Polynomials are probably the most usual types of functions out there, because they do not need any heavy machinery to be introduced: all one needs to know is how to add and multiply numbers. This alone justifies a discussion of polynomials. However, seeing polynomials as merely “simple functions” is reductive, and indeed, a more abstract point of view is at the same time more direct, more straightforward, and more general. This posts discusses basic properties of polynomials in a classical context, namely polynomials with real coefficients. This is merely for convenience and clarity: for algebra buffs out there, everything is still true in some general field instead of just real numbers.
Definitions
Discussion
The usual definition of a polynomial is a function written
where and
. As such, this “function” is missing a few elements, notably a domain and a co-domain. Classically, we choose the domain and co-domain to be
, sometimes
. The issue with this is that it instills a layer of complexity that is not needed, and at the same time decreases the generality. A polynomial can be used as a function, but many properties of polynomials have nothing to do with this. Hence, it is better to see a polynomial as merely its coefficients. The only other thing that we need to do is to say how these coefficients behave when we add or multiply polynomials. Well, as one would expect…
Formal definition
We will always assume that our polynomials have coefficients in . You could replace
with
if you know complex numbers, or with any field if you are familiar with abstract algebra. Recall also that our
includes
.
- A (real) polynomial is a sequence
of real numbers whose terms are all zero for
large enough.
- The terms
are called the coefficients of the polynomial.
- The set of all polynomials is denoted
.
- The zero polynomial, written merely
, is the polynomial whose coefficients are all zero.
- If
, its degree, denoted by
, is
if
, and otherwise the index of the largest coefficient which is not zero. In formulas, for
,
- If
has coefficients
and degree
, the coefficient
is called its constant coefficient, and the coefficient
is called its leading coefficient.
In a classical setting, think of such a sequence as representing the polynomial
. The notation
is not totally standard, and the notation
instead is commonly use in algebra.
It is natural and convenient to say that a polynomial has coefficients
, and we shall indulge. But formally, a polynomial is its coefficients:
. Therefore, by definition, two polynomials are equal if and only if they have the same coefficients.
It would also be reasonable to say that a polynomial is a finite sequence. Though it is possible, it makes everything quite tedious. Indeed, in our definition, is a subset of
the set of sequences with values in
. On the other hand, the set of finite sequences is
Operations
How to add and multiply polynomials? Using standard notation, if we have
then we obtain the sum by adding the coefficients
and the product by doing the multiplication and expanding
This is why it makes sense to define the sum and product of polynomials as follows.
Consider two polynomials , with coefficients respectively
and
.
- We define the sum
as the polynomial
with
for all
.
- We define the product
as the polynomial
with
for all
.
Something implied in this definition is that the sum and products of polynomials are also polynomials, meaning the coefficients are for large enough indices. This is easy to check: in the notation of Definition I.2, we have
for
, and
for
.
A few sanity checks are de rigueur. For instance, we naturally define a constant polynomial to be one of the form for some
, and write merely
. Then multiplying a polynomial by a constant (polynomial) does exactly was one would expect.
- Check precisely that if
is a constant polynomial and
has coefficients
, then
has coefficients
- Check also that if
and
has coefficients
, then
has coefficients
Degrees also behave in a nice way, where we recall that . Naturally, we make the convention that for any
(which can be a natural number or
), we have
For any polynomials , we have
.
Moreover, the first inequality is an equality except if and
have the same degree and their leading coefficients are opposite of each other.
Show Proposition I.3, making sure to consider all possible cases.
The indeterminate
This is all nice and dandy, but it seems quite cumbersome to be dealing with sequences, when we really want to see a sum of powers of . But what would
be? In the previous definition, it should be the sequence
, as hinted at in Exercise I.1. As we start from sequences, not
, let us go the other route and do the following definition.
We define to be the polynomial with coefficients
. It is called the indeterminate.
Formally, we really define . It is traditional to write a capital
as opposed to a lowercase one. This is really made to say that
is not a variable, but an entity of its own. We could replace it by some value, but we do not want to see the polynomial as a function that (for instance) takes real numbers to real numbers. It is much more convenient to keep things formal.
The lovely thing about the indeterminate is that it allows to eschew sequences completely. Indeed, let us compute the coefficients of
. By definition
and then
and so on. We therefore see that . In general, we have the following expected result.
Let with coefficient
and degree
. Then
Naturally, by convention, we let .
- Check that, for any
,
has coefficients
, where
for
, and
.
- Show Theorem I.5. You can use Exercise I.1.
We are henceforth perfectly legitimized to totally disregard sequences, and write any polynomial in the form
. Note however that we do not imply that
, i.e. that
has degree
, but merely that
has degree at most
.
Euclidean division
Euclidean division for integers is classical, and this often done by long division. The same goes for polynomials. Let us try to divide by
.
- Put as many
as possible in
: there are
, and it remains
.
- Put as many
as possible in
: there are
, and it remains
.
- Put as many
as possible in
: there are
, and it remains
.
- As we cannot put any
in
, we are done, and we conclude that
We see that we stop because the degree of the polynomial obtained is strictly smaller than the degree of .
- Do the Euclidean division of
by
.
- Do the Euclidean division of
by
.
- Do the Euclidean division of
by
.
- Do the Euclidean division of
by
and by
This algorithm can be generalized to any polynomials, as summarized in the following result. The formal proof is merely writing down the algorithm precisely, which is quite tedious.
Let with
. Then then there exists two polynomials
(the quotient) and
(the rest), with
, such that
.
Moreover, such and
are unique.
The uniqueness does not follow from the algorithm, but is easier.
- Show that if
and
, then
or
is
.
- Show that the polynomials
of Theorem II.1 are unique: if
are such that
with
and
, then
and
.
