What is the square root of ? Whatever the quantity
means, we want to denote
, and then discuss calculations involving the set
of complex numbers, whose calculations are extended by usual algebraic techniques.
But having developed many ideas in linear algebra, let’s use some of them to properly define the complex numbers. Intuitively, we want to think of as a
-counterclockwise rotation. Furthermore, we want this transformation to be linear.
Let be a field. Not only will we develop the usual complex numbers, but we can define the complex numbers for basically any field we wish. Recall that
as a subspace. This will be our starting point, and we will identify
We want the basis vector to be transformed to
, and the basis vector
to be transformed to
. Hence, our matrix that represents the rotation
will be as follows:
Definition 1. .
The complex numbers over is then defined by
We abbreviate for the usual complex numbers. Under this definition, rather remarkably, we recover the usual definitions and intuitions for the square root of
:
Lemma 1. .
Proof. By the definition of ,
Therefore, if there are no other elements such that
, we define
by convention.
Interestingly, by this definition, can be defined from just the rational numbers
, since
is an ordered field
(in which for any
,
so that
).
If we limit ourselves a little more, as long as is an ordered ring, we can define
just as well. This is in fact the definition of the Gaussian integers, which we spell out more explicitly since
is not a field:
Definition 2. The set of Gaussian integers is defined by
By definition, forms a vector space over
, since it is a subspace of
.
Lemma 2. and
.
This result means that addition in works just like addition in
. What about multiplication?
Lemma 3. Multiplication in is closed, associative and commutative. Furthermore,
is a multiplicative identity.
Proof. We can easily verify that as the multiplicative identity. For the closure of multiplication, we observe that for
, matrix multiplication yields
This computation also establishes that complex number multiplication is commutative. Associativity follows from the associativity of matrix multiplication.
In fact, we get something even more than a vector space: If is an ordered field like
or
, then
forms a field, so that
as a sub-field.
Lemma 4. If is an ordered field, then
forms an abelian group under multiplication. Furthermore, multiplication is distributive over addition.
Proof. By Lemma 3, we just need to check that every nonzero complex number has an inverse. To that end, we need to find a complex number
such that
We leave it as an exercise to verify that and
yield the desired complex number, which is well-defined since
in an ordered field, so that
Distributivity of multiplication over addition in the complex numbers follows from the linearity property
Finally, once we have completed our verifications, we have the canonical chain of number systems:
Theorem 1. We have the canonical chain of number systems:
with arithmetic being preserved at each step, except for order.
Interestingly, however, we cannot order like how we usually order
.
Theorem 2. Suppose there exists a total order on
. Then
is not the usual total order on
.
Proof. Suppose that is the usual total order on
. Since
is a total order, either
or
. Suppose
for vibes. By the transitivity of
,
. Hence, multiplying by
yields
Since is antisymmetric, we must have
, a contradiction.
We’ll conclude by mentioning some other strange number systems. The dual numbers are defined by , where
but
. The split-complex numbers are defined by
, where
but
. These definitions may seem absurd until we define
The desired properties are then obtained by an exercise in matrix multiplication.
—Joel Kindiak, 2 Mar 25, 2308H
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