Multivariate calculus problem: Calculating the gradient vector

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Homework Help Overview

The discussion revolves around a multivariate calculus problem focused on calculating the gradient vector and applying the chain rule in the context of a vector function. Participants are exploring the implications of partial derivatives and the conditions for using the chain rule.

Discussion Character

  • Exploratory, Conceptual clarification, Mathematical reasoning, Assumption checking

Approaches and Questions Raised

  • Participants discuss the calculation of partial derivatives and the formation of the gradient vector. There are questions regarding the application of the chain rule and the interpretation of derivatives at specific intervals. Some participants express confusion about the conditions necessary for applying the chain rule.

Discussion Status

The discussion is active, with participants sharing their calculations and seeking clarification on the application of mathematical concepts. Some have provided partial solutions, while others are questioning assumptions and the rigor of definitions related to the problem.

Contextual Notes

There are mentions of textbook references and the need to verify conditions for using the chain rule, indicating that participants are working within the constraints of their course materials and possibly specific homework guidelines.

squenshl
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Homework Statement
Let ##U := \left\{(x,y)\in \mathbb{R}^2: xy\neq 0\right\}## and let ##f: U\mapsto \mathbb{R}## be defined by
$$f(x,y) := (\log_{e}{(|x|)})^2+(\log_{e}{(|y|)})^2.$$


1. Calculate ##\nabla f(x,y)## at each point of ##U##.

2. Let ##\mathbf{r}: (0,1)\mapsto \mathbb{R}^2## be defined by ##\mathbf{r}(t) := \left(e^{\sin{(t)}},e^{\cos{(t)}}\right).##
Calculate the derivative of ##\mathbf{r}## at each point of ##(0,1).##

3. Justify whether you can use the chain rule to calculate the derivative of ##f\circ \mathbf{r}.##
If it is justifiable, calculate the derivative of ##f\circ \mathbf{r}## using the chain rule.
Relevant Equations
None
1. We find the partial derivatives of ##f## with respect to ##x## and ##y## to get ##f_x = \frac{2\ln{(x)}}{x}## and ##f_y = \frac{2\ln{(y)}}{y}.## This makes the gradient vector
$$\nabla{f} = \begin{bmatrix}
f_x \\
f_y
\end{bmatrix} = \begin{bmatrix}
\frac{2\ln{(x)}}{x} \\
\frac{2\ln{(y)}}{y}
\end{bmatrix}.$$

2. We have
$$\mathbf{r}'(t) = \left(\cos{(t)}e^{\sin{(t)}},-\sin{(t)}e^{\cos{(t)}}\right).$$

After this I'm a little confused. Any help is appreciated.
 
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For (3), what does your version of the chain rule say?

If your multivariable calculus textbook is rigorous, it might also want you to show that ##U## is an open set (which is easily seen by a drawing).
 
The derivative of ##\mathbf{r}## at each point of ##(0,1)##?
 
squenshl said:
The derivative of ##\mathbf{r}## at each point of ##(0,1)##?
That confused me initially too. It would be clearer if it said "at each point in the open interval (0,1)."
 
Okay (1) and (2) are done.
So for (3), assuming ##t > 0##, ##f\circ \mathbf{r} = \ln{(e^{\sin{(t)}})}^2+\ln{(e^{\sin{(t)}})}^2 = \sin^2{(t)}+\cos^2{(t)} = 1## so the derivative is ##0##.
 
For #3, you need calculate the derivative using the chain rule if it can be applied.
 
Okay then I’m lost how do we then justify whether to use the chain rule?
 
I'm sure the conditions are stated in your textbook or were covered in lecture. Look them up.
 

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