Exploration 3: Polynomials
December 1, 2023.Questions:
- How do we factor a polynomial with coefficients in a ring?
- How do we study the rest of ring theory from the lens of polynomial rings?
- What does the derivative of a polynomial mean in the context of ring theory?
Recall that to adjoin an element to a ring is to create a ring generated by the two: something like .
When you adjoin a symbol that commutes with the entire ring , the result is a polynomial ring. It turns out polynomial rings are fundamental in the sense that much of ring theory is built upon generalizing the properties of polynomials, such as irreducibility.
The elements of a polynomial ring are called polynomials with coefficients in , and look like this:
where are known as the coefficients of the polynomial , is known as an indeterminate over , and the exponent of the leading is known as the degree of the polynomial, denoted . The degree of a constant polynomial is zero, and the degree of the zero polynomial is undefined.
Let’s show some basic facts that hold when we form a polynomial ring.
- WTS the product of two nonzero polynomials in is always nonzero.
- Let and be the leading coefficients of respectively. Since are nonzero, and are nonzero.
- Then the leading coefficient of is . Since is an integral domain, this product is nonzero.
- Then since the leading coefficient of is nonzero, is nonzero, and we are done.
In this section, we define the operations possible on polynomials.
Polynomial addition/subtraction is straightforward – it is pairwise addition/subtraction of corresponding coefficients.
Polynomial multiplication is more complex. In general, it looks like Note that this means that the resulting coefficients are the convolution of the coefficients and . Also note that this implies that .
What about polynomial division? Dividing a polynomial by a polynomial with remainder means finding unique polynomials where (or ) such that . Let’s explore how this can be done.
- Let and .
- First of all, if then the only solution is . Otherwise if , then the only solution is and . Therefore we can induct on with the assumption that .
- If
,
then
implies
and therefore
are both constant polynomials
.
- Then we have in . In , the condition that either or collapses to just since .
- Since , becomes in . Thus the solution is and . This requires be a unit in so when is constant it must be a unit.
- Otherwise, assume that for all
,
there is some
such that
.
WTS that’s true for
as well.
- With the intention of applying the induction hypothesis, we’d like to obtain a polynomial of degree less than . This is easy when and have the same leading coefficient and degree; then has degree less than . Otherwise, we must use where is a factor that transforms the leading coefficient and degree of to match those of .
- Let and , where and are nonzero. Then the value of that lets us do this is .
- Note that this means that the leading coefficient of must be a unit. (This matches our earlier finding that when is constant, it must be a unit.) Then we have
- Since and have the same leading term , the difference cancels out the leading terms and therefore has degree less than . Then the induction hypothesis with and gives us unique polynomials such that (where either or ).
- Thus we have a solution and .
To see this, towards contradiction assume we have any two distinct solutions and where implies .
- We know that and therefore the RHS has degree .
- Then the LHS has degree .
- Since the LHS and RHS should have the same degree, this is a contradiction.
In summary, we always have addition, subtraction, and product defined for . But you can only divide by polynomials whose leading coefficient is a unit in . This means polynomial rings in general don’t admit a division algorithm, because they have nonzero polynomials that you can’t divide by. Rings that do admit such a division algorithm are known as Euclidean domains.
You can only divide by nonzero polynomials in whose leading coefficient is a unit in , but every leading coefficient is a unit when is a field. Thus you can divide by any nonzero polynomial in , making a Euclidean domain.
Following from the division algorithm, you can only divide by polynomials whose leading coefficient is a unit, and is always a unit. Therefore you can always divide by monic polynomials.
Corollary: Same, but for nonzero polynomials whose leading coefficient is a unit.
Since every nonzero element in a field is a unit, you can already divide by every element in a field: . Therefore all fields have a division algorithm and are Euclidean domains.
Note that the division algorithm in question requires a notion of degree for every nonzero element in the ring. To generalize the notion of degree to non-polynomial rings, this means having some function mapping each nonzero to a natural number called the Euclidean norm, where for all units . The Euclidean norm also needs to satisfy the divisibility condition where for every and nonzero , there is a division where either or . (We don’t need to mention the norm in the above proof, since in that proof.)
The Euclidean condition norm requires that for every , we have either or where either or . This is exactly the required division.
Then in general, a Euclidean domain is an integral domain for which a Euclidean norm is defined.
Remember that for polynomial rings that are not Euclidean domains, you can only divide by polynomials whose leading coefficient is a unit in . Then:
- If and divide each other, we have and .
- implies .
- implies .
- Therefore , which implies that are constant polynomials that don’t affect the degree of the product.
