We now have fields: number systems in which we can
add, subtract, multiply, and divide by anything nonzero.
The next objects built on top of a field are
polynomials. They will be everywhere in this book: as
examples of vectors in Chapter 1, as the characteristic
and minimal polynomials of a matrix later on, and as the
reason some fields behave differently from others. This
section says precisely what a polynomial is, introduces
its degree, and explains why a polynomial is
not the same thing as the function it
defines.
What a
polynomial is
At school, a polynomial is “an expression like ”. That is a
good picture, but it leaves one question open: what is
? One tempting
answer is that is
a number to be plugged in, so a polynomial is really a
function. This answer breaks down as soon as we leave
the familiar number systems.
Work over the field of Example (Arithmetic on and the
Field ),
where .
The expressions and
look different. But if we plug in the two elements of
, we get and . As
functions on ,
the two are the same. If a polynomial were its
function, then would be the zero polynomial, and it would
have no sensible degree. We want to be a genuine
polynomial of degree 2, so we must define polynomials by
their coefficients alone.
A polynomial is its list of coefficients, and
nothing else.
Definition
0.8.1 (Polynomial)
Let be a
field. A polynomial over in the
indeterminate is
a sequence of elements of , indexed by , such that
only finitely many are nonzero. That is,
there is some with for every .
The element
is the coefficient of . We write
the polynomial as Two polynomials and are
equal if and only if for
every .
In words: a polynomial is an infinite list of
coefficients that is eventually all zero. The expression
is only a way of displaying the list: marks the position
, and we stop
writing once the remaining coefficients are all zero.
Two polynomials are equal exactly when they agree
position by position. A sequence indexed by is a function , so this is
just equality of functions in the sense of Definition 0.4.1.
There is one thing to check about the notation. The
number in the
display is not unique: if for every , the same is
true for every . Writing or
only adds a term , which we
agree to drop. So the display names the same sequence
whichever admissible we use. We also drop
terms with zero coefficient in the middle, write for , and write
for .
Example
(Polynomials over various fields)
Read off the coefficient sequence of each polynomial,
and check it against Definition 0.8.1.
(The symbol for the set of all
polynomials over
is defined formally in Definition 0.8.2
below.)
Solution. The first is the sequence
of real numbers. It has finitely many
nonzero terms, so it is a polynomial over .
The second is . Its coefficients
are real but irrational; the definition only asks that
they lie in the field.
The third is , a polynomial over .
The fourth is with entries in . It is
not the zero sequence, so it is not the
zero polynomial, even though it vanishes at both points
of .
The constant
is the sequence . It is a polynomial over , , or . Over it would be , because
there.
The last, , is the zero
polynomial. It is the degenerate case: every
coefficient is zero, and the finiteness condition holds
with . It
matters because it is the one polynomial whose degree
needs a special convention, as we will see.
Now the nonexample, by a minimal change. Take the
polynomial , whose sequence is ,
and change every later to . The result ,
informally “”, is still a sequence of elements
of . What fails
is the clause only finitely many
coefficients are nonzero, so this is
not a polynomial. (It is a formal
power series, which we will not need.) Expressions
such as
and are
not polynomials either: they are not of the form with at all.
Why insist on finitely many nonzero coefficients?
Because we want to plug elements of the field into
polynomials, which means forming the sum , and in a
field only finite sums make sense. Finiteness is also
what gives every nonzero polynomial a highest power, its
degree.
Adding and
multiplying polynomials
The coefficient picture tells us how to add and
multiply. Adding and at school means collecting like powers, so we
add coefficients position by position. Multiplying means
expanding every product and
collecting like powers, so the coefficient of collects all pairs
with .
Definition
0.8.2 (The polynomial ring )
Let be a
field. The set of all polynomials over
is denoted . For and
in
, define the
sum and the product by their coefficients:
We must check that and
are again polynomials, that is, that their coefficient
sequences are eventually zero. Suppose for every and for every . If , then
. If , then in each product either or , because
otherwise . So every term is , and the coefficient of
in is . Hence both are
polynomials, and addition and multiplication are well
defined on .
