Complex Mapping - Is transforming boundaries enough?

In summary: This is not a trivial question.In summary, when transforming a region with boundary C in the z plane to the w plane, it is not always the case that R will be inside the transformed boundaries. This is because the inside-outside relationship depends on the continuity of the mapping and the concept of inside, which is not always clear. A counterexample is given where R is mapped to the outside of C. Therefore, it cannot be assumed that every point in R will be mapped to a point inside the transformed boundaries.
  • #1
davidbenari
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Say I will make the transformation from the ##z## plane to the ##w## plane. Moreover, I'll transform a region ##R## with boundary ##C## in the ##z## plane to something in the ##w## plane.

Why is it that if I know the equations for ##C## then I can transform these and immediately know that ##R## will be inside the transformed boundaries? Why isn't it the case that some point in ##R## maps into some point not inside ##C'## (which is my transformed boundary)?

Thanks.
 
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  • #2
You have to say something about the transformation. Normally, you are using linear, or at least continuous mappings which by definition will preserve this inside-outside relationship.
 
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  • #3
According to what you say I think continuous mappings would be what I'm dealing with. Strangely I didn't think of continuity, which makes this more intuitive, but not obvious to me.

I see that every point in the neighborhood of ##z_o## in ##R## will also be mapped in ##R'## as a simple closed region. I guess I can visualize these small neighborhoods expanding until they reach the transformed contour...

Is this the argument?

I was told this was because analytic transformations are "open maps" is this what they mean by it?
 
  • #4
davidbenari said:
Say I will make the transformation from the ##z## plane to the ##w## plane. Moreover, I'll transform a region ##R## with boundary ##C## in the ##z## plane to something in the ##w## plane.

Why is it that if I know the equations for ##C## then I can transform these and immediately know that ##R## will be inside the transformed boundaries? Why isn't it the case that some point in ##R## maps into some point not inside ##C'## (which is my transformed boundary)?

Thanks.
Counterexample: Let [itex] C= (z:\lvert z \lvert = 1)[/itex], then [itex]R= (z:\lvert z \lvert < 1) [/itex]. Now transform this using [itex] w=\frac{1}{z}[/itex]. This maps C onto C, but R is mapped to the outside of C.
 
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  • #5
Svein, but if the function ##w## is analytic in every point in ##R## then what I say will hold right?
 
  • #6
davidbenari said:
Svein, but if the function ww is analytic in every point in RR then what I say will hold right?
Sorry, I do not know. I checked out Ahlfors, and he carefully does not make that statement. It depends very much on C and the concept of inside.
 
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Related to Complex Mapping - Is transforming boundaries enough?

1. What is complex mapping?

Complex mapping is a process of transforming boundaries between different coordinate systems, such as converting latitude and longitude coordinates to a Cartesian coordinate system.

2. Why is complex mapping important?

Complex mapping is important because it allows scientists and researchers to accurately represent and analyze data from different coordinate systems, making it easier to compare and combine information from different sources.

3. Is transforming boundaries enough in complex mapping?

No, transforming boundaries is only one aspect of complex mapping. In addition to transforming boundaries, complex mapping involves taking into account other factors such as projection, scale, and datum to accurately represent spatial data.

4. What are some challenges of complex mapping?

Some challenges of complex mapping include selecting the appropriate coordinate system, dealing with data in different projections and scales, and accounting for errors in spatial data.

5. How can complex mapping benefit society?

Complex mapping can benefit society by providing more accurate and comprehensive spatial data, which can help in decision-making processes for a variety of fields such as urban planning, disaster management, and environmental conservation.

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