Confusion about partial derivatives

In summary: F(t)= 3t(2t^2+ t)+ e^{2t^2+ t}= 12t^5+ 12t^4+ 3t^3+ e^{2t^2+ t}In summary, the conversation discusses the confusion about using partial derivatives in functions where one variable is dependent on another. The conclusion is that it is possible to use partial derivatives in these cases by factoring in the chain rule. It is also noted that it is more accurate to use a different name for the function when it is expressed as a composition of another function.
  • #1
Hassan2
426
5
Dear all,

I have a confusion about partial derivatives.

Say I have a function as

[itex]y=f(x,t)[/itex]

and we know that
[itex]x=g(t)[/itex]

1. Does it make sense to talk about partial derivatives like [itex]\frac{\partial y}{\partial x}[/itex] and [itex]\frac{\partial y}{\partial t}[/itex] ?

I doubt, because the definition of partial derivative is the change in the function due to the change on the selected variable ( other variables are kept constant).

2. If it does not make sense, then how in Euler–Lagrange equation we use the partial derivatives with respect to a function(x(t)) and its derivative(x'(t)) while they depend on one another.

Your help would be appreciated.
 
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  • #2
Hassan2 said:
Dear all,

I have a confusion about partial derivatives.

Say I have a function as

[itex]y=f(x,t)[/itex]

and we know that
[itex]x=g(t)[/itex]

1. Does it make sense to talk about partial derivatives like [itex]\frac{\partial y}{\partial x}[/itex] and [itex]\frac{\partial y}{\partial t}[/itex] ?

I doubt, because the definition of partial derivative is the change in the function due to the change on the selected variable ( other variables are kept constant).

2. If it does not make sense, then how in Euler–Lagrange equation we use the partial derivatives with respect to a function(x(t)) and its derivative(x'(t)) while they depend on one another.

Your help would be appreciated.

Hey Hassan2.

For 1. Yes it makes sense to do both but you need to factor in things like the chain rule for this particular example: as long as you are taking into account these kinds of factors, then yes it's ok. Your partial with respect to t can take into account your g(t) using the chain rule.

If the function is differentiable in the the region you are considering, the derivative will make sense: it's guaranteed to as a consequence of differentiability holding.
 
  • #3
Thanks Chiro,

Yes, I checked the derivation of Euler-Largrange equation once again, and i found that the derivatives wit respect to x and x' appear as a result of applying chain rule.

Thanks again.
 
  • #4
The notation [itex]\partial f/\partial x[/itex] means the derivative of f with respect to x while holding x constant- and ignoring the fact that x is a function of t. We are really dealing with the "form" of f rather than the content.

The same is true of [itex]\partial f/\partial t[/itex]. However, we can, using x= g(t), think of f as a function of t only- f(x, t)= f(g(t), t). In that case, by the chain rule,
[tex]\frac{df}{dt}= \frac{\partial f}{\partial t}+ \frac{\partial f}{\partial x}\frac{dx}{dt}[/tex]

Example: if [itex]f(x,t)= 3tx^2+ e^x[/itex] then [itex]\partial f/\partial x= 6tx+ e^x[/itex] and [itex]\partial f/\partial t= 3x^2[/itex]. That has nothing to do with x being a function of t or vice-versa.

But if we also know that [itex]x= g(t)= 2t^2+ t[/itex] we can write [itex]f(t)= 3t(2t^2+ t)+ e^{2t^2+ t}= 12t^5+ 12t^4+ 3t^3+ e^{2t^2+ t}[/itex] so that the derivative is
[tex]\frac{df}{dt}= 60t^4+ 48t^3+ 9t^2+ (4t+ 1)e^{2t^2+ t}[/tex]

Or, you could use the chain rule as I said:
[itex]\partial f/\partial t= 3x^2[/itex] and [itex]\partial f/\partial x= 3tx+ e^x[/itex], as above, while [itex]dx/dt= 4t+1[/itex] and so
[tex]\frac{df}{dx}= 3x^2+ (3tx+ e^x)(4t+ 1)[/tex]
and, replacing x in that with [itex]2t^2+ t[/itex]
[tex]\frac{df}{dx}= 3(2t^2+ t)+ (3t(2t^2+ t)+ e^{2t^2+ t})(4t+1)[/tex]
gives the same thing.
 
  • #5
Strictly speaking, one should not write f(t)=f(g(t),t). The function on the left should have gotten a new name. That is the source of some confusion.
 
  • #6
algebrat said:
Strictly speaking, one should not write f(t)=f(g(t),t). The function on the left should have gotten a new name. That is the source of some confusion.

Agreed!
What we should write, is something like:

F(t)=f(g(t),t)
 

Related to Confusion about partial derivatives

1. What are partial derivatives and how are they different from ordinary derivatives?

Partial derivatives are a type of derivative used in multivariable calculus. They measure the rate of change of a function with respect to one of its variables, while holding all other variables constant. This is different from ordinary derivatives, which measure the instantaneous rate of change of a function with respect to one variable.

2. Why is it important to use partial derivatives?

Partial derivatives are important because they allow us to analyze the behavior of a function in multiple dimensions. This is useful in many fields such as physics, economics, and engineering, where the relationships between multiple variables are often complex.

3. How do you calculate partial derivatives?

To calculate a partial derivative, you take the derivative of a function with respect to one variable while treating all other variables as constants. This is done using the same rules and formulas as ordinary derivatives, but with the added step of keeping the other variables constant.

4. What is the difference between a partial derivative and a total derivative?

A partial derivative measures the rate of change of a function with respect to one variable, while keeping all other variables constant. A total derivative, on the other hand, measures the overall rate of change of a function with respect to all of its variables. In other words, a partial derivative only considers the effect of one variable on the function, while a total derivative considers the effects of all variables.

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

Partial derivatives have many real-world applications, such as in physics to calculate the velocity and acceleration of objects moving in multiple dimensions, in economics to analyze the relationship between multiple variables, and in engineering to optimize designs and systems. They also play a crucial role in machine learning and data analysis, where they are used to optimize functions and make predictions based on multiple variables.

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