With this multiplication, has coefficient
sequence , and by induction on the -th power of the
polynomial is the
sequence with a
in position and
elsewhere. So the
notation in Definition 0.8.1
agrees with the actual power, and is an honest
sum of products.
Example
(A product, coefficient by coefficient)
In ,
compute from the definition.
Solution. Here and , with all other coefficients . The coefficient of
in the product
is : and every coefficient with is by the argument above
(here ).
Hence , which is what expanding
by hand gives.
The operations obey the rules we expect. We record
them once, so that later sections can use them
freely.
Theorem
0.8.1 (Arithmetic in )
Let be a field
and . Then:
-
and ;
- , and
, where
;
- and
;
- ,
where is the
constant polynomial ;
- .
Idea. Two polynomials are equal
when their coefficients agree, so each identity reduces
to an identity between coefficients, which the field
axioms supply. For products it helps to write the
coefficient of
in
symmetrically, as a sum over all pairs of natural numbers
with .
Proof. Let , , and
.
By Definition 0.8.1, it
suffices to compare the coefficient of on both sides, for
each .
Parts 1, 2, and 4 hold because in each position they
are the corresponding field axioms of Definition 0.7.1: for
example, the coefficient of in is ,
the coefficient in . For 4, the coefficient of in is
with and
for , which equals
.
For 3, the coefficient of in is .
Since multiplication in is commutative, this
equals , the coefficient in . Next, the coefficient
of in is where the equality uses distributivity and
associativity in .
The same computation for gives . Therefore .
For 5, the coefficient of in is by distributivity in , which is the
coefficient in . This proves the theorem.
A set with an addition and a multiplication
satisfying these rules is called a commutative
ring; this is where the name “polynomial ring”
comes from. We will not need the word again in this
chapter. What matters is that we may now calculate with
polynomials exactly as at school.
Quick check. Over , are and equal as
polynomials? Over , are and equal as
polynomials?
Solution. Both answers are yes, but
for a reason that depends on the field. Expanding gives
, with coefficient sequence . Over
this is exactly
the sequence of . Over we have , so the
sequence is , which is the sequence of .
Degree
The most useful single number attached to a
polynomial is the highest power of that actually occurs.
Every nonzero polynomial has one: it has at least one
nonzero coefficient and only finitely many, so there is
a largest position holding a nonzero coefficient. The
zero polynomial has no such position, and we must decide
what to do with it.
Definition
0.8.3 (Degree)
Let .
- If ,
the degree of , written , is the
largest with . The coefficient is the
leading coefficient of , and is
monic if its leading coefficient is
.
- The zero polynomial has degree .
We use the conventions and for every , and .
Examples, simplest first. A nonzero constant has degree ; its leading
coefficient is .
The polynomial is monic of degree . The polynomial from
Example (A product, coefficient by coefficient)
has degree and
leading coefficient . Over , has degree , even though it
vanishes at every point of .
Why , and
not or ? Look at the formula
we expect: the degree of a product is the sum of the
degrees. With it fails at once, since would give
. With it fails too: . The
formula needs for every , and is exactly the
symbol with that property. The convention keeps a
formula true, and that is its only job.
It turns out that the degree of a sum is controlled
by the larger degree, and the degree of a product is the
sum of the degrees:
Theorem
0.8.2 (Degree of a sum)
Let be a field
and .
Then with equality whenever .
Proof. Let , , and
. If , then , so and both sides are . Suppose . For every
we have
and
, so
by Definition 0.8.3.
Hence the coefficient of
in is for every , and therefore
.
Now suppose ; by symmetry we may assume , so
.
Then and
, because
. The
coefficient of
in is , so
.
Together with the first part, . This
proves the theorem.
The inequality can be strict: over any field, . The leading terms cancel.
That is the only way the degree of a sum can drop.
Theorem
0.8.3 (Degree of a product)
Let be a field
and .
Then If and
are nonzero, the
leading coefficient of is the product of
their leading coefficients.
Idea. Expanding , the only way to
reach is
, and nothing reaches beyond. So the top
coefficient is . The one real question is whether could be . In a field it cannot,
and this is exactly where the field axioms enter.
