Partial Vs. Complete differentials when dealing with non-independent variables

In summary, the differentials in the solution to #3 are partial because the constraint dictates that g_y=g_x.
  • #1
raxAdaam
32
0
I'm brushing up on differentiating multi-variable functions subject to a constraint and was curious about the notation. In particular, why the derivatives change from complete to partial derivates. I've illustrated the question with an example, below. My specific question w.r.t. the example is in bold.

For example, if [itex]w = w(x,y,z)[/itex] is subject to the constraint [itex]g(x,y,z) = c[/itex], where c is a constant. To find [itex] \left(\frac{\partial w}{\partial y}\right)_z[/itex] using differentials, we would first write:

[itex] dw = w_x dx + w_y dy + w_z dz[/itex]

Because we are interested in the case where [itex]z[/itex] is held constant [itex]dz = 0[/itex], which leaves us with:

  1. [itex] dw = w_x dx + w_y dy[/itex].

    Now, in order to find [itex] \left(\frac{\partial w}{\partial y}\right)_z[/itex], we use the constraint to find an expression for [itex]dx[/itex] in terms of [itex]dy[/itex], skipping the steps, this comes out to be:
  2. [itex] dx = -\frac{g_y}{g_x}dy[/itex],


    where [itex] g_{\alpha} = \frac{\partial g}{\partial \alpha}[/itex] is just convenient shorthand. Plugging this expression for [itex]dx[/itex] into #1, rearranging and factoring out the [itex]dy[/itex], we have:
  3. [itex] dw = \left[w_y-w_x\frac{g_y}{g_x}\right]dy[/itex]

My question arises here: as I understand, the differentials in #3 are "complete" (i.e. not partial); however, if we want to go from #3 to the desired expression, viz. [itex]\left(\frac{\partial w}{\partial y}\right)_z[/itex], they become partial differentials - why?

A related question that interests me is how one would interpret these two elements on the RHS of #3 - I understand where each comes from entirely, so I'm not looking for a literal translation from the math to English, I'm trying to understand the relevance of the terms. I see that [itex]w_y[/itex] is simply the partial derivative w.r.t. [itex]y[/itex] in the case that the variables were all independent, but how to understand the other term and why it has the form that it does?
 
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  • #2
I managed to answer the second question (I think / I hope!) & thought I'd post it in case anyone was curious.

The first term [itex] w_y = \frac{\partial w}{\partial y}[/itex] is just the usual partial, as mentioned above.

Now the significance of the second term becomes clearer if one writes out the equivalent form of [itex]\frac{g_y}{g_x}[/itex], viz. because [itex]g(x,y,z) = 0[/itex] we have (holding [itex]z[/itex] constant: [itex]dg = 0 = g_x dx + g_y dy[/itex] which gives us [itex]\frac{g_y}{g_x} = -\left(\frac{\partial x}{\partial y}\right)_z[/itex] and the answer above becomes:

[itex]\left( \frac{\partial w}{\partial y} \right)_z = w_y + w_x\cdot \left(\frac{\partial x}{\partial y}\right)_z[/itex]

so in the second term we are adding the additional change in [itex]w[/itex] caused by [itex]x[/itex] varying in response to the change in [itex]y[/itex] (which is what we would expect, I realize now - but the negative sign was confusing).

If there is a more salient (or geometric) interpretation - I'd be very interested to hear!
 
  • #3
Any thoughts or clarifications on this? Am very keen to understand what's happening here ...
 
  • #4
raxAdaam said:
#3 [itex] dw = \left[w_y-w_x\frac{g_y}{g_x}\right]dy[/itex]

My question arises here: as I understand, the differentials in #3 are "complete" (i.e. not partial); however, if we want to go from #3 to the desired expression, viz. [itex]\left(\frac{\partial w}{\partial y}\right)_z[/itex], they become partial differentials - why?

A related question that interests me is how one would interpret these two elements on the RHS of #3 - I understand where each comes from entirely, so I'm not looking for a literal translation from the math to English, I'm trying to understand the relevance of the terms. I see that [itex]w_y[/itex] is simply the partial derivative w.r.t. [itex]y[/itex] in the case that the variables were all independent, but how to understand the other term and why it has the form that it does?

As far as the differentials not being partial, two things. First thing, we have the notation [itex]dx[/itex], [itex]\frac{\partial}{\partial x}[/itex], and [itex]\frac{d}{dx}[/itex]. No idea why derivatives have a regular and partial version, and differentials don't. That is an interesting question. Second thing is, that partial also has a z on it, which the differential doesn't have that either. I'm just going to make a wild guess and say that it has something to with theoretical mathematician's realizing that differentials are more well behaved, and don't require a lot of policing, but I'm not sure. I think you were observant to notice that, and it's good that you are seeing all the mechanisims that are going on. And the notation in math is not perfect, you are welcome to make your own system, maybe notes in the margins about what is being held fixed when.

But here's another way I might help, it may even help with the differentials. I like to be careful about naming things. For instance, from the constraint, we are to solve for x as a function y and z, so enforcing g=c implies we can find for x(y,z). So we have w(y,z)=w(x(y,z),y,z). The left side doesn't look right, so I like to rename it, v(y,z)=w(x(y,z),y,z). So we really want v_y. Which is w_x*x_y+w_y. So renaming things got me to where I want to go a little quicker.


raxAdaam said:
If there is a more salient (or geometric) interpretation - I'd be very interested to hear!

Umm, geometrically, you are constraining yourself to move along the g=c surface. Now you take a z-slice, and the intersection of the z-slice with the g=c surface is a curve. Now let y vary, and staying on that curve tells you how the other dependent variables change, which in turn detemrines how the f value changes.
 

Related to Partial Vs. Complete differentials when dealing with non-independent variables

1. What is the difference between partial and complete differentials?

Partial differentials involve taking the derivative of a function with respect to one variable while holding all other variables constant. Complete differentials, on the other hand, involve taking the derivative of a function with respect to all variables simultaneously.

2. When should I use partial differentials versus complete differentials?

Partial differentials are used when dealing with non-independent variables, meaning that the variables are related to each other. Complete differentials are used when dealing with independent variables, meaning that they are not related to each other.

3. How are partial and complete differentials related?

Partial and complete differentials are related through the chain rule. The partial derivatives of a function can be combined using the chain rule to find the complete differential of the function.

4. Can a partial differential be converted into a complete differential?

Yes, a partial differential can be converted into a complete differential by using the chain rule to combine the partial derivatives. However, the reverse is not true - a complete differential cannot be converted into a partial differential.

5. What is the significance of partial and complete differentials in science?

Partial and complete differentials are important in science because they allow us to analyze how a function changes in response to changes in its variables. This is especially useful in fields such as physics and engineering, where many variables are often related to each other.

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