Since the complex numbers
are nothing but
with a multiplicative structure, the notion of open sets carries over from
to
. Hence, we consider a set
open if and only if
is open as a subset of
(that is, around each point
there exists a ball around
completely contained within
) w.r.t. Euclidean norm (or any other norm, due to norm equivalence).
Recall that a function
is differentiable at
iff the limit

exists, and in this case the derivative
is defined as the value of that limit. By analogy, we infer the analogous definition for functions
:
The derivative is linear in the following sense:
Since a complex number is a tuple
in
, a map
is tantamount to a map
. The complex differentiability of
at a certain point implies its real differentiability, in the sense that the directional derivatives exist. In fact, we will later prove that in case of holomorphy, even continuous differentiability of
(in the sense of existence of partial derivatives) will follow, and hence, we have a Jacobian matrix which equals the differential of
. However, the converse is not true: If
in the sense of real numbers (that is, considering
as a map
: All partial derivatives exist and are continuous), we don't know yet whether
is holomorphic or not. The next section will make that precise.
If
in the real sense, then there is a precise criterion for when
is complex differentiable. This is given by the Cauchy–Riemann equations:
Theorem 2.3:
Let
be continuously differentiable at
, that is, all partial derivatives exist and are continuous, both at
. Then
as a function
is complex differentiable in
if and only if the Cauchy–Riemann equations, given by
and
,
are satisfied, where
.
Proof:
For the whole proof, note that if
, then
for
.
If
is continuously differentiable in
, then
,
,
where
means
. Thus, in this case,
![{\displaystyle {\begin{aligned}{\frac {f(z_{0}+h)-f(z_{0})}{h}}&={\frac {J_{f}(z_{0})h+r(h)}{h}}\\&={\frac {h_{1}-ih_{2}}{|h|^{2}}}J_{f}(z_{0})h+{\frac {r(h)}{h}}\\&={\frac {h_{1}-ih_{2}}{\|h\|^{2}}}{\begin{pmatrix}\partial _{x}f_{1}&\partial _{y}f_{1}\\\partial _{x}f_{2}&\partial _{y}f_{2}\end{pmatrix}}{\begin{pmatrix}h_{1}\\h_{2}\end{pmatrix}}+{\frac {r(h)}{h}}\\&={\frac {h_{1}(h_{1}\partial _{x}f_{1}+h_{2}\partial _{y}f_{1})+h_{2}(h_{1}\partial _{x}f_{2}+h_{2}\partial _{y}f_{2})+i\left[h_{1}(h_{1}\partial _{x}f_{2}+h_{2}\partial _{y}f_{2})-h_{2}(h_{1}\partial _{x}f_{1}+h_{2}\partial _{y}f_{1})\right]}{\|h\|^{2}}}+{\frac {r(h)}{h}}.\end{aligned}}}](https://wikimedia.org/api/rest_v1/media/math/render/svg/29814814bf3b6135e87aaf459cbaed43cb069f76)
If the Cauchy–Riemann equations are satisfied, we may replace
by
and
by
in the latter expression and obtain

(whereby we also obtained another formula for the complex derivative). On the other hand, if the limit

does exist, then in particular we are free to choose
for real positive
to get

and similarly
for real, positive
to get

and hence the Cauchy–Riemann equations.
For the usual real derivative, there are several rules such as the product rule, the chain rule, the quotient rule and the inverse rule. Fortunately, these carry over verbatim to the complex derivative, and even the proofs remain the same (although we will repeat them for the sake of completeness).
Proof:
Set

Then

by the continuity of
at
(which can be easily proven by multiplying the limit definition of complex differentiability by
and observing that the limit is then
by multiplicativity of limits).
Proof:


Proof:
The derivative of the function
is given by
; for

Hence, product and chain rule imply


Proof:
Proof:

by the binomial theorem.
Due to the linearity of the complex derivative, we can now compute the complex derivative of any polynomial, even with complex coefficients:
.
- Compute the complex derivative of the polynomial
.