Proof. If or , then by the definition
of the product, so both sides equal by the
conventions in Definition 0.8.3.
Suppose now and are nonzero, with and . Then , , for , and for .
We showed after Definition 0.8.2 that
the coefficient of in is for every . For , the
coefficient is . A term with has , and a term with
has , so
. Hence only
, survives, and the
coefficient is .
Since
and , Theorem 0.7.1 gives
,
because a product of nonzero elements of a field is
nonzero. Therefore and the leading coefficient of is , as claimed.
Warning. The field axioms are doing
real work here. The same definitions make sense with
coefficients in , which is
not a field. There , because . The
factors have degrees and , but the product has
degree , not .
The first consequence is that polynomials over a
field behave like integers: a product can only be zero
if a factor is, and nonzero factors can be canceled.
Corollary
0.8.4 (No zero divisors in )
Let be a field
and .
- If , then
or .
- If and
, then
.
Proof. For 1, we prove the
contrapositive. Suppose and . Then , so by Theorem 0.8.3, . In particular , so
.
For 2, suppose and . By Theorem 0.8.1, .
By part 1 and , we get , that is, . This proves the corollary.
Quick check. Let with
and
. What
are , , and ? Can you say
what
is?
Solution. By Theorem 0.8.3, and . Since the
degrees differ, Theorem 0.8.2 gives
.
The degree of is not determined: if the leading
coefficient of is
, the terms cancel and the
degree is at most
(it could even be if ); otherwise it is
.
Polynomials
of bounded degree
In linear algebra we constantly need “all polynomials
up to a given size”. For instance, the quadratics are
described by three numbers, much like points of . So we give such
collections names.
Definition
0.8.4 (Polynomials of degree at most )
Let be a field
and . The
set of polynomials over of degree at
most is
The two descriptions agree: says exactly
that every coefficient beyond position is zero, and the
coefficients are then free, any of them allowed to be
zero. In particular the zero polynomial lies in , since .
Example
(Inside )
Which of , ,
, , and lie in
?
Which lie in ?
Solution. All five lie in . Their
degrees are ,
, , , and (the last is the
polynomial , since
as
polynomials). Only and lie in , which is
the set of constant polynomials, included.
Sometimes we need the degree to be exactly , for instance when we
speak of “a quadratic” and mean that the term is really
there.
Definition
0.8.5 (Polynomials of degree exactly )
Let be a field
and . The
set of polynomials over of degree
exactly is
Example
(Comparing the two notations)
For each of , ,
and , decide
whether it lies in and
whether it lies in .
Solution. The polynomial has degree , so it lies in both.
The polynomial has degree , so it lies in but
not in . The zero
polynomial has degree , so it lies
in ,
but ,
so it is not in . In general
for , and the union is
disjoint.
The two sets differ in one small clause, , and that
clause changes their behavior completely.
Warning. is closed
under addition, but is not. For example and both lie in
, but
their sum has
degree . The
leading terms cancel. Also does not
contain . In
Chapter 1 this is why is a
subspace and is not.
The positive half is Theorem 0.8.2 at work:
if and
, then
. Multiplying by a constant also cannot raise
the degree, by Theorem 0.8.3.
Evaluation
and roots
A polynomial is not a function, but every polynomial
defines a function: plug an element of the
field in for .
Definition
0.8.6 (Evaluation and roots)
Let be a
field, , and . The
value of at is the element where . An element is a root of if . The function
, , is the
polynomial function of .
The value does not depend on the choice of : enlarging adds terms (by Theorem 0.7.1), which
do not change the sum. So is well defined.
For example, has and , so
is a root. Over
, the polynomial has , so is a root; the other
two values are and , so is
its only root in .
Evaluation turns the operations of into the operations
of :
Theorem
0.8.5 (Evaluation respects sums and
products)
Let be a
field, , and . Then and the constant polynomial has value at .
Proof. Let and , where we choose and large enough that all
nonzero coefficients are included. The statement about
constants is immediate from Definition 0.8.6. For
sums, taking and padding with zero coefficients, by distributivity in .