- The fact that both are monic shows that the leading coefficient is before and after multiplying by ’, which implies that are both .
- Therefore .
This last theorem actually applies in all integral domains. Let’s modify the statement a bit:
- and being nonzero in an integral domain implies that neither of them are zero divisors.
- If and generate each other, we have and , and therefore .
- Then where is not a zero divisor, implying .
- This means , i.e. are units.
- Thus means differs from by a unit.
- The converse is trivial — if differ by a unit , then they generate each other via the unit: and .
In this section, we explore the consequences of evaluating polynomials.
One of the most important things we can do with polynomials is evaluation, in which we substitute with .- Such a mapping is always a ring homomorphism.
- The resulting expression is a rational expression, made up of elements of connected with addition, subtraction, multiplication, integer scalar multiplication, powers, and division by units.
- Since ring homomorphisms preserve rational expressions, the resulting expression is an element of .
This substitution is formalized as the evaluation map (a ring homomorphism) . Applying the evaluation map to a polynomial can be denoted , but is more often denoted , the evaluation of at .
Since there is a constant polynomial for every , and constant polynomials remain unchanged by the evaluation map, every element of gets mapped to.
- The evaluation map , which evaluates a polynomial at , has kernel . To see this, notice that for every , implies the constant coefficient is , and therefore so the kernel of is .
- The first ring isomorphism theorem says . We just showed , and since is surjective, , therefore the above becomes .
Remember that you can always divide by a monic polynomial in polynomial rings. We’ll see that division relates to evaluation in multiple ways:
Since is monic, the division algorithm implies some unique such that . Evaluating at gives . Therefore, the remainder is .
The evaluation replaces with . If , then . Conversely, if , then since is monic, by the remainder theorem divided by results in . But , so this becomes .
When , then is called a root of , and the following are equivalent:
- for some polynomial
- , the principal ideal generated by
Since the factor theorem lets you factor a polynomial by finding its roots, finding the roots of polynomials is pretty important if you want to factor polynomials.
This is easily proved by induction by applying the factor theorem times.
The theorems below are useful for factoring a polynomial (i.e. find roots) in a given polynomial ring. Here is an important one for integer polynomials :
- Let be a rational root of the polynomial .
- Assume are coprime integers – if they are not, divide both and by their GCD to make them coprime.
- Since is a root of , we have :
- Multiply both sides by :
- From here, we can go in two directions. First, isolate the term and factor out from the other terms: This means is a factor of . Since are coprime integers, must divide .
- Second, isolate the term instead and factor out from the other terms: Similarly, this means is a factor of . Since are coprime integers, must divide .
Corollary: when is monic, the only rational roots are all the integer factors of .
To remember this theorem, you can think about the polynomial which obviously has a root . So the numerator divides the constant , and the denominator divides the leading coefficient .
- Try to interpret as a rational root () of some polynomial .
- If , it would be a rational root of the polynomial . We know is one such root.
- By Rational Roots Theorem, and , therefore . Then so the root must be some integer . Therefore is the square of some integer.
- (Same proof as above)
- If , it would be a rational root of the polynomial . We know is one such root.
- By Rational Roots Theorem, and , therefore . Then so the root must be some integer . Therefore is the th power of some integer.
In this section, we classify the unique factorization of real and complex polynomials.
All the work involved in factoring complex polynomials rests on this one theorem:
The proof often requires complex analysis or topology. Here is a proof due to Artin, trying not to use many ideas outside of ring theory:
- It is a theorem that if you treat evaluation of the polynomial as a map , then is continuous.
- Evaluate at each point on a circle of radius around the origin of the complex plane. Since is continuous, the images represent some loop on the complex plane. Each point on the circle can be represented in polar coordinates as for some angle . Let its corresponding point on the loop be .
- There are two loops we want to consider:
- First, with approaching , we know the images are all close to the constant coefficient of . So is a tiny loop around . We assume is nonzero – if it’s zero then implies is a root and we are done.
- Second, with approaching , we know the images are very large but also represent some loop. Since for large values the leading term of dominates the other terms, which we can write as , we know and (because ) therefore . This implies the distance between and the leading term is always less than , no matter what is. If you imagine increasing, then as walks a circle of radius around the origin, while (being continuous) is following a distance less than behind and therefore the loop it traces must also enclose the origin.
- Importantly, the first loop does not enclose the origin, while the second one does. Since is continuous, varying within will continously vary the corresponding loop between one that doesn’t enclose the origin and one that does. So at some between and , the resulting loop crosses the origin, and therefore we get a root for some .
