Undergrad Tangent Spaces and Subspaces .... McInerney Theorem 3.3.13 ....

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SUMMARY

The discussion centers on proving that the Jacobian matrix associated with the function ##\phi## in Theorem 3.3.13 of Andrew McInerney's book, "First Steps in Differential Geometry," has a rank of ##n - 1##. Participants clarify that the Jacobian matrix, constructed from the functions ##f_1, f_2, \ldots, f_n##, is of size ##n \times (n-1)##, which inherently limits its rank to a maximum of ##n - 1##. Additionally, the first ##n - 1## rows of the matrix are linearly independent, confirming that the rank is indeed ##n - 1##.

PREREQUISITES
  • Understanding of Jacobian matrices in differential geometry
  • Familiarity with the concepts of rank and linear independence
  • Knowledge of Riemannian geometry as presented in McInerney's work
  • Basic proficiency in multivariable calculus
NEXT STEPS
  • Study the properties of Jacobian matrices in differential geometry
  • Learn about linear transformations and their ranks
  • Explore the implications of the McInerney Theorem 3.3.13 in various geometric contexts
  • Review examples of rank determination in multivariable functions
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Students and researchers in mathematics, particularly those focusing on differential geometry, Riemannian geometry, and advanced calculus. This discussion is beneficial for anyone looking to deepen their understanding of Jacobian matrices and their applications in geometric proofs.

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TL;DR
Thread involves finding the dimension of a tangent subspace ...
I am reading Andrew McInerney's book: First Steps in Differential Geometry: Riemannian, Contact, Symplectic ... and I am focused on Chapter 3: Advanced Calculus ... and in particular on Section 3.3: Geometric Sets and Subspaces of ##T_p ( \mathbb{R}^n )## ... ...

I need help with an aspect of the proof of Theorem 3.3.13 ... ...

Theorem 3.3.13 (together with a relevant definition) reads as follows:
McInerney - Defn 3.3.12 & Theorem 3.3.13 ... ... Page 1 ... .png

McInerney - 2 - Defn 3.3.12 & Theorem 3.3.13 ... ... Page 2 ... .png

In the above text from McInerney we read the following:

" ... ... The fact that ##\phi## has rank ##n -1## follows by computing the Jacobian matrix at any point in ##U## ... ... "Can someone please demonstrate rigorously, formally and explicitly that ##\phi## has rank ##n -1## ... ...My computations with respect to the Jacobian ##[D \phi(p) ]## were as follows:

We have ##\phi ( x_1, \ ... \ ... \ x_{n-1} ) = ( x_1, \ ... \ ... \ x_{n-1}, f( x_1, \ ... \ ... \ x_{n-1}) )##

Now put ...

##f_1( x_1, \ ... \ ... \ x_{n-1} ) = x_1##

##f_2( x_1, \ ... \ ... \ x_{n-1} ) = x_2##

... ... ...

... ... ...

##f_{n-1}( x_1, \ ... \ ... \ x_{n-1} ) = x_{n-1}##

##f_n( x_1, \ ... \ ... \ x_{n-1} ) = f( x_1, \ ... \ ... \ x_{n-1} )##Then ... the Jacobian ...##[D \phi(p) ] = \begin{bmatrix} \frac{ \partial f_1 }{ \partial x_1} & ... & ... & \frac{ \partial f_1 }{ \partial x_{n-1} } \\ ... & ... & ... & ... \\ ... & ... & ... & ... \\ \frac{ \partial f_{n-1} }{ \partial x_1} & ... & ... & \frac{ \partial f_{n-1} }{ \partial x_{n-1} } \\ \frac{ \partial f }{ \partial x_1} & ... & ... & \frac{ \partial f }{ \partial x_{n-1} } \end{bmatrix}####= \begin{bmatrix} 1 & 0 & 0 & ... & ... & 0 \\ 0 & 1 & 0 & ... & ... & 0 \\ ... & ... & ... & ... & ... & ... \\ ... & ... & ... & ... & ... & ... \\ \frac{ \partial f }{ \partial x_1} & ... & ... & ... & ... & \frac{ \partial f }{ \partial x_{n-1} } \end{bmatrix}##

... now ... how do we show that the rank of ##[D \phi(p) ]## is ##n-1## ...?

Hope someone can help ...

Peter
 
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Hi Peter,

if you write down a bit more of the Jacobi matrix, then it will be
##[D \phi(p) ] = \begin{bmatrix} 1 & 0 & 0 & ... & ... & 0 \\ 0 & 1 & 0 & ... & ... & 0 \\ ... & ... & ... & ... & ... & ... \\ ... & ... & ... & ... & 1 & 0 \\ ... & ... & ... & ... & 0 & 1 \\ \frac{ \partial f }{ \partial x_1} & ... & ... & ... & ... & \frac{ \partial f }{ \partial x_{n-1} } \end{bmatrix}##

We have a matrix of dimensions ##n## times ##n-1##, so the rank can at most be ##n-1## because we cannot have ##n## independent columns, if there are only ##n-1##. The rank is also at least ##n-1## since the first ##n-1## rows are linear independent.
 
Thanks fresh_42 ...

Appreciate your help ...

Peter
 
note also the matrix is that of a linear map from R^n-1 to R^n, hence the rank cannot be more than n-1.
 
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Thanks mathwonk ...

Peter
 

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