Checking Total Differential of f(x,y) in [0,0]

In summary, the conversation was about computing the total differential for the function f(x,y) = \sqrt[3]{x^3+y^3} and determining if it exists at the point [0,0]. The approach taken was to first find the partial derivatives, which were found to be continuous except at [0,0]. Then, using the limit definition, the partial derivatives at [0,0] were computed to be 1. However, when considering the limit for total differential, it was found that it does not exist, leading to the conclusion that f does not have total differential at [0,0]. There was also a mention of a typo in the partial derivatives.
  • #1
twoflower
368
0
Hi,

I started computing excercises on total differential and I would like to know if I'm doing it correctly. Could you please check it? Here it is:

Does the function

[tex]
f(x,y) = \sqrt[3]{x^3+y^3}
[/tex]

have total differential in [0,0]?

First I computed partial derivatives:

[tex]
\frac{\partial f}{\partial x} = \frac{x^3}{\sqrt[3]{(x^3 + y^3)^2}}
[/tex]

[tex]
\frac{\partial f}{\partial y} = \frac{y^3}{\sqrt[3]{(x^3 + y^3)^2}}
[/tex]

I see that partial derivatives are continuous everywhere with the exception of the point [0,0].

For the point [0,0] I have to compute partial derivatives from definition using the limit:

[tex]
\frac{\partial f}{\partial x}(0,0) = \lim_{t \rightarrow 0} \frac{f(t,0) - f(0,0)}{t} = \lim_{t \rightarrow 0} \frac{t}{t} = 1
[/tex]

[tex]
\frac{\partial f}{\partial y}(0,0) = \lim_{t \rightarrow 0} \frac{f(0,t) - f(0,0)}{t} = \lim_{t \rightarrow 0} \frac{t}{t} = 1
[/tex]

So in the case that total differential in the point [0,0] exists, it must be of form:

[tex]
L(h) = \frac{\partial f}{\partial x}(0,0) h_1 + \frac{\partial f}{\partial y}(0,0) h_2 = h_1 + h_2
[/tex]

for any

[tex]
h = (h_1, h_2) \in \mathbb{R}^2
[/tex]

and must satisfy the limit

[tex]
\lim_{||h|| \rightarrow 0} \frac{f(0,0) + h) - f(0,0) - L(h)}{||h||} = 0
[/tex]

I can write it this way:

[tex]
\lim_{[h_1,h_2] \rightarrow [0,0]} \frac{\sqrt[3]{h_1^3 + h_2^3} - 0 - h_1 - h_2}{\sqrt{h_1^2 + h_2^2}}
[/tex]

When I put

[tex]
h_2 = kh_1
[/tex]

I can write

[tex]
\lim_{h_1 \rightarrow 0} \frac{ \sqrt[3]{h_1^3 + k^3h_1^3} - h_1kh_1}{\sqrt{h_1^2 + k^2h_1^2}} = \frac{\sqrt[3]{1+k^3} - 1 - k}{\sqrt{1 + k^2}} \neq 0
[/tex]

And thus I say that f doesn't have total differential in [0,0].

Is this correct approach?

Thank you for checking this out.
 
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  • #2
You have the partial derivatives wrong- though it may just be a typo.
[tex]f_x(x,y)= \frac{x^2}{^3\sqrt{(x^3+ y^3)^2}}[/tex]
 
  • #3
HallsofIvy said:
You have the partial derivatives wrong- though it may just be a typo.
[tex]f_x(x,y)= \frac{x^2}{^3\sqrt{(x^3+ y^3)^2}}[/tex]

You're right, it's a typo. Is it ok otherwise?
 

1. What is the purpose of checking the total differential of a function at a specific point?

The total differential of a function at a specific point, also known as the total derivative, allows us to understand how the function changes in response to small changes in its input variables. It helps us analyze the behavior of a function and its sensitivity to changes in its inputs.

2. How is the total differential of a function calculated?

The total differential of a function f(x,y) is calculated using the partial derivatives of the function with respect to each of its input variables (x and y). It is represented by the symbol df and can be calculated using the formula: df = ∂f/∂x * dx + ∂f/∂y * dy.

3. What does checking the total differential at [0,0] tell us about the function?

Checking the total differential at [0,0] allows us to understand the behavior of the function at that specific point. It tells us about the rate of change of the function with respect to small changes in its input variables at that point. This can help us determine the direction of maximum increase or decrease of the function at [0,0].

4. Can the total differential of a function be negative?

Yes, the total differential of a function can be negative. This means that the function is decreasing in response to small changes in its input variables. It can also be positive, indicating that the function is increasing, or zero, indicating that the function is not changing at that point.

5. How can checking the total differential help in optimizing a function?

Checking the total differential can help in optimizing a function by providing information about the sensitivity of the function to changes in its inputs. This can help in determining the direction in which the function should be modified to achieve the desired outcome. It can also help in identifying critical points, such as local maxima or minima, which are important in optimization problems.

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