A function is conformal at if it preserves the angle (with orientation) between any two smooth curves intersecting at .
If curves cross at at angle (measured from to counterclockwise), their images cross at at the same angle — direction and orientation both.
Theorem (analytic ⇒ conformal)
If is analytic at and , then is conformal at .
Why
Near , by Taylor’s theorem, . The map is multiplication by the complex constant . Multiplication by a complex number is a uniform rotation by and scaling by — applied uniformly to every direction.
Rotations preserve angles; uniform scaling preserves angles. So infinitesimally, acts like a rigid rotation-and-scaling, which is angle-preserving.
The condition is essential. If , the linear term vanishes. Expand around in a Taylor series:
where is the order of the lowest-order nonvanishing term (i.e., but ). Near , the dominant behavior is — which raises angles to the -th power, i.e., multiplies them by .
The point is then a critical point of , and conformality fails there.
Example: . At , and , so . Curves through the origin have their crossing angles doubled under squaring.
Conjugation is anti-conformal
preserves the magnitude of angles but reverses orientation — a reflection. So conjugation is anti-conformal: angle-preserving up to a flip.
This is the cleanest geometric statement of why is not analytic. Real-analytic-but-orientation-reversing maps fail the “rotation-and-scaling” character that complex differentiability demands.
Application: orthogonal coordinate systems
If is analytic, the level curves of and the level curves of are mutually orthogonal.
Proof. and . By Cauchy-Riemann equations and ,
Gradients are perpendicular, so the level curves they define are perpendicular.
Example. , so (level curves: hyperbolas with - and -axes as asymptotes) and (level curves: hyperbolas with as asymptotes). These two families intersect at right angles — the curvilinear coordinate grid generated by squaring.
Why conformal maps matter in physics and engineering
Laplace’s equation is preserved by conformal maps. If is harmonic and is conformal, then is harmonic in the image domain.
So you can solve Laplace problems by conformal transformation:
- Find an analytic mapping your “hard” region (complicated boundary) to an “easy” region (disk, half-plane).
- Solve Laplace’s equation with the transformed boundary conditions on the easy region.
- Pull back to the original region via the inverse map.
This was the central technique of 19th-century electrostatics and fluid mechanics. The Smith chart in transmission-line theory is a working example: the Möbius map conformally maps the right half-plane to the unit disk, and properties of impedance in the right half-plane translate to properties of reflection coefficient on the chart.
The Riemann mapping theorem
The deepest result: any simply connected proper open subset of can be mapped conformally onto the unit disk. So in principle, almost any 2D Laplace problem can be transformed to a disk problem. The practical issue is finding the explicit map — Möbius transformations and a few standard families handle the most useful cases.