What is the geometric interpretation of the partial derivative?

In summary, the differential of a function is the change in the function at a point over the course of one dimension.
  • #1
gulsen
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0
Say, E is dependent to x,y,z. I'm expecting it's derivative at [tex]x_0,y_0,z_0[/tex] to be

[tex]dE = \lim_{\substack{\Delta x\rightarrow 0\\\Delta y\rightarrow 0\\\Delta z\rightarrow 0}} E(x_0+\Delta x, y_0+\Delta y,z_0+\Delta z) - E(x_0,y_0,z_0)[/tex]

But with following definition, it's not the thing above:

[tex]dE = \lim_{\substack{\Delta x\rightarrow 0\\\Delta y\rightarrow 0\\\Delta z\rightarrow 0}} \frac{E(x_0+\Delta x, y_0,z_0) - E(x_0,y_0,z_0)}{\Delta x} \Delta x + \frac{E(x_0, y_0+\Delta y,z_0) - E(x_0,y_0,z_0)}{\Delta y} \Delta y + \frac{E(x_0, y_0,z_0+\Delta z) - E(x_0,y_0,z_0)}{\Delta z} \Delta z = \frac{\partial E}{\partial x}dx + \frac{\partial E}{\partial y}dy + \frac{\partial E}{\partial z}dz[/tex].

Now, which is correct? (and why?!?)
 
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  • #2
Neither one. The differential (not "derivative") is
[tex]dE= \left(\lim_{\Delta x\rightarrow0}\frac{E(x_0+\Delta x,y_0,z_0)-E(x_0,y_0,z_0)}{\Delta x}\right)dx+ \left(\lim_{\Delta y\rightarrow 0}\frac{E(x_0,y_0+\Delta y,z_0)-E(x_0,y_0,z_0)}{\Delta y}\right)dy+ \left(\lim_{\Delta z\rightarrow 0}\frac{E(x_0,y_0,z_0+\Delta z)-E(x_0,y_0,z_0)}{\Delta z}\right)dz[/tex]
That's the same as your second formula except for the "d" rather than "[itex]\Delta[/itex]" in the numerator.

Why would you "expect" the first? In one variable, would you "expect" the differential of f(x) to be
[tex]df= lim_{\substack{\Delta x\rightarrow 0}}f(x_0+\Delta x)- f(x_0)[/tex]
If f is any continuous function, that's 0!
 
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  • #3
Whoops, just a typo anyway.

Why would you "expect" the first?

That was just a guesswork based on intuition and my ignorance, I simply don't know. So tell me, why would you expect the latter?
 
  • #4
Well, at least you could point some links.
 
  • #5
Or you could look at the definition of the differential in any calculus book:

[tex]df(x,y,z)= \frac{\partial f}{\partial x}dx+ \frac{\partial f}{\partial y}dy+ \frac{\partial f}{\partial z}dz[/tex]
which, if you go back to the definition of the partial derivatives, is the formula I gave.
 
  • #6
Whoops, we've got a communication problem here, it seems.
I know that this is the definition, and I've written it before you as well. My question is: why? What geometry/mathematical quantity does this correntponds to?
 
  • #7
From what I've found, it should be like this:
[tex]df(x,y,z)= \frac{\partial f}{\partial x}dx \vec{i} + \frac{\partial f}{\partial y}dy \vec{j} + \frac{\partial f}{\partial z}dz \vec{k} [/tex]
But this way, for the magnitude of this df, we got to multiply (dot product) df with itself and square root...
 
  • #8
gulsen said:
Whoops, we've got a communication problem here, it seems.
I know that this is the definition, and I've written it before you as well. My question is: why? What geometry/mathematical quantity does this correntponds to?
Just picture f as a function of two variables instead of three; z = f(x,y). Thus f can be represented by a surface S in 3 space. The total differential df in the equation
[tex]df(x,y)= \frac{\partial f}{\partial x}dx+ \frac{\partial f}{\partial y}dy[/tex]
would represent the change in the z component of the tangent plane T of f at a point P at coordinates (x,y,z) as we go to some other point P' at (x+delta x,y+delta y,f(x+delta x,y+delta y)). In this case, since delta x and delta y are independent variables, we can say dx=delta x and dy=delta y; i.e dx and dy can be actual distance values. Notice that df is related to the z component of points in T but delta f is related to the z component of points in the surface that f generates.

It's even easier to picture if you just consider f as function of one variable: y=f(x). Though you lose the "partial" nature of the derivitive, the geometric picture you were looking for is still there. For example, you can picture some curved line that f generates and some tangent line T at a point P at (x, f(x)). If you take another point on the curve P' at (x+delta x, f(x+delta x)), dy would represent the verticle distance between a horizontal line through P and the tangent line T. In other words, dy would represent the distance that T changes in the y direction for some change dx=delta x in the x direction. We could imagine an animal called delta y (as distinct from dy) that represents the distance from the horizontal line through point P to the CURVE (rather than the tangent line T).

Why would I even begin to set here and type all that?
 

1. What is partial differentiation?

Partial differentiation is a mathematical concept used to calculate the rate of change of a function with respect to one of its variables while holding the other variables constant. It is often used in multivariable calculus to analyze functions with multiple independent variables.

2. Why is partial differentiation important?

Partial differentiation allows us to analyze how a function changes with respect to one variable while keeping the other variables constant. This is useful in many fields, such as physics and economics, where there are multiple factors that can affect a system.

3. How is partial differentiation different from ordinary differentiation?

Ordinary differentiation involves finding the rate of change of a function with respect to one variable, while partial differentiation involves finding the rate of change of a function with respect to one variable while holding the other variables constant. In other words, partial differentiation takes into account the effects of all other variables on the function, while ordinary differentiation does not.

4. What are the notations used in partial differentiation?

There are several notations used in partial differentiation, including the subscript notation (∂) and the prime notation ('). The subscript notation is often used for partial derivatives, while the prime notation is used for ordinary derivatives. The notation for partial differentiation can vary, so it is important to check the specific notation being used in a particular problem.

5. What are some practical applications of partial differentiation?

Partial differentiation has many practical applications, such as in optimization problems where we want to find the maximum or minimum value of a function. It is also used in physics to analyze the rate of change of physical quantities, such as velocity and acceleration. In economics, partial differentiation is used to analyze the sensitivity of a system to changes in different variables.

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