For products, all nonzero coefficients of occur at positions
, so
where the first equality is Definition 0.8.2, the
second uses distributivity and and
regroups the pairs , the third uses
commutativity of multiplication in
to move past , and the last is
distributivity again. This shows .
Note which step used commutativity. In the next
section we will plug a square matrix into a polynomial.
Products of matrices do not commute in general, but the
proof only moves scalars past powers of
, and multiplies
powers of the same ; both are still
allowed for matrices, so the same identity will hold
there.
As a first use, a root of a factor is a root of the
product: if , then . Conversely, if then , so or by Theorem 0.7.1. This is
how one solves at school.
Now we can return to the question from the start of
the section.
Example
(Different polynomials, same function)
Over ,
compare the polynomials and ,
and the polynomials and , both as polynomials
and as functions .
Solution. As polynomials, has coefficient
sequence and has . They
differ in position , so by Definition 0.8.1. Its
degree is .
As functions, has two elements, and So the polynomial function of is the zero
function, the same as that of . Both elements of are roots of a
polynomial of degree 2 that is not the zero
polynomial.
Similarly as polynomials, but and , so they define
the same function. Indeed, by Theorem 0.8.5, two
polynomials define the same function exactly when their
difference is a polynomial whose function is zero, and
in .
Warning. A polynomial is
not a function. Two different polynomials can
define the same polynomial function, as and do over . So “ for every ” does
not imply in general, and we may never read off
coefficients or a degree from the values alone. This
happens over every finite field: if ,
then has degree by Theorem 0.8.3, yet
vanishes at every by Theorem 0.8.5. Over
, Exercise (C2: A nonzero polynomial vanishing everywhere)
below gives the shorter example .
Over an infinite field such as , , or , the problem
disappears: a polynomial whose function is zero is the
zero polynomial, so polynomials and polynomial functions
can be identified. We prove this in Chapter 3 (in the
section on applications of linear systems), once we can
count roots. Until then, whenever we say two polynomials
are equal we mean their coefficients agree.
Looking
ahead
Two tools will be built on this section later.
Exercises
A. Check your
understanding
Exercise
(A1)
- (a) Define the
degree of a polynomial over a field , including the zero
polynomial. State the formula for .
- (b) Is , with every coefficient equal to , a polynomial over
? Justify your
answer.
- (c) Determine
whether the following statement is true: “for all , .” Justify your answer.
- (d) Determine
whether the following statement is true: “if and for every , then .” Justify your
answer.
- (e) Explain why
is
not closed under addition, while is.
Solution.
- (a) For ,
is the
largest with
; and
.
For all , (Theorem 0.8.3).
- (b) No. Its
coefficient sequence has infinitely many nonzero terms, so
it fails the clause “only finitely many are nonzero” of Definition 0.8.1.
- (c) False. Take
and . Then has degree
, while
. Only the inequality holds in general (Theorem 0.8.2).
- (d) False. By Example (Different polynomials, same function),
satisfies , but .
- (e) The sum of and , both of degree
exactly , is , of degree . For : if and , then by Theorem 0.8.2.
B. Practice
Exercise
(B1: Sums, products, and degrees)
- (a) In , let and
. Compute and ,
and give their degrees. Which inequality or formula from
this section does each degree illustrate?
- (b) In , compute .
Hence find all roots in of the
product.
Solution.
- (a) Adding
coefficients gives , of degree . Here and
the terms
cancel, so the inequality of Theorem 0.8.2 is
strict. Expanding, of degree , as Theorem 0.8.3
predicts; its leading coefficient is .
- (b) Expanding, . In we have , so the product is
. By Theorem 0.8.5 and Theorem 0.7.1, is a root of the
product if and only if or . The first gives . For the second,
the values at are ,
, and . Hence the only
root in is
, which occurs
in both factors.
Exercise
(B2: Degree of a composition)
For and in , define the
composition , where .
- (a) Prove that if
and are nonconstant, then
.
- (b) Give an example
showing the formula fails when is constant.
Hint: first find .
