)=0. The polynomial z−λ is degree 1. Because a polynomial with degree less than 1 is a constant function, using the Division Algorithm for Polynomials implies there's some polynomial q∈P(F) and a number r∈F such that:

p(z)=(z−λ)q(z)+r

for every z∈F. Since p(λ)=0 then plug z=λ:

p(λ)=(λ−λ)q(λ)+r=0→r=0

thus r=0 so then p(z)=(z−λ)q(z) as required.
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A polynomial has at most as many zeroes as its degree

Suppose p∈P(F) is a polynomial with degree m≥0. Then p has at most m distinct zeros in F.

Proof
If m=0 then p(z)=a0≠0 so p has no zeros.

If m=1 then p(z)=a0+a1z where a1≠0. There's only one zero λ=−a0/a1.

Suppose m>1. We use induction on m, assuming that every polynomial with degree m−1 has at most m−1 distinct zeros. If p has no zeros in F then we are done. If p has a zero λ∈F then by Chapter 4 - Polynomials (short)#^b4d22e there's a polynomial q such that:

p(z)=(z−λ)q(z)

for all z∈F. Clearly deg(q)=m−1. The equation above shows that if p(z)=0 then either z=λ or q(z)=0. In other words, the zeros of p consist of λ and the zeros of q. By our induction hypothesis, q has at most m−1 distinct zeros in F. Thus p has at most m distinct zeros in F.
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Factorization of Polynomials over C

Fundamental Theorem of Algebra

Every non-constant polynomial with complex coefficients has a zero.

We just won't prove it here, as the proof uses Liouville's theorem which we haven't proved. If we had to prove it we'd do the following. Let p be a non-constant polynomial with complex coefficients. Suppose p has no zeros. Then 1/p is an analytic function on C. Furthermore, |p(z)|→∞ as |z|→∞, which implies that 1/p→0 as |z|→∞. Thus, 1/p is a bounded analytic function on C. By Liouville's Theorem, every such function is constant, but if 1/p is constant, then p is constant, contradiction our assumption that p is non-constant.

Factorization of a polynomial over C.

If p∈P(C) is a non-constant polynomial, then p has a unique factorization (except for the order of the factors) of the form:

p(z)=c(z−λ1)…(z−λm)

where c,λi∈C for all i.

See Year3/Winter2024/MATH306-LinearAlgebraII/2015_Book_LinearAlgebraDoneRight.pdf#page=125 for the proof if you're curious. It's a relatively simple proof though, just long for a write-up here. Notice that both existence and uniqueness of these factors are here.

Factorization of Polynomials over R

We've seen how factoring over C allows us to use λ∈C, but what if we are restricted to factorizing over R?

Polynomials with real coefficients have zeros in pairs

Suppose p∈P(C) is a polynomial with real coefficients. If λ∈C is a zero of p, then so is λ¯.

Proof
Let:

p(z)=a0+a1z+⋯+amzm

where a0,...,am are real numbers. Suppose λ∈C is a zero of p. Then:

a0+a1λ+⋯+amλm=0

Take the complex conjugate of both sides of this equation, obtaining:

a0+a1λ¯+⋯+amλ¯m=0

via the property of complex conjugate via Chapter 4 - Polynomials (short)#^4d08d5. Thus λ¯ is a zero for p.
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Factorization of a quadratic polynomial

Suppose b,c∈R. Then there is a polynomial factorization of the form:

x2+bx+c=(x−λ1)(x−λ2)

where now λ1,λ2∈R iff b2≥4c.

We omit the proof here, which again is at Year3/Winter2024/MATH306-LinearAlgebraII/2015_Book_LinearAlgebraDoneRight.pdf#page=127. The proof is very derived from elementary algebra you've likely done before.

Factorization of a polynomial over R

Suppose p∈P(R) is a non-constant polynomial. Then p has a unique factorization (except for the order of the factors) of the form:

p(x)=c(x−λ1)…(x−λm)(x2+b1x+c1)…(x2+bMx+cM)

where c,λ1,...,λm,b1,...,bM,c1,...,cM∈R with bj2<4cj for each j.

Again, the proof is long and arduous. Look at Year3/Winter2024/MATH306-LinearAlgebraII/2015_Book_LinearAlgebraDoneRight.pdf#page=128.