Prove that the functin is differentiable at (0, ,0).

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SUMMARY

The discussion centers on proving the differentiability of a function \( f: B_{r}(\textbf{0}) \rightarrow \textbf{R} \) at the point \( \textbf{0} \) under the condition that \( |f(\textbf{x})| \leq ||\textbf{x}||^{\alpha} \) for \( \alpha > 1 \). The participants emphasize the necessity of demonstrating the continuity of the first-order partial derivatives at \( \textbf{0} \) to establish differentiability. A theorem referenced states that if the first-order partial derivatives exist and are continuous at a point, then the function is differentiable at that point. The conversation also explores the implications when \( \alpha = 1 \).

PREREQUISITES
  • Understanding of vector-valued functions and their differentiability.
  • Familiarity with the concept of norms in \( \mathbb{R}^n \).
  • Knowledge of first-order partial derivatives and their continuity.
  • Ability to apply limits in the context of differentiability.
NEXT STEPS
  • Study the continuity of first-order partial derivatives in vector-valued functions.
  • Learn about the implications of differentiability when \( \alpha = 1 \).
  • Explore the definition of differentiability and its application in various contexts.
  • Review theorems related to differentiability and continuity in multivariable calculus.
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Students and educators in advanced calculus, particularly those focusing on multivariable functions and differentiability, as well as mathematicians seeking to deepen their understanding of vector calculus concepts.

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Homework Statement



Let r>0, and let f be a function from B_{r}(\textbf{0}) \rightarrow \textbf{R}, and suppose that there exists an \alpha > 1 such that |f(\textbf{x})| \leq ||\textbf{x}||^{\alpha} for all \textbf{x} \in B_{r}(\textbf{0}). Prove that f is differentiable at 0.

What happens to this result when \alpha = 1?

Homework Equations


Note:

The characters in bold are vectors.

B_{r}(\textbf{0}) is an open ball in R^{n} about 0

The symbol ||.|| represents the norm of the vector.

Some definitions of differentiability of a function

A function f from R \rightarrow R^{n} is differentiable if

lim_{\textbf{h} \rightarrow \textbf{0}} \frac{f(\textbf{0} + \textbf{h}) - f(\textbf{0}) - Df(\textbf{a})(\textbf{h})}{||\textbf{h}||} = \textbf{0}.

Where Df(\textbf{a}) is the matrix of first order partials. In our case, since the function is from R to R^n, this would be the gradient of f.

The Attempt at a Solution



The started this problem by computing that the first order partials exists. But that by itself is not sufficient to concluded that f is differentiable at 0. The next step would be to show that the first-order partials of f are continuous at 0. This is where I got stuck.
 
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Can you explain what you are thinking about this problem?
 
LeonhardEuler said:
Can you explain what you are thinking about this problem?

Hi Euler,

Thank you for your reply.

There's a theorem in my textbook that says that if the first-order partial derivatives of a vector-valued function f exists at a, and if these first-order partial derivatives are continuous at a, then f is differentiable at a.

I know how to show the existence of the first-order partial derivatives of f at 0, but I'm having trouble proving that they are continuous at 0. Any insights?
 
I see how you are stuck. Have you thought about avoiding this theorem, and working directly from the definition of the derivative?
 
LeonhardEuler said:
I see how you are stuck. Have you thought about avoiding this theorem, and working directly from the definition of the derivative?

You mean using:

lim_{\textbf{h} \rightarrow \textbf{0}} \frac{f(\textbf{0} + \textbf{h}) - f(\textbf{0}) - Df(\textbf{a})(\textbf{h})}{||\textbf{h}||} = \textbf{0}.

directly?
 
yes.
 

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