Differentiability of a function

In summary, the conversation discusses a problem on the differentiability of a function and the individual is seeking help in solving it. They discuss different criteria for differentiability and the individual receives a helpful hint from the expert to solve the problem. The conversation also touches upon the definition of differentiable functions and provides a theorem from the individual's book.
  • #1
estro
241
0
Hello,

I'm having problems figuring out theoretical problem on "differentiability of a function". [I hope that I spelled it right...]

Suppose that:
1. Functions f(x,y) and g(x,y) are well defined in some little domain around (0,0). (*1)
2. g(x,y) is continuous at (0,0). (*2)
3. f(x,y) is differentiable and continuous at (0,0) and f(0,0)=0. (*2)

Prove that h(x,y)=f(x,y)g(x,y) is differentiable at (0,0).

What I tried:
Let ε>0
From (*1) and (*2) I know that for every ||(x,y)||<δ_1 |g(x,y)-g(0,0)|<ε/2. (*4)
From (*1) and (*3) I know that there are a,b and u(x,y), v(x,y) so that:
f(x,y)=f(0,0)+ax+by+xu(x,u)+yv(x,u) ; u(x,y) and v(x,y) approaches 0 when (x,y) approaches (0,0). (*5)

So from (*4) and (*5) and a little of algebra I get that:
[tex]
x[g(0,0)-\epsilon/2]+y[g(0,0)-\epsilon/2]+xg(x,y)v(x,y)+yg(x,y)v(x,y) \leq h(x,y) \leq x[g(0,0)+\epsilon/2]+y[g(0,0)+\epsilon/2]+xg(x,y)v(x,y)+yg(x,y)v(x,y)
[/tex]

And at this point I have no idea what to do and I fear my approach to this problem is wrong...
 
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  • #2
If f(x, y) is differentiable at (0, 0), there exists a linear map [itex]df_{(0, 0)}(u, v)[/itex] such that [tex]\lim_{(u, v) \rightarrow (0, 0)} \frac {f(u, v) - df_{(0, 0)}(u, v) - f(0, 0)} {||(u, v)||} = \lim_{(u, v) \rightarrow (0, 0)} \frac {f(u, v) - df_{(0, 0)}(u, v)} {||(u, v)||} = 0[/tex] Now check whether [itex]g(0, 0) \cdot df_{(0, 0)}(u, v)[/itex] is such a linear map for h(x, y) at (0, 0).
 
  • #3
I'm sorry but I'm still not getting it, ofcourse I tried to find a, b so that:

[tex]\lim_{(x,y)\rightarrow(0,0)} \frac {h(x,y)-h(0,0)-ax-by}{||(x,y)||}=0[/tex]
but wasnt able to find appropriate a,b...
 
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  • #4
[itex]g(0, 0) \cdot df_{(0, 0)}(x, y) = ax + by[/itex] is what you are looking for. You need to show that.
 
  • #5
I appreciate your help, however your hints are points that I already know. [I think you get the wrong impression that I'm not familiar with the basic staff, indeed a lot of time passed since I took that course however I do remember the basics (I'm retaking the exam to improve my GPA)]

I am familiar with the different criterias for differentiability and I know that if I can show that:
[tex]\lim_{(x,y)\rightarrow (0,0)} \frac{f(x,y)g(x,y)-xf_x(0,0)g(0,0)-yf_y(0,0)g(0,0)}{\sqrt{x^2+y^2}}=0 [/tex] then I will solve the problem but the problem is that I COULDN"T show that. [this was the first thing I tried]

There is also another criteria [which I remember I was using with great success] for differentiability: there are scalars a,b [in my case a=f_x, b=f_y] and functions u(x,y),v(x,y) [both functions approaches to 0 when (x,y) goes to (0,0)] so that:
[tex]f(x,y)=f(0,0)+xf_x(0,0)+yf_y(0,0)+xu(x,y)+yv(x,y)[/tex]
Now if I multiply [and remember f(0,0)=0] both sides by g(x,y) I get:
[tex]f(x,y)g(x,y)=xf_x(0,0)g(x,y)+yf_y(0,0)g(x,y)+xu(x,y)g(x,y)+yv(x,y)g(x,y)[/tex] and this is also very close to what I need:
[tex]f(x,y)g(x,y)=x[f_x(0,0)g(0,0)]+y[f_y(0,0)g(0,0)]+x[u(x,y)g(x,y)]+y[v(x,y)g(x,y)][/tex]
where "the new a" is f_x(0,0)g(0,0) "the new b" is [f_y(0,0)g(0,0)] "the new u(x,y)" is [u(x,y)g(x,y)] and so on, I'm close to this but I'm not there...

What I tried to do in my first post is:
I arrived to:
[tex]f(x,y)g(x,y)=xf_x(0,0)g(x,y)+yf_y(0,0)g(x,y)+xu(x,y)g(x,y)+yv(x,y)g(x,y)[/tex]
So due to continuity of g I can conclude:
[tex]xf_x(0,0)[g(0,0)+\epsilon/2]+yf_y(0,0)[g(0,0)+\epsilon/2]+xu(x,y)g(x,y)+yv(x,y)g(x,y) \leq h(x,y) \leq xf_x(0,0)[g(0,0)+\epsilon/2]+yf_y(0,0)[g(0,0)+\epsilon/2]+xu(x,y)g(x,y)+yv(x,y)g(x,y)[/tex]
and it is very tempting to say the following [which is most likely not "legal"]: because this inequality is true for every epsilon that I can "swap" it to:
h(x,y) = xf_x(0,0)[g(0,0)]+yf_y(0,0)[g(0,0)]+xu(x,y)g(x,y)+yv(x,y)g(x,y)[/tex]

Sorry if this post is disorganized, I tried to think out loud...
 
