Partial derivative of an ordinary derivative?

In summary, the partial derivative of a rate can be treated as an ordinary differential if the top part tends to zero. This might not always be the case, and in that case you would need to use the chain rule. Thanks for the clarification, Ultimâ!
  • #1
Ultimâ
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I think the heading says it all. What happens if we take the partial derivative of a rate for example?

eg [tex]\frac{\delta}{\delta t}(\frac{dx}{dt})[/tex]

If it was normal differentiation with respect to t we'd get acceleration, or [tex]\ddot{x}[/tex]. I read somewhere that the partial can be treated as an ordinary if the top part tends to zero as the bottom part does, but if this is not the case? (such as if we had a function of cos which would approach 1)...
 
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  • #2
Ultimâ said:
I think the heading says it all. What happens if we take the partial derivative of a rate for example?

eg [tex]\frac{\delta}{\delta t}(\frac{dx}{dt})[/tex]

If it was normal differentiation with respect to t we'd get acceleration, or [tex]\ddot{x}[/tex].

Hi Ultimâ! :smile:

(have a partial: ∂ :smile:)

Partial derivative ∂/∂t simply means that you keep all variables constant other than t.

So if x only depends on t, then ∂/∂t = d/dt.

If x depends on t and something else, then you shouldn't write d/dt.

So ∂/∂t(dx/dt) doesn't really make sense. :smile:
I read somewhere that the partial can be treated as an ordinary if the top part tends to zero as the bottom part does, but if this is not the case? (such as if we had a function of cos which would approach 1)...

Sorry … not following any of that. :confused:
 
  • #3
tiny-tim said:
If x depends on t and something else, then you shouldn't write d/dt.

So ∂/∂t(dx/dt) doesn't really make sense.

This is false. You just need to apply the chain rule. If x is a function of t and some other variable u, then

[tex]\frac{d}{dt}[x(t, u)] = \frac{\partial x}{\partial t} + \frac{\partial x}{\partial u} \frac{du}{dt}[/tex]

The result will be some function [itex]\dot x = \dot x(t, u, \dot u)[/itex], and then one can certainly take

[tex]\frac{\partial}{\partial t}[\dot x(t, u, \dot u)][/tex]
 
  • #4
Thanks for that. As ben mentions, I had a case of a rate of changes (sounds like a rare disease), where the chain rule needed to be applied, and I thought the outcome seemed a bit weird. Thanks tiny-tim for verifying my suspicions that the partial can be treated as an ordinary differential when x is only dependant on t.

Given that's the case, I guess [tex]\frac{\delta}{\delta t}(cos\theta)[/tex] can produce [tex]-sin\theta\frac{d\theta}{dt}[/tex]! (of course given dependence on t)

a [tex]\delta{bye\ for\ now}[/tex]!
 

1. What is the difference between a partial derivative and an ordinary derivative?

A partial derivative measures the rate of change of a function with respect to one variable while holding all other variables constant. An ordinary derivative, on the other hand, measures the rate of change of a function with respect to one variable in general.

2. How is a partial derivative denoted?

A partial derivative is denoted by the symbol ∂, followed by the variable with respect to which the derivative is taken, and enclosed in parentheses. For example, ∂f(x,y) is the partial derivative of the function f with respect to x.

3. What is the chain rule for partial derivatives?

The chain rule for partial derivatives states that to find the partial derivative of a composite function, we take the partial derivative of the outer function with respect to the inner function, multiplied by the partial derivative of the inner function with respect to the variable in question.

4. Can a function have partial derivatives of different orders?

Yes, a function can have partial derivatives of different orders. For example, if a function has two independent variables, it can have first-order partial derivatives with respect to each variable, as well as second-order partial derivatives with respect to each variable and mixed partial derivatives of order two.

5. How are partial derivatives used in real-life applications?

Partial derivatives are commonly used in physics, engineering, and economics to model and analyze complex systems with multiple variables. They are also used in optimization problems to find the maximum or minimum value of a function. In addition, partial derivatives are essential in the study of multivariable calculus and vector calculus, which have numerous applications in various fields.

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