Chain rule with multiple variables

In summary: The conversation also includes a discussion on how to derive the formula and clarifications on the notation used. The key is to remember that all derivatives are partial and to keep track of the implicit dependence of the variables.
  • #1
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I was reading over a textbook that stated the following, where [itex]y(s,t) = v(x(s,t),t)[/itex]

[tex]\frac{\partial y}{\partial t} = \frac{\partial v}{\partial x}\frac{\partial x}{\partial t} + \frac{\partial v}{\partial t}[/tex]

and

[tex]\frac{\partial^2y}{\partial t^2} = \frac{\partial^2 v}{\partial x^2}\left ( \frac{\partial x}{\partial t} \right )^2 + 2\frac{\partial^2 v}{\partial x \partial t}\frac{\partial x}{\partial t} + \frac{\partial^2 v}{\partial t^2}+ \frac{\partial v}{\partial x}\frac{\partial^2 x}{\partial t^2}[/tex]

I have been having trouble figuring out how they came to the second statement. My logic proceeds as such, using the product rule:

[tex]\frac{\partial^2y}{\partial t^2} = \frac{\partial}{\partial t}\left [ \frac{\partial v}{\partial x}\frac{\partial x}{\partial t} + \frac{\partial v}{\partial t} \right] = \frac{\partial^2 v}{\partial t \partial x}\frac{\partial x}{\partial t} + \frac{\partial v}{\partial x}\frac{\partial^2 x}{\partial t^2} + \frac{\partial^2 v}{\partial t^2}[/tex]

But certainly my result is not equivalent to the correct one. Where did I go astray? Thanks all!
 
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  • #2
It looks like the textbook's result is correct. I just came up with a long, messy proof of the formula, and I've attached it as a PDF. You're probably going to need to zoom into see all the details. Tell me if you don't understand something. It seems like I'm making this proof unnecessarily complicated, so let's see whether I can find a way to make it shorter and more intuitive.
 

Attachments

  • Monstrous Multivariable Chain Rule.pdf
    30.2 KB · Views: 380
  • #3
you have to remember
[tex] \frac{\partial v}{\partial x},[/tex]
is a function of t explicitly and a function of t through x.
so that
[tex] \frac{\partial}{\partial t}\left( \frac{\partial v(x(t), t)}{\partial x} \right)
= \frac{\partial}{\partial x}\left( \frac{\partial v(x(t), t)}{\partial x} \right) \frac{\partial x}{\partial t}+
\frac{\partial^2 v(x(t), t)}{\partial t \partial x}
[/tex]

this is one of those cases where the notation is kind of sloppy.

and of course the same thing for
[tex] \frac{\partial v}{\partial t}( x(t), t) [/tex]
 
Last edited:
  • #4
qbert, are you using total derivatives instead of partial derivatives, but denoting them as partial derivatives? If so, why?
 
  • #5
all derivatives are partial holding s constant.
you just need to keep the implicit dependence straight.
 
  • #6
OK, I got it now. I just needed to keep the partial and total derivatives straight. I've attached a PDF with two relatively compehensible proofs of the formula.
 

Attachments

  • Not-So-Monstrous Chain Rule.pdf
    27.1 KB · Views: 309
  • #7
i said something wrong which has been bugging me.
i was going to let it slide but then there was an answer
with the phrase "total derivative", which to me needed
commenting on.

this is basically nit-picking, but...

all the derivatives are partial. they're partial and the
notation is ambiguous as to what's "being held constant"
which is why i commented on the sloppiness of the notation.

when you write [itex] \frac{\partial^2 y}{\partial t^2} [/itex]where [itex]y = y(s,t)[/itex] is a function
of the two variables it means, keep s constant through both derivatives.

so we need to remember our function always depends on the
two variables s an t.

now if we define [itex]y(s,t)=v(x(s,t), t)[/itex] then v is
a function of the two variables x and t. and x is a function
of the two variables s and t.

so that
[tex]\frac{\partial y}{\partial t} = \frac{\partial v}{\partial x}\frac{\partial x}{\partial t}
+ \frac{\partial v}{\partial t}[/tex]

The symbol [itex]\frac{\partial }{\partial t}[/itex] means different things on each side of
the equation! acting on y(s,t) it means differentiate with respect to t keeping s constant.
When it acts on v(x,t) it means differentiate with respect to t keeping x constant.

It turns out to be convenient here to introduce
[tex]
\frac{\partial v}{\partial x}(x,t) = w(x, t), \text{ and }
\frac{\partial v}{\partial t}(x, t) = u(x, t).
[/tex]

So that

[tex]\frac{\partial y}{\partial t}(s,t) = w(x(s,t), t) \frac{\partial x}{\partial t}(s,t)
+ u(x(s, t), t)[/tex]

Now doing the derivative holding s constant gives
[tex] \frac{\partial^2 y}{\partial t^2} =
\left( \frac{\partial w}{\partial x} \frac{\partial x}{\partial t}
+ \frac{\partial w}{\partial t}
\right) \frac{\partial x}{\partial t}
+ w \frac{\partial^2 x}{\partial t^2}
+ \left( \frac{\partial u}{\partial x} \frac{\partial x}{\partial t} + \frac{\partial u}{\partial t} \right)
[/tex]

now plugging in for w and u the derivatives of v gives the books result.
notice all the derivatives are partial.
 

FAQ: Chain rule with multiple variables

1. What is the chain rule with multiple variables?

The chain rule is a mathematical formula used to find the derivative of a composite function. In other words, it helps us find the rate of change of a function that is made up of two or more functions.

2. How is the chain rule applied when there are multiple variables?

In the chain rule, the derivatives of the inner functions are multiplied together and then multiplied by the derivative of the outer function. This process is repeated for each variable in the composite function.

3. What are the benefits of using the chain rule with multiple variables?

The chain rule allows us to find the derivative of complex functions that would be difficult or impossible to find using other methods. It also helps us understand the relationship between different variables in a composite function.

4. Can the chain rule be used for any number of variables?

Yes, the chain rule can be applied to functions with any number of variables. However, as the number of variables increases, the calculations can become more complex and time-consuming.

5. How can the chain rule be used in real-life applications?

The chain rule is used in various fields of science and engineering, such as physics, economics, and chemistry. It can be used to analyze and optimize complex systems, model physical phenomena, and solve problems in areas like finance and biology.

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