Multivariable Derivative Practice

In summary, the conversation is about multivariable calculus and the correctness of a vector function and its partial derivative. The participants also discuss an example involving Lagrangian mechanics and the derivative of a function with respect to theta. The final conclusion is to be more careful in calculations.
  • #1
malawi_glenn
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I am repeting some multivariable calculus.

I want to know if have done right now:

[tex]\mathbf{r} = \mathbf{r}(q_1, q_2, q_3)[/tex]

[tex] \dfrac{\partial \mathbf{r}}{\partial q_1} = \left(\dfrac{\partial r_1}{\partial q_1} , \dfrac{\partial r_2}{\partial q_1} , \dfrac{\partial r_3}{\partial q_1} \right) [/tex]

let

[tex] \mathbf{r} = (q_1 + 2q_3, q_2 + 3q_1 - q_3, q_1 - q_3) [/tex]

[tex] \dfrac{\partial \mathbf{r}}{\partial q_1} = (1,3,1) [/tex]
 
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  • #2
If I understand what your problem is correctly- that r is a three dimensional vector function of 3 variables, then, yes, your answer is correct.
 
  • #3
thanx dude!

How about this one?

[tex] \dfrac{d}{d\theta}\left( \dfrac{d\theta}{dt}\right) = 0 \text{ ?} [/tex]
 
  • #4
Yes. What about it? What is [itex]\theta[/itex]? And what is the question?
 
  • #5
theta is a function, and I am wondering if

[tex] \dfrac{d}{d\theta}\left( \dfrac{d\theta}{dt}\right) = 0 \text{ ?} [/tex]

Is correct in this case: i forgot to post the link.

http://en.wikipedia.org/wiki/Lagrangian_mechanics

I am trying to figure out what is happening in "Pendulum on a movable support"
 
  • #6
According to information presented in the link
you are right
[tex] \dfrac{d\theta}{dt} [/tex] is only function of t so derivativee w.r.t. theta is 0
 
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  • #7
great thanx! Have not done calculus for a while, so I am repeting a bit before next semester=)
 
  • #8
No, that is not true.

In general, if [itex]\theta[/itex] is a function of t and f is any function of [itex]\theta[/itex] then it is also a function of t and
[tex]\frac{df}{d\theta}= \frac{df}{dt}\frac{dt}{d\theta}[/tex]
In particular, if [itex]f= d\theta /dt[/itex] then
[tex]\frac{d}{dt}\frac{d\theta}{dt}= \frac{d^2\theta}{dt^2}\frac{dt}{d\theta}[/tex]
which is not necessarily 0.

To take an easy example, if [itex]\theta= e^t[/itex] then
[tex]\frac{d\theta}{dt}= e^t= \theta[/itex]
so that
[tex]\frac{d}{d\theta}\frac{d\theta}{dt}= \frac{d\theta}{d\theta}= 1[/tex]
 
  • #9
Right but

In the link L is function of theta, theta- dot and t

So for L at least
[tex] \frac{\partial}{\partial\theta}\left( \dfrac{d\theta}{dt}\right) = 0 [/tex]
is true
I have considered the lagrangian and was not carefull:blushing:
thanks
 
  • #10
Try being careful!
 

FAQ: Multivariable Derivative Practice

What is a multivariable derivative?

A multivariable derivative is a type of derivative that involves multiple independent variables. It measures the rate of change of a function with respect to each variable, while holding all other variables constant.

How is a multivariable derivative calculated?

A multivariable derivative is calculated using partial derivatives, which involve taking the derivative of a function with respect to one variable while treating all other variables as constants. These partial derivatives are then combined to calculate the full multivariable derivative.

Why is it important to know how to calculate multivariable derivatives?

Multivariable derivatives are important in many fields of science, such as physics, engineering, economics, and more. They allow us to understand how a function changes in relation to multiple variables, which is crucial in solving real-world problems and making predictions.

What is the difference between a multivariable derivative and a single variable derivative?

The main difference is that a multivariable derivative involves multiple independent variables, while a single variable derivative only involves one independent variable. Multivariable derivatives also use partial derivatives instead of regular derivatives.

Are there any applications of multivariable derivatives in everyday life?

Yes, there are many applications of multivariable derivatives in everyday life. For example, they are used in calculating rates of change in stock prices, determining optimal production levels in manufacturing, and predicting the trajectory of a spacecraft. They also play a crucial role in machine learning and data analysis.

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