This is repeated application of the FTA. You apply FTA to find a root , factor it out with the factor theorem to get , and repeat with until is a constant polynomial . Since we’re always factoring out a monic polynomial , the leading coefficient never changes, and so the final is the leading coefficient of .
- Since complex conjugation fixes the real numbers, when is a real polynomial.
- Therefore, if , then and therefore implies is also a root of .
- Do the same thing you did for complex polynomials, factoring into a product where the roots are complex.
- Since the coefficients of are real, by the Conjugate Root Theorem, the complex roots come in conjugate pairs. Then the product of their corresponding factors, , is a monic irreducible real quadratic, i.e one of the .
- Therefore, after combining all complex factors into monic real quadratic factors, can be written in the form where are the product of each conjugate pair of complex factors within the original .
Corollary: all irreducible polynomials in are linear or quadratic (have degree or ).
We see that the Fundamendal Theorem of Algebra implies that (nonconstant) polynomials in or factor uniquely into a constant times a product of (monic) irreducible factors.
In this section, we examine the ideals of a polynomial ring.
Let’s explore what the ideals of a polynomial ring look like.
- If is the zero ideal, it is generated by and we are done.
- Otherwise, contains a nonzero polynomial.
- We can divide by monic polynomials, but doesn’t necessarily contain one, unless is a Euclidean domain – then we can make any polynomial monic by dividing the polynomial by the leading coefficient. Since any product with an element in the ideal is also in , always contains a monic polynomial.
- Take a monic polynomial of minimal degree in . Every polynomial must have as a factor because the division algorithm lets us divide by monic polynomials.
- Then the division algorithm says where either or .
- Since , must also be in . We can also make monic and the result is also in .
- Since contradicts being the monic polynomial of minimal degree in . Therefore .
- This means . Since was arbitrary, generates .
- To show that
uniquely generates
,
assume that
is another generator of
.
Then
and
generate each other:
and
.
But monic polynomials that divide each other are
equal,
so
.
- implies , and implies . Therefore .
- implies that are constant polynomials that don’t affect the degree of the product. The fact that both are monic (leading coefficient is before and after multiplying by ’) implies that are both . This implies .
This means we can write all quotient rings of ( a field) as , where is some monic polynomial. Since the generator of every ideal is unique, this implies a bijection between monic polynomials in and nonzero ideals in .
When every ideal of a ring is principal, we have a principal ideal domain (PID).
It turns out every Euclidean domain is a PID.
- Let be a Euclidean domain with norm . Then for every element , we can divide by nonzero to get where either or .
- We can show that for every ideal in , every element of is generated by some element $b$ with the smallest norm . That is, for some .
- This follows immediately from the division algorithm. We have , and since is minimal by definition, there is no such that , therefore .
In this section, we determine what it means to quotient in polynomial rings defined over a field .
In particular, when is a field, then is a Euclidean domain and therefore a PID. Let’s explore polynomial rings defined over a field .
- When you quotient by some ideal , you’re effectively sending the polynomial to and therefore enforcing the relation on the polynomial ring. That means whenever , .
- But in a Euclidean domain, every polynomial of degree at least can factor out : . This means every polynomial of degree and above gets sent to .
- The remaining polynomials are necessarily of degree less than .
We identify with , so all the degree polynomials get sent to , leaving only the degree and polynomials (and the zero polynomial).
- Here we identify with . We can understand this as (in ).
- Since every resulting polynomial is at most degree , they are in the form .
- In other words, the elements of are .
- This is exactly how we write elements of , so the two rings are isomorphic.
- Here we identify with . We can understand this as (in ).
- Since every resulting polynomial is at most degree , they are in the form .
- In other words, the elements of are .
- But this is the same as adjoining an element to .
To generalize these last two examples, when is a field and is irreducible, we can take the quotient to form a ring isomorphic to , where is a solution to (i.e. a root of ). It turns out the result is a field:
- Since is a PID, the result follows directly from this theorem.
- (Note that if is reducible, then sends to , meaning there are zero divisors so the result fails to be even an integral domain.)
In other words, the quotient rings of polynomial rings can be used to construct field extensions, which we’ll explore in depth later on.
In this section, we introduce how the derivative of a polynomial helps determine roots.
The derivative of the polynomial can be constructed by taking each term of (), and mapping it to , where is mapped into using the canonical homomorphism (i.e. taking but times.)
The derivative helps us determine when a polynomial has multiple roots. is a multiple root of if has a factor for some .
- Since has as a root, factor out . To show that is a multiple root, we can show that also has as a root, i.e. .
- By the product rule, . Since , we have , implying , implying is a root of .
Exploration 2: Ring homomorphisms