Differentiation of Vector Valued Functions - Browder, Proposition 8.12 ....

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SUMMARY

The discussion centers on proving Proposition 8.12 from Andrew Browder's "Mathematical Analysis: An Introduction," specifically in Chapter 8, Section 8.2, which deals with differentiable maps. The proposition involves vector-valued functions and their derivatives, with a focus on constructing the derivative matrix. A practical example is provided using the function \(\vec{f}(x, y) = \begin{pmatrix} x^2y \\ e^x \sin(y) \end{pmatrix}\) to illustrate the computation of partial derivatives and the formation of the derivative matrix.

PREREQUISITES
  • Understanding of vector-valued functions
  • Knowledge of partial derivatives
  • Familiarity with matrix representation of derivatives
  • Basic concepts of differentiability in multivariable calculus
NEXT STEPS
  • Study the proof of Proposition 8.12 in Browder's "Mathematical Analysis: An Introduction"
  • Learn about the properties of differentiable maps in multivariable calculus
  • Explore examples of vector-valued functions and their derivatives
  • Investigate the application of the derivative matrix in optimization problems
USEFUL FOR

Students of mathematical analysis, particularly those focusing on multivariable calculus, as well as educators and researchers interested in the differentiation of vector-valued functions.

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I am reading Andrew Browder's book: "Mathematical Analysis: An Introduction" ... ...

I am currently reading Chapter 8: Differentiable Maps and am specifically focused on Section 8.2 Differentials ...

I need help in proving Proposition 8.12 ... ...

Proposition 8.12 and the definitions, remarks and propositions leading up to it read as follows:
View attachment 7467
https://www.physicsforums.com/attachments/7468Although Browder states that Proposition 8.12 is easy to prove I am unable to make an effective start on the proof ...

Can someone please demonstrate how Proposition 8.12 is proved ...

[Note that I am unsure about the definition ... and the nature ... of the $$f'_i (p)$$ ... ... ]

Help will be much appreciated ...

Peter
 
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When you are "not sure" about definitions, look at simple examples. Start with a two dimensional case, say [math]\vec{f}(x, y)= \begin{pmatrix} f_1(x, y) \\ f_2(x, y)\end{pmatrix}= \begin{pmatrix}x^2y \\ e^x sin(y)\end{pmatrix}[/math].

The "rows" referred to are [math]\begin{pmatrix}\frac{\partial f_1}{\partial x} & \frac{\partial f_1}{\partial y}\end{pmatrix}= \begin{pmatrix}2xy & x^2\end{pmatrix}[/math] and [math]\begin{pmatrix}\frac{\partial f_2}{\partial x} & \frac{\partial f_2}{\partial y}\end{pmatrix}= \begin{pmatrix} e^x sin(y) & e^x cos(y)\end{pmatrix}[/math] so that the 2 by 2 "derivative matrix" is
[math]\begin{pmatrix}\frac{\partial f_1}{\partial x} & \frac{\partial f_1}{\partial y} \\ \frac{\partial f_2}{\partial x} & \frac{\partial f_2}{\partial y}\end{pmatrix}= \begin{pmatrix} 2xy & x^2 \\ e^x sin(y) & e^x cos(y)\end{pmatrix}[/math]
 

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