# Multivariable Calculus: Applications of Grad (and the Chain Rule?)

1. May 10, 2010

1. The problem statement, all variables and given/known data
We say that a differentiable function $$f : \mathbb{R}^n \rightarrow \mathbb{R}$$ is homogenous of degree p if, for every $$\mathbf{x} \in \mathbb{R}^n$$ and every a>0,
$$f(a\mathbf{x}) = a^pf(\mathbf{x}).$$

Show that, if f is homogenous, then $$\mathbf{x} \cdot \nabla f(\mathbf{x}) = p f(\mathbf{x})$$ .

2. Relevant equations
The chain rule (not sure if I need it): $$\displaystyle \frac{d}{dt} f(\mathbf{x}(t)) = \Sigma_{i = 1}^{n} f_{x_i}\dot{x_i} = \dot{\mathbf{x}} \cdot \nabla f$$
3. The attempt at a solution

Well, I see the resemblance between the rightmost hand side of the chain rule I wrote down, but I don't really understand how the chain rule is applied in this situation, seeing as there isn't anything about x being a function of something else here.

Any ideas?
Cheers.

Last edited: May 10, 2010
2. May 10, 2010

### vela

Staff Emeritus
Try differentiating

$$f(a\mathbf{x}) = a^pf(\mathbf{x})$$

with respect to a.

3. May 11, 2010

$$\frac{\partial}{\partial a} f(a \mathbf{x}) = pa^{p-1}f(\mathbf{x})$$

Okay. I'm still clueless.

EDIT:

Hang on. $$\frac{\partial}{\partial a} f(a \mathbf{x}) = \frac{\partial}{\partial a} (a \mathbf{x}) \frac{\partial}{\partial \mathbf{x}} f(a\mathbf{x}) = \mathbf{x} \cdot \nabla f (a \mathbf{x})$$ (if you'll forgive the abuse of notation), right?

Last edited: May 11, 2010
4. May 11, 2010

### vela

Staff Emeritus
Good. Now let a=1.