Further Questions on Computations in Coordinates - Lee, Ch 3

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In summary, Lee discusses computations with tangent vectors and pushforwards in Chapter 3 of his book Introduction to Smooth Manifolds. He shows that the pushforwards of these vectors form a basis for T_p M.
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I am reading John M. Lee's book: Introduction to Smooth Manifolds ...

I am focused on Chapter 3: Tangent Vectors ...

I have some further questions concerning Lee's conversation on computations with tangent vectors and pushforwards ...

The relevant conversation in Lee is as follows:
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In the above text we read:

" ... ... we see that [itex]\phi_* \ : \ T_p M \longrightarrow T_{ \phi(p) } \mathbb{R}^n[/itex] is an isomorphism ... ... "

and then further ...

" ... ... [itex]T_{ \phi(p) } \mathbb{R}^n[/itex] has a basis consisting of all derivations [itex]\frac{ \partial }{ \partial x^i } |_{\phi(p)} \ , \ i = 1, \ ... \ ... , n[/itex]. Therefore the pushforwards of these vectors under [itex]( \phi^{-1} )_*[/itex] form a basis for [itex]T_p M[/itex] ... ... "Question 1

Is [itex]( \phi^{-1} )_*[/itex] the inverse of [itex]\phi_*[/itex] and hence the isomorphism from [itex]T_{ \phi(p) } \mathbb{R}^n[/itex] to the tangent space [itex]T_p M[/itex]?

Why isn't the inverse [itex]( \phi_* )^{-1}[/itex] ?Question 2

Since [itex]( \phi^{-1} )_* \ : \ T_{ \phi(p) } \mathbb{R}^n \longrightarrow T_p M [/itex] and we know that [itex]T_{ \phi(p) } \mathbb{R}^n[/itex] is a vector space ... then since [itex]( \phi^{-1} )_*[/itex] is an isomorphism ... then ... [itex]T_p M[/itex] is a vector space ... is that correct? ... ...

Hope someone can help ... ...

Peter
 

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  • #2
Math Amateur said:
Question 1

Is [itex]( \phi^{-1} )_*[/itex] the inverse of [itex]\phi_*[/itex] and hence the isomorphism from [itex]T_{ \phi(p) } \mathbb{R}^n[/itex] to the tangent space [itex]T_p M[/itex]?

Why isn't the inverse [itex]( \phi_* )^{-1}[/itex] ?

They are the same. But the point is that the inverse mapping gives you the inverse differential. This is just the Chain Rule.

Question 2

Since [itex]( \phi^{-1} )_* \ : \ T_{ \phi(p) } \mathbb{R}^n \longrightarrow T_p M [/itex] and we know that [itex]T_{ \phi(p) } \mathbb{R}^n[/itex] is a vector space ... then since [itex]( \phi^{-1} )_*[/itex] is an isomorphism ... then ... [itex]T_p M[/itex] is a vector space ... is that correct? ... ...

yes but you already know that it is a vector space. Otherwise what would isomorphism mean?
 
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  • #3
lavinia said:
They are the same. But the point is that the inverse mapping gives you the inverse differential. This is just the Chain Rule.
yes but you already know that it is a vector space. Otherwise what would isomorphism mean?
Thanks Lavinia ... Needed that confirmation For confidence in what I am doing ...

Thanks again ...

Peter
 

What is the main purpose of Chapter 3 in Lee's "Further Questions on Computations in Coordinates"?

The main purpose of Chapter 3 is to introduce the concept of computations in coordinates and provide a deeper understanding of how to perform calculations using coordinates.

What are some common types of computations that are performed in coordinates?

Some common types of computations in coordinates include finding the length of a vector, determining angles between vectors, and projecting one vector onto another.

How does the use of coordinates simplify complex calculations?

Using coordinates allows us to break down complex calculations into simpler components, making it easier to visualize and understand the problem at hand. It also allows us to use algebraic methods to solve problems instead of relying solely on geometric intuition.

What is the difference between Cartesian coordinates and polar coordinates?

Cartesian coordinates use two perpendicular axes (x and y) to represent a point in a two-dimensional plane, while polar coordinates use a distance from the origin and an angle to represent a point. Polar coordinates are often used for circular or rotational problems, while Cartesian coordinates are used for more general problems.

How can I improve my understanding of computations in coordinates?

To improve your understanding of computations in coordinates, it is important to practice solving problems and to always think about the geometric meaning behind the algebraic equations. It can also be helpful to visualize problems using graphs or diagrams to better understand the concepts.

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