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  • #6
estro said:
There is also another criteria [which I remember I was using with great success] for differentiability: there are scalars a,b [in my case a=f_x, b=f_y] and functions u(x,y),v(x,y) [both functions approaches to 0 when (x,y) goes to (0,0)] so that:
[tex]f(x,y)=f(0,0)+xf_x(0,0)+yf_y(0,0)+xu(x,y)+yv(x,y)[/tex]

This is not correct. It should be [tex]f(x,y)=f(0,0)+xf_x(0,0)+yf_y(0,0)+R(x,y)[/tex] where [tex]\lim_{(x, y) \rightarrow (0, 0)} \frac {R(x, y)} {||(x, y)||} = 0[/tex] That is, R need not be linear but it must go to zero faster than the norm of the point.

Then [tex]f(x,y)g(x, y) = f(0,0)g(x, y) + [xf_x(0,0) + yf_y(0,0)]g(x, y) + g(x, y)R(x,y)[/tex][tex] = f(0,0)g(x, y) + [xf_x(0,0) + yf_y(0,0)]g(0, 0) + [xf_x(0,0) + yf_y(0,0)]g(x, y) - [xf_x(0,0) + yf_y(0,0)]g(0, 0) + g(x, y)R(x,y)[/tex][tex] = f(0,0)g(x, y) + [xf_x(0,0) + yf_y(0,0)]g(0, 0) + [xf_x(0,0) + yf_y(0,0)] \cdot [g(x, y) - g(0, 0)] + g(x, y)R(x,y)[/tex][tex] = f(0,0)g(x, y) + [xf_x(0,0) + yf_y(0,0)]g(0, 0) + R'(x, y)[/tex] Prove [tex]\lim_{(x, y) \rightarrow (0, 0)} \frac {R'(x, y)} {||(x, y)||} = 0[/tex]
 
  • #7
voko said:
This is not correct. It should be [tex]f(x,y)=f(0,0)+xf_x(0,0)+yf_y(0,0)+R(x,y)[/tex] where [tex]\lim_{(x, y) \rightarrow (0, 0)} \frac {R(x, y)} {||(x, y)||} = 0[/tex] That is, R need not be linear but it must go to zero faster than the norm of the point.
...

Are you sure about that?
I have a theorem in my book that proves that the following 2 are "equivalent".
1. [itex] f(x,y)=o(||(x,y)||)[/itex] when [itex](x,y) \rightarrow (0,0)[/itex]
2. there are functions u(x,y) and v(x,y) defined around (0,0) so that in some domain around this point the following holds:
[itex]f(x,y)=xu(x,y)+yv(x,y) [/itex] when u,v goes to 0 around (0,0).

And I think these 2 are the same [equivalent] to what you have written.

In this same theorem the book proves some different criteria for differentiability. [unfortunately it somewhat long to copy to the forum and written in Hebrew]

And btw your last hint, was very helpful I guess I can prove what is needed now, however I hope you can help me clear the above point.
Again thank you very much.
 
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  • #8
estro said:
And I think these 2 are the same [equivalent] to what you have written.

What I wrote is the definition of differentiability. This is all you really need here.

What you wrote is a more complex expression having the same effect (which seems true), but it just makes things seem, well, more complex.
 
  • #9
voko said:
What I wrote is the definition of differentiability. This is all you really need here.

What you wrote is a more complex expression having the same effect (which seems true), but it just makes things seem, well, more complex.

I see.
A million thanks for your help. [This trick with adding something and then subtracting it, I always forget about it...]
 

Related to Differentiability of a function

What is the definition of differentiability of a function?

The differentiability of a function refers to the property of a function being smooth and continuous, without any abrupt changes or discontinuities. In mathematical terms, it means that the function has a well-defined derivative at every point in its domain.

How do you determine if a function is differentiable at a certain point?

To determine if a function is differentiable at a point, you can use the definition of differentiability which states that the function is differentiable at a point if the limit of the difference quotient as the independent variable approaches that point exists. In simpler terms, you can find the derivative of the function at that point and see if it is a finite value.

Can a function be differentiable but not continuous?

No, a function cannot be differentiable at a point where it is not continuous. This is because the definition of differentiability requires the function to be continuous at that point, as well as having a well-defined derivative.

What is the relationship between differentiability and continuity?

The relationship between differentiability and continuity is that a function must be continuous at a point in order to be differentiable at that point. In other words, a function cannot have a derivative at a point where it is not continuous.

How can the differentiability of a function be used in real-world applications?

The concept of differentiability is used in various real-world applications, such as physics, engineering, and economics. It is used to calculate rates of change, determine maximum and minimum values, and analyze the behavior of functions over time. For example, in physics, differentiability is used to calculate the velocity and acceleration of an object at a particular point in time.

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