Understanding Derivatives of f(r) in Multiple Variables

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SUMMARY

The discussion focuses on computing derivatives of functions of multiple variables, specifically f(r(t)), f(r(u, v)), and their nested forms. The primary formula referenced is the chain rule for derivatives, expressed as \(\frac{df}{dt}=\frac{df}{d\vec{r}}\cdot \frac{d\vec{r}}{dt}\). The user seeks a more compact method for differentiating nested variables, suggesting that while partial derivatives are necessary, there may be alternative approaches to simplify the process. The conversation emphasizes the importance of understanding vector differentiation and the application of the chain rule in multi-variable calculus.

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Jhenrique
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I have some important questions and essentials for understand some theories. They are six:
given f(r(t)), f(r(u, v)), f(r(u(t), v(t))), f(r(t)), f(r(u, v)) and f(r(u(t), v(t))). How compute its derivatives wrt independent variables?

Unfortunately, I just know the answer for 1nd:
[tex]\frac{df}{dt}=\frac{df}{d\vec{r}}\cdot \frac{d\vec{r}}{dt}[/tex]
I don't know equate the other derivatives.
 
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Where you have more than one variable, you use partial derivatives.
When the variables are nested, just repeat the chain rule.
Recall how to differentiate a vector.
 
But I think that chain rule will expand to much. I think if exist another way more compact for these differentations... some so so like
##\frac{d^2f}{du dv}=\frac{d^2 f}{d\vec{r}^T d\vec{r}}\cdot \frac{d\vec{r}}{du}\times \frac{d\vec{r}}{dv}##
 

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