Solution.
- (a) Let and
,
so . By
Theorem 0.8.3 and
induction on (Theorem 0.2.7), for every
: the case
is , and . Hence, again by Theorem 0.8.3, , and for , (it is or ). Let . Applying Theorem 0.8.2 times gives . Since , the equality case of Theorem 0.8.2 gives
. This proves .
- (b) Take and . Then has
degree ,
while .
Exercise
(B3: All small polynomials over )
List all polynomials in . For
each, give its degree and its polynomial function (the
values at and
). Hence determine
which of them define the zero function, and explain why
every function is the polynomial function of exactly two
of them.
Solution. A polynomial
with
has value at
and at . With choices of
coefficients:
|
|
0 |
0 |
|
0 |
1 |
1 |
|
1 |
0 |
1 |
|
1 |
1 |
0 |
|
2 |
0 |
1 |
|
2 |
1 |
0 |
|
2 |
0 |
0 |
|
2 |
1 |
1 |
The zero function requires and , that
is, and
. Hence
exactly and define the zero
function.
A function is determined by the pair . Given such
a pair , the
polynomial defines exactly when and . The
first fixes ,
and for each of the two choices of the second fixes
.
Therefore exactly two of the eight polynomials define
, and the table
confirms this.
C. Going deeper
Exercise
(C1: Roots of a quadratic)
Let be a
field.
- (a) Let and with . Prove that .
- (b) Deduce that a
nonzero polynomial in has at most
roots in .
- (c) The same
definitions make sense with coefficients in . Show that has four roots
there, and name the step of (b) that breaks.
Hint for (b): use (a) together with Theorem 0.8.5.
Solution.
- (a) Since , we have , so
.
Expanding with Theorem 0.8.1,
- (b) Let with . Case
1. .
Then
is constant and for every , so has no roots. Case
2. ,
say with
. Then
if and
only if , so has exactly one root.
Case 3. , say with . If
has no root we are done. Otherwise let be a root. By (a),
with
,
of degree since
. Let be any root of . By Theorem 0.8.5, ,
so or by Theorem 0.7.1. By Case
2, has exactly
one root. Hence every root of is or the root of , and has at most roots. This proves the
claim.
- (c) In , , , , and , so are four roots
of . The
argument in (b) breaks at “ implies
or ”: for , we get with both factors nonzero. That step needs
the field property that a product of nonzero elements is
nonzero.
Exercise
(C2: A nonzero polynomial vanishing everywhere)
Let be a prime
and .
- (a) Fix .
Prove that the map , , is a
bijection.
- (b) Deduce that
for
every .
- (c) Hence show that
the polynomial is not the zero polynomial but that
its polynomial function is the zero function.
Hint for (b): multiply together all the elements
of in two ways.
Solution.
- (a) The map lands in
,
since a product of nonzero elements of a field is
nonzero (Theorem 0.7.1). It is
injective: if , multiplying by gives . The set is
finite with
elements, so an injective map from it to itself is
surjective by Theorem 0.4.9, hence
bijective.
- (b) Let be the product of all
elements of
;
it is nonzero by Theorem 0.7.1. Since
is a
bijection by (a), the elements , as runs over , are
the same elements in a different order. Multiplication
in is commutative
and associative, so the product does not depend on the
order, and Multiplying by gives .
- (c) The coefficient
of in is , so the
polynomial is nonzero, of degree . For its function:
, and
for , (b)
gives . Hence every element of
is a root,
and the polynomial function of is the zero
function. For
this is , the polynomial of Example (Different polynomials, same function).
Exercise
(C3: Which polynomials have inverses?)
- (a) Let be a field and with . Prove that and are nonzero
constants.
- (b) Show that (a)
fails with coefficients in by computing
there.
Solution.
- (a) Since , neither
nor is the zero polynomial,
so . By Theorem 0.8.3, . Two natural numbers with sum are both , so .
Therefore and
are nonzero
constants.
- (b) In , , because . So has degree and is its own inverse.
The proof of (a) breaks at Theorem 0.8.3, which
fails here because the leading coefficient .