# Derivative of $\|x\|$

$f:\mathbb{R}^n\rightarrow\mathbb{R}$ is a map $f(x)=\langle x,x\rangle$, $g:\mathbb{R}\rightarrow\mathbb{R}$ is a map $g(x)=\sqrt{x}$, so the composition $h:=g\circ f:\mathbb{R}^n\rightarrow\mathbb{R}$ is a map $x\mapsto \|x\|$, I want the derivative of $h$ at $a$, according to chain rule it should be $D(g(f(a)))\circ D f(a)$,could any one tell me now next steps?

• Since $h$ is a function of multiple variables you can find partial derivatives. So $\frac {\partial h}{\partial x_i} = \frac {dg}{df(x))}\frac {\partial f}{\partial x_i}$ – Kaster Feb 26 '13 at 18:39
• The chain rule would give $Dh(x) = Dg(f(x)) Df(x)$. You are missing a 'D'. Also note that $h$ is differentiable iff $x \neq 0$. – copper.hat Feb 26 '13 at 18:50
• @copper.hat yes, I missed – Marso Feb 27 '13 at 12:30

## 4 Answers

If $x_1,\ldots,x_n$ are coordinates on $\mathbb{R}^n$ then $f(\vec{x}) = x_1^2+\cdots+x_n^2$. It follows that $$h(\vec{x}) = \sqrt{x_1^2+\cdots+x_n^2} \equiv \left(x_1^2+\cdots+x_n^2\right)^{1/2} \, .$$

The differential of $h$ is given by the partial derivatives $\partial h/\partial x_k$. Provided that $\vec{x}$ is not the zero vector, i.e. at least one of the $x_k$ is non-zero, we can apply the chain rule:

$$\frac{\partial h}{\partial x_k} = \frac{1}{2}\times\left(x_1^2+\cdots+x_n^2\right)^{-1/2} \times 2x_k \equiv \frac{x_k}{\sqrt{x_1^2+\cdots+x_n^2}} \, .$$

If the differentiation confuses you then try it on a single variable: $\sqrt{x^2}$. Putting everything together:

$$(Dh)(\vec{x}) = \left(\frac{\partial h}{\partial x_1},\ldots,\frac{\partial h}{\partial x_n}\right) = \frac{(x_1,\ldots,x_n)}{\sqrt{x_1^2+\cdots+x_n^2}}$$

Equivalently: $(Dh)(\vec{x})=\vec{x}/||\vec{x}||.$

• A note: this is true only for $\vec{x}\neq 0$. In $\vec{x} = 0$ the function is not differentiable. – Daniel Robert-Nicoud Feb 26 '13 at 19:23
• @DanielRobert-Nicoud +1 Absolutely! Thanks for the clarification. I took that as a tacit assumption. If the OP's doing multi-variable calculus then I assumed they realise that division by zero is forbidden. I've made that explicit with a cheeky edit. Thanks again Dan. – Fly by Night Feb 26 '13 at 19:52

Here is an approach which works on any inner product space.

First the derivative of $f$ is $$Df_x(k)=(x,k)+(k,x)=2(x,k)$$ and the derivative of $g$ is $$Dg_t(s)=g'(t)s=\frac{s}{2\sqrt{t}}$$ for all $t\neq 0$.

Now the derivative of $h=g\circ f$ is, by he chain rule $$Dh_x(k)=Dg_{f(x)}\circ Df_x(k)=g'(f(x))2(x,h)=\frac{(x,k)}{\|x\|}$$ for all $x\neq 0$.

You can also think about it geometrically: perturbing $a$ by a $\delta a$ perpendicular to $a$ does not change the length of $a$ to first order. Perturbing it in the direction of $a$ increases the length by $\delta a$. Therefore the derivative is $\hat{a}=a/\|a\|$.

• But it's not. Provided $\hat{a} \neq 0$, the differential of $\hat{a} \mapsto ||\hat{a}||$ is $\hat{a}/||\hat{a}||$. – Fly by Night Feb 26 '13 at 18:52
• @FlybyNight I'm using the notation (which might not be standard outside of physics) that a hatted vector is a unit vector: $\hat{a} = a/\|a\|$. – user7530 Feb 26 '13 at 19:07
• Ah, okay! I'd seen the hat used by engineers but assumed it simply denoted a vector as in $i$-hat, $j$-hat and $k$-hat. It seems that the hat denotes, in general, a unit vector. So using $\hat{a}$ to denote the vector parallel to $\vec{a}$ and of unit length, namely $\vec{a}/||\vec{a}||$ makes perfect sense. My apologies. Thanks for teaching me something new! – Fly by Night Feb 26 '13 at 19:16

Here is a coordinate free argument:

According to the chain rule $$dh(a)=dg\bigl(f(a)\bigr)\circ df(a)\ .\tag{1}$$ Now $$f(a+X)-f(a)=(a+X)\cdot(a+X)-a\cdot a=2a\cdot X+|X|^2\tag{2}$$ and therefore $$df(a).X=2 a\cdot X\ .$$ Furthermore the formula $$g'(y)={1\over 2\sqrt{y}}\qquad(y>0)$$ can be written in the form $$dg(y).Y={1\over 2g(y)}Y\ .\tag{3}$$ Letting $y:=f(a)$ and plugging $(2)$ and $(3)$ into $(1)$ we obtain $$dh(a).X=dg\bigl(f(a)\bigr)\bigl(df(a).X\bigr)={1\over 2g\bigl(f(a)\bigr)}\bigl(2a \cdot X)\bigr)={a\cdot X\over|a|}\ .$$ It follows that $dh(a)$ can be represented by the gradient $$\nabla h(a)={a\over|a|}\qquad(a\ne0)$$ in the form $$dh(a).X=\nabla h(a)\cdot X\qquad(X\in{\mathbb R}^n)\ .$$