The Chain Rule for Multivariable Vector-Valued Functions .... ....

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SUMMARY

The discussion centers on understanding Theorem 12.7 from Tom M. Apostol's "Mathematical Analysis" (Second Edition), specifically in Chapter 12: Multivariable Differential Calculus, Section 12.9. Theorem 12.7 involves the chain rule for multivariable vector-valued functions, with a focus on the equations presented in (16) and (17). Participants clarify that the definition of \(E(y)\) is crucial for deriving Equation (16) from the initial equation, and they confirm that \(E(0) = 0\) is a formal definition necessary for the theorem's proof.

PREREQUISITES
  • Understanding of multivariable calculus concepts, particularly the chain rule.
  • Familiarity with the notation and definitions used in differential calculus.
  • Knowledge of the total derivative as discussed in Apostol's work.
  • Ability to manipulate and interpret mathematical equations and proofs.
NEXT STEPS
  • Study the proof of Theorem 12.7 in Apostol's "Mathematical Analysis" (Second Edition).
  • Learn about the total derivative and its applications in multivariable calculus.
  • Explore the implications of the chain rule in vector-valued functions.
  • Review examples of applying the chain rule to complex functions in multivariable calculus.
USEFUL FOR

Students of mathematics, particularly those studying multivariable calculus, educators teaching differential calculus, and researchers needing a solid understanding of the chain rule for vector-valued functions.

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I am reading Tom M Apostol's book "Mathematical Analysis" (Second Edition) ...I am focused on Chapter 12: Multivariable Differential Calculus ... and in particular on Section 12.9: The Chain Rule ... ...I need help in order to fully understand Theorem 12.7, Section 12.9 ...Theorem 12.7 (including its proof) reads as follows:
View attachment 8523
View attachment 8524
In the proof of Theorem 12.7 we read the following:

" ... ... Using (14) in (15) we find$$f(b+v) - f(b) = f'(b) [ g'(a) (y) ] + f'(b) [ \| y \| E_a(y) ] + \|v \| E_b(v) $$$$= f'(b) [ g'(a) (y) ] + \| y \| E(y)$$ ... ... ... (16)Where $$E(0) = 0$$ and $$E(y) = f'(b) [ E_a(y) ] + \frac{ \| v \| }{ \| y \| } E_b (v) \ \ \ \ \text{ if } y\neq 0$$ ... ... ... (17)... ... ... "

My questions are as follows:Question 1

Can someone show how Equation (16) follows ... that is ...

... how exactly does $$f(b+v) - f(b) = f'(b) [ g'(a) (y) ] + \| y \| E(y)$$

follow from

$$f(b+v) - f(b) = f'(b) [ g'(a) (y) ] + f'(b) [ \| y \| E_a(y) ] + \|v \| E_b(v)$$?

Question 2

What is $$E(0)$$ ... I know what $$E_a$$ and $$E_b$$ are ... but what is $$E$$?

Similarly ... what is $$E(y)$$ in (16) and in (17) ... shouldn't it be $$E_a(y)$$ ... ?

Further ... why (formally and rigorously) does $$E(0) = 0$$
Question 3

Can someone please demonstrate how/why

$$E(y) = f'(b) [ E_a(y) ] + \frac{ \| v \| }{ \| y \| } E_b (v)$$
Help will be appreciated ...

Peter

=========================================================================================

It may help MHB readers of the above post to have access to Apostol's section on the Total Derivative ... so I am providing the same ... as follows:
View attachment 8525
View attachment 8526
Hope that helps ...

Peter
 

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Peter said:
In the proof of Theorem 12.7 we read the following:

" ... ... Using (14) in (15) we find$$f(b+v) - f(b) = f'(b) [ g'(a) (y) ] + f'(b) [ \| y \| E_a(y) ] + \|v \| E_b(v) $$$$= f'(b) [ g'(a) (y) ] + \| y \| E(y)$$ ... ... ... (16)Where $$E(0) = 0$$ and $$E(y) = f'(b) [ E_a(y) ] + \frac{ \| v \| }{ \| y \| } E_b (v) \ \ \ \ \text{ if } y\neq 0$$ ... ... ... (17)... ... ... "

My questions are as follows:Question 1

Can someone show how Equation (16) follows ... that is ...

... how exactly does $$f(b+v) - f(b) = f'(b) [ g'(a) (y) ] + \| y \| E(y)$$

follow from

$$f(b+v) - f(b) = f'(b) [ g'(a) (y) ] + f'(b) [ \| y \| E_a(y) ] + \|v \| E_b(v)$$?

Question 2

What is $$E(0)$$ ... I know what $$E_a$$ and $$E_b$$ are ... but what is $$E$$?

Similarly ... what is $$E(y)$$ in (16) and in (17) ... shouldn't it be $$E_a(y)$$ ... ?

Further ... why (formally and rigorously) does $$E(0) = 0$$
Question 3

Can someone please demonstrate how/why

$$E(y) = f'(b) [ E_a(y) ] + \frac{ \| v \| }{ \| y \| } E_b (v)$$
The answer to all three of those questions is that the equations in (17) are meant to be the definition of $E(y)$. In other words, if you define \[E(y) = \begin{cases}0&\text{if }y=0,\\ f'(b) [ E_a(y) ] + \frac{ \| v \| }{ \| y \| } E_b (v)&\text{if }y\ne0,\end{cases}\] then the second line of (16) follows immediately from the first line.
 
Opalg said:
The answer to all three of those questions is that the equations in (17) are meant to be the definition of $E(y)$. In other words, if you define \[E(y) = \begin{cases}0&\text{if }y=0,\\ f'(b) [ E_a(y) ] + \frac{ \| v \| }{ \| y \| } E_b (v)&\text{if }y\ne0,\end{cases}\] then the second line of (16) follows immediately from the first line.
Thanks Opalg ...

Indeed ... you are right, of course!

Should have seen that ...

Peter
 

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