Smooth Structures .... Dundas, Example 2.2.6 .... ....

In summary: This gives us:x^{1,1}(x^{0,0})^{-1}(p)=(\sqrt{1-|p|^2},\widehat{p_1},...,p_n)which is exactly what we were trying to show.Now, to answer your question on why this is a smooth map, we can use the definition of a smooth map between two manifolds. A map is smooth if it is smooth in local coordinates. In this case, we can see that both x^{1,1} and (x^{0,0})^{-1} are smooth maps in local coordinates. Therefore, the composition of these two maps is also smooth.In summary
  • #1
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I am reading Bjorn Ian Dundas' book: "A Short Course in Differential Topology" ...

I am focused on Chapter 2: Smooth Manifolds ... ...

I need help in order to fully understand Example 2.2.6 ... ... Example 2.2.6 reads as follows:
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My questions are as follows:
Question 1

In the above text from Bjorn Dundas we read the following:

" ... ... First we calculate the inverse of \(\displaystyle x^{ 0,0 }\) : Let \(\displaystyle p = ( p_1, \ ... \ ... \ p_n )\) be a point in the open disk \(\displaystyle E^n\), then \(\displaystyle ( x^{ 0,0 } )^{ -1 } (p) = ( \sqrt{ 1 - \mid p \mid^2 } , p_1, \ ... \ ... \ p_n )\) ... ... "
Can someone please show the details of how Dundas gets

\(\displaystyle ( x^{ 0,0 } )^{ -1 } (p) = ( \sqrt{ 1 - \mid p \mid^2 } , p_1, \ ... \ ... \ p_n )\) ... ... ?Question 2

In the above text from Bjorn Dundas we read the following:

" ... ... Finally we get that if \(\displaystyle p \in x^{ 0,0 } (U)\) then

\(\displaystyle x^{ 1,1 } ( x^{ 0,0 } )^{ -1 } (p) = ( \sqrt{ 1 - \mid p \mid^2 } , \widehat{p_1} , \ ... \ ... \ p_n )\) ... ... "Can someone please show/explain the details of how Dundas gets

\(\displaystyle x^{ 1,1 } ( x^{ 0,0 } )^{ -1 } (p) = ( \sqrt{ 1 - \mid p \mid^2 } , \widehat{p_1} , \ ... \ ... \ p_n )\) ... ... "Further, why/how are we sure that this is a smooth map ...?Peter

==========================================================================================The above post refers to Bjorn Dundas' Example 2.1.5 ... so I am providing access to this example as follows:
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It may be very helpful to MHB readers of the above post to have access to the start of Dundas' Section on topological manifolds ... so I am providing the same as follows:
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View attachment 8658It may also be very helpful to MHB readers of the above post to have access to the start of Dundas' Section on smooth structures ... so I am providing the same as follows:

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Hope that helps ...

Peter
 

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  • #2

Hello Peter,

Thank you for reaching out for help with understanding Example 2.2.6 in Bjorn Dundas' book on Differential Topology. I will do my best to explain the details and provide further clarification on your questions.

First, let's review the definition of a smooth manifold. A smooth manifold is a topological space that is locally homeomorphic to Euclidean space. In other words, for each point on the manifold, there exists a neighborhood that can be mapped smoothly to a corresponding neighborhood in Euclidean space. Now, let's dive into the details of Example 2.2.6.

Question 1:

In order to find the inverse of x^{0,0}, we start by considering a point p=(p_1,...,p_n) in the open disk E^n. This point can also be written as p=(0,p_1,...,p_n) since the first coordinate is always 0 in the open disk. Now, we need to find the inverse of x^{0,0} at this point p.

Recall that x^{0,0} is defined as x^{0,0}(p_1,...,p_n)=(0,p_1,...,p_n). So the inverse of this map will take a point (0,p_1,...,p_n) and map it back to (p_1,...,p_n). In other words, it will remove the first coordinate of the point and give us the remaining coordinates.

Using this information, we can see that (x^{0,0})^{-1}(p)=(\sqrt{1-|p|^2},p_1,...,p_n). This is because the first coordinate of p is always 0 in the open disk, so we can simply replace it with \sqrt{1-|p|^2} to get the inverse.

Question 2:

Now, let's consider the map x^{1,1}. This map takes a point (p_1,...,p_n) and maps it to (\sqrt{1-|p|^2},\widehat{p_1},...,p_n). Here, \widehat{p_1} represents the unit vector in the direction of p_1.

To get the composition x^{1,1}(x^{0,0})^{-1}(p), we simply plug in the inverse of x^{0,0} that we found in Question
 

1. What is a "Smooth Structure" in mathematics?

A smooth structure, also known as a smooth atlas or differentiable structure, is a set of coordinate charts on a manifold (a mathematical space that locally resembles Euclidean space) that are compatible with each other. This means that any two charts overlap smoothly, allowing for a consistent way to define differentiable functions on the manifold.

2. What is the significance of Example 2.2.6 in Dundas' work?

Example 2.2.6 is an example of a non-smooth structure on a manifold. It demonstrates that not all sets of coordinate charts can form a smooth structure, as there are certain conditions that must be met for a smooth structure to exist. This example helps to illustrate the importance of smooth structures in understanding and studying manifolds.

3. How is a smooth structure different from a topological structure?

A smooth structure is a more specialized type of structure than a topological structure. While a topological structure only requires sets and their open subsets, a smooth structure requires additional structure in the form of coordinate charts and smooth transition functions between them. In other words, smooth structures provide a more precise way to define differentiable functions on a manifold.

4. Can a manifold have multiple smooth structures?

Yes, it is possible for a manifold to have multiple smooth structures. This is known as a non-unique smooth structure and is a subject of study in differential topology. In fact, there are infinitely many smooth structures that can be defined on a given manifold, making it a rich area of research in mathematics.

5. What are some real-world applications of smooth structures?

Smooth structures have many practical applications in fields such as physics and engineering. They are essential for understanding smooth surfaces and curves, as well as for modeling and analyzing physical systems that involve continuous changes. Some examples of real-world applications include fluid dynamics, computer graphics, and robotics.

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