Stuck on proof regarding partial derivatives

In summary, the conversation discusses proving that a function with first-order partial derivatives is constant. The hint suggests showing that the function is constant along lines parallel to the coordinate axes. Using the Mean Value Theorem, the conversation discusses how the function must be continuous and therefore constant along these lines. This, combined with the fact that the function is constant along both axes, leads to the conclusion that the function is constant everywhere.
  • #1
Yami
20
0

Homework Statement


Suppose the function f:R^2→R has 1st order partial derivatives and that
δf(x,y)/δx = δf(x,y)/δy = 0 for all (x,y) in R^2.
Prove that f is constant; there exists c such that f(x,y) = c for all (x,y) in R.

There's a hint as well:
First show that the restriction of f:R^2→R to a line parallel to one of the coordinate axes is constant.

Homework Equations


The chapter defines partial derivatives in general:
Let O be open in R^n and i be an index with 1≤i≤n. A function f:O→R has a partial derivative with respect to its ith component at the point x in O provided that
lim_(t→0)(f(x + t*e_i) - f(x))/t exists.


The Attempt at a Solution


The chapter has no mention of integrals but I tried using integrals anyway since I have no idea what to do with the given hint.

0 =
y
∫δf(x,t)/δy dt +
0
x
∫δf(t,0)/δy dt
0
= f(x,y) - f(x,0) + f(x,0) - f(0,0)
= f(x,y) - f(0,0)

implying f(x,y) = f(0,0) for all (x,y).
But then I realized that the partial derivatives being 0 means their antiderivatives are constant, so that won't work out.
Now I'm looking at the hint again but, I'm really stumped on how to use it. The chapter mentions the Mean Value Theorem. I thought of trying that somehow, but it's not given that the function is continuous. Can anyone point me in the right direction?
 
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  • #2
Set y = c, constant, and consider h(x) = f(x,c). Can you apply the MVT to that?
 
  • #3
Well, another reason I'm having trouble with this problem is I'm having trouble believing it's true.
What if f(x,y) =
{2 if (x,y) = (0,0),
{3 if (x,y) ≠ (0,0).

Wouldn't the partial derivatives be 0 still? Again it's not given that the function is continuous. Do I have to assume it's continuous?
 
  • #4
Yami said:
Well, another reason I'm having trouble with this problem is I'm having trouble believing it's true.
What if f(x,y) =
{2 if (x,y) = (0,0),
{3 if (x,y) ≠ (0,0).

Wouldn't the partial derivatives be 0 still? Again it's not given that the function is continuous. Do I have to assume it's continuous?

If the partial derivative with respect to x exists at (x,c) then the function of x given by f(x,c) must be continuous. Same for f(c,y). Assuming the derivative exists implies continuity.
 
  • #5
Ah, yes. But this section in the book specifically states that
"For n > 1, a function f: R^n→R that has first order partial derivatives need not be continuous," and even provides an example:
f(x,y) =
{xy/(x^2+y^2) if (x,y) ≠ (0,0)
{0 if (x,y) = (0,0)

The partials at (0,0) are 0.

Okay, I'm going try this:
Suppose f is not continuous. Then f is not constant, since f being constant implies it's continuous. Then we are done?

Then with that assertion that f should be continuous I can use MVT. Yes?
 
  • #6
LCKurtz said:
If the partial derivative with respect to x exists at (x,c) then the function of x given by f(x,c) must be continuous. Same for f(c,y). Assuming the derivative exists implies continuity.

Yami said:
Ah, yes. But this section in the book specifically states that
"For n > 1, a function f: R^n→R that has first order partial derivatives need not be continuous," and even provides an example:
f(x,y) =
{xy/(x^2+y^2) if (x,y) ≠ (0,0)
{0 if (x,y) = (0,0)

The partials at (0,0) are 0.

Okay, I'm going try this:
Suppose f is not continuous. Then f is not constant, since f being constant implies it's continuous. Then we are done?

Then with that assertion that f should be continuous I can use MVT. Yes?

But I didn't say the function f(x,y) was continuous as a function of two variables. What you do have is that as a function of one variable with the other held constant it is continuous. And its derivative is given to exist and is 0.
 
  • #7
Oh, I think I see now. For a function of one variable, differentiability implies continuity. So that's where the hint fits in? Use the line parallel to an axis to equate it to a function with an interval domain to imply continuity?

So I can do something like this:
I = {(x,c) | c = some constant}, the line.
g:I→R ; g(x) = f(x,c). Since g is differentiable on I it is continuous?
 
  • #8
Yami said:
Oh, I think I see now. For a function of one variable, differentiability implies continuity. So that's where the hint fits in? Use the line parallel to an axis to equate it to a function with an interval domain to imply continuity?

So I can do something like this:
I = {(x,c) | c = some constant}, the line.
g:I→R ; g(x) = f(x,c). Since g is differentiable on I it is continuous?

You have a function of one variable whose derivative is 0 and you are trying to show it is a constant. Perhaps if you show it is constant along the line where y = c that would get you started. Look in your calculus book to see how f'(x) identically 0 implies f(x) is a constant. I bet you will see a reference to the MVT.
 
  • #9
And I might add that once you have f(x,y) is constant along lines (x,c) and (a,y) you need to show that f is the same constant everywhere.
 
  • #10
I think I've written out a satisfying proof. Thanks for your help.
 

1. What are partial derivatives and why are they important?

Partial derivatives are a type of derivative used in multivariable calculus to measure how a function changes with respect to a specific variable while holding all other variables constant. They are important in many fields of science, including physics, economics, and engineering, as they allow us to analyze how systems change based on multiple variables.

2. How do I solve for partial derivatives?

To solve for partial derivatives, you will need to use the chain rule and the rules of differentiation. First, identify the variable you want to differentiate with respect to, and treat all other variables as constants. Then, take the derivative of the function with respect to that variable, keeping all other variables constant. Repeat this process for each variable in the function.

3. 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 a specific variable, while holding all other variables constant. A total derivative, on the other hand, measures the overall rate of change of a function with respect to all variables at once. In other words, a partial derivative only considers one variable at a time, while a total derivative takes into account the influence of all variables on the function.

4. How can I use partial derivatives in real-world applications?

Partial derivatives are used in many real-world applications, such as optimizing production processes, predicting financial outcomes, and analyzing changes in weather patterns. They allow scientists and engineers to understand how various factors affect a system and make predictions about how it will behave under different conditions.

5. Are there any strategies for simplifying partial derivative calculations?

One strategy for simplifying partial derivative calculations is to first rewrite the function in terms of one variable, eliminating any constants or terms that do not involve the variable you are differentiating with respect to. Additionally, using the product rule, quotient rule, and chain rule can help simplify more complex functions. It is also helpful to practice and become familiar with common derivative rules and techniques.

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