Simple Surfaces, Coordinate Mapping
Definition 1 1
Let’s consider subsets of a -dimensional Euclidean space with coordinates , to be open sets. If there exists a injective function that satisfies the following for all , it is called a Simple Surface.
Explanation
In the definition, the open set is drawn from the -dimensional space, and it’s mapped into the -dimensional space without overlapping parts (since it’s injective), whether it’s flat or curved. In that sense, a simple surface can be imagined as smoothly connecting flat pieces of dimensions within the -dimensional space. It’s best to grasp the geometric definition of this surface as a function, but don’t worry if it doesn’t come to mind right away; just spend time getting familiar with it.
The reason for defining a surface as a mapping from 2-dimensional space to 3-dimensional space is to treat the surface as if it’s locally like a plane. For example, although the Earth is close in shape to a sphere, we experience its surface as if it’s a 2-dimensional plane from above. can be likened to a world map, and to a globe.
Meanwhile, the mathematical condition given in the definition is similar to the condition a regular curve must meet, as in . Intuitively, this means we’re immediately excluding any parts that are pointy or bizarrely twisted. Satisfying means that any directional partial derivative is not singular (not ), implying in some sense that we’re considering the geometry using two linearly independent (curve) axes.
If the simple surface is explicitly presented with coordinates and a graph, it’s also called a Monge Patch. For instance, if the simple surface is , its graph is and can be referred to as a Monge Patch.
Definition 2 2
Let’s consider subsets of a -dimensional Euclidean space with coordinates , to be open sets. If the mapping is bijective and regular, then is called a coordinate patch.
Explanation 3
For to be regular means that the rank of the Jacobian matrix of is the same as . If we say , the Jacobian matrix of is as follows.
The rank of this matrix being means that the dimension of its column space is , implying and are linearly independent. Therefore, their cross product is not .
Thus, we can see that the two definitions are equivalent.