Roots
Evaluation
According to our previous motivation and definitions, a polynomial is not a function. However, it can act as a function, still in the way that we would expect.
Consider a polynomial . Then for any
, the evaluation of
at
, denoted
, is the real number
Therefore, a (real) polynomial can be seen as a function from to
. In view of this definition, it is also natural to write indifferently
and
(with a capital
, the indeterminate). This is not an evaluation, as
is not a number, and we merely define
. But it is very convenient, and allows to write things such as the composition of polynomials: if
and
, then we can define the polynomial
There is a subtle thing to notice here. It is obvious that , because we just defined
to be the same as
. However, it does not tell that for any
, we have
. Mark the difference: on the left-hand side, we first multiply the polynomials, then evaluate; on the right hand side, we first evaluate both polynomials at
, then multiply these two real numbers. But then is it true? Let us check: write
and
. Then
But we recognize the coefficients of . Indeed we have by definition of the product of polynomials,
Therefore, by definition of the evaluation,
and we finally recognize that
Similarly, and more easily, we get that for all ,
.
Roots
A root (or a zero) of a polynomial is a number
such that
.
Note that the zero in is the zero of real numbers, not the zero polynomial.
It is in general hard, or even impossible, to obtain explicit formulas for roots. We all know the quadratic formula, but that is pretty much it.
The existence of roots may depend on where we look for them. The polynomial has no root in
but has two roots in
, namely
. For this introductory post, if we talk about roots, we always mean real numbers.
Factorization
Zeros of polynomials are pretty cool, for numerous reasons, but one of the main ones is that they allow to factorize.
The polynomial has a root
if and only if there exists a polynomial
, such that
In this case, is unique, and
.
One direction is simple: if such a exists, then
. Now, assume that
is a root of
and do the Euclidean division of
by
. Then exists
such that
and
. As
has degree 1, this means that
has degree
or
, i.e.
is a constant. However, evaluating at
gives
But since
is a root of
,
, and thus
. But
is constant, so this means
, and finally
. The uniqueness is from the Euclidean division, and the statement about the degree is just from Proposition I.3.
The process can be repeated on : if it has a root
, then for some
, we have
, and thus
. Continuing, we see that we can write
as
where has no roots. The values
are all the roots of
. Note however that some of them could be identical. Grouping the same roots together, we get the following.
Consider the distinct roots of a polynomial
. Then there exists unique integers
and a unique
with no roots such that
The integer is called the multiplicity of
. A root of multiplicity 1 is called a simple root; a root of multiplicity 2 is called a double root, etc.
Note as well that once we have a root (or several), finding the other factor (or
) can be done by Euclidean division. If we have several roots
, the same holds, though we need to expand the product
first.
Consider the polynomial . Find two “obvious” roots and factorize
. Argue that we cannot factorize further (unless we use complex numbers).
Irreducibility
Consider the polynomial . It has clearly no real roots. However, it is easy to check that
In short having no roots is not the same as not being factorizable. This is true for polynomials of degree two though: if they can be factored, both factor have degree 1, and thus they have a root. In the example above, the two degree 2 factors have no roots (since does not), and they are therefore not factorizable. A polynomial that cannot be factorized (except by a constant) is called irreducible.
We have just argued that polynomials of degree 2 are irreducible if and only if they have no roots, i.e. if and only if the discriminant is strictly negative. Are there other ones? It turns out that no, these are the only ones. Seeing this however requires complex numbers and the fundamental theorem of algebra, so we shall not talk about this for now.
Developing and factorizing
Polynomial from its roots
When we count the roots of a polynomial, we often count them with multiplicity, so for instance, a double root is counted twice. Consider a polynomial of degree
which has roots
, each written the number of time of its multiplicity. According to Corollary 4, it can be factored as
where has degree
, i.e. it is a constant. Therefore, if we know
roots of a polynomial, we know it totally, up to a constant: for some
, we have
We can obtain for instance if we know a coefficient of
: expand the right-hand side, and take
to match the coefficients.
Assume that . What is
in terms of
? In terms of
? In terms of
? In terms of
? For convenience, you can assume that all quantities involved are non-zero.
The polynomial has roots
. Factor it as above.
What can we say about two polynomials of degree at most and which have the same
roots (counted with multiplicity)?
Uniqueness
As before, from Corollary III.4, we can factorize a polynomial of degree once for each of its roots. In particular, a polynomial of degree
cannot have for than
roots. This implies the following very important result.
- A non-zero polynomial of degree
has at most
roots (counted with multiplicity).
- A polynomial of degree
with more than
roots is zero.
- In particular, a polynomial with infinitely many roots is zero.
Applying this to the difference of two polynomials gives the following.
- If two polynomials of degree at most
take the same values at
different points, then they are equal.
- In particular, two polynomials which are equal at infinitely many points are equal.
What can we say about a polynomial such that ? Give a direct proof, and a proof with Corollary IV.2.
Consider a polynomial of degree
such that, for all
we have
.
- How many polynomial at most can satisfy this assumption?
- Compute
. You may want to consider
.
Bonus: derivative
For a polynomial
it is natural to define its derivative as
The following exercises deal with the properties of the derivative. Beware: there is no calculus here! It is all formal definitions, so this is all that you can use.
Check the usual derivative formulas, as follows.
- For
,
.
- For
and
,
,
.
- For
,
.
Check the chain rule, as follows.
- For
,
, and
,
. (Hint:
.)
- For
and
,
.
Take and let
.
- Show that
is a root of
of multiplicity at least 2 if and only if
.
- Show that
is a root of
of multiplicity exactly
if and only if
is a root of multiplicity exactly
of
.
- Show that
is a root of
of multiplicity exactly
if and only if
,
but
.