# Dot/inner product

## In words...

An inner product is a bilinear function of two vectors returning a real number that represents the level of alignement of these vectors.

The most common inner product is the Euclidean standard dot product for Euclidean spaces.

## In pictures...

## In maths...

In a vector space $\X$, an inner product $\inner{\cdot}{\cdot}_{\X}$ (or simply $\inner{\cdot}{\cdot}$ when the vector space is clear from context) is a function from $\X^2$ to $\R$ which satisfies, for all $(u,v) \in\X^2$,

- (Symmetry) $\inner{u}{v} = \inner{v}{u}$
- (Linearity in the first argument) $\inner{\lambda u}{v} = \lambda \inner{u}{v}$ for all scalars $\lambda\in\R$
- (Linearity in the first argument) $\inner{u+v}{w} = \inner{u}{w} + \inner{v}{w}$ for all vector $w\in\X$
- (Positive semi-definiteness) $\inner{u}{u} \geq 0$
- (Positive definiteness) $\inner{u}{u} = 0 \ \Rightarrow\ u=0$

Any inner product induces a norm as
$$
\|x\| = \sqrt{\inner{x}{x}}.
$$

### Euclidean dot product in $\R^d$

The standard dot product in Euclidean space $\R^d$,
$$
\inner{\g u}{\g v} = \g u^T \g v = \sum_{i=1}^d u_iv_i,
$$
is an inner product.

### Inner product of functions

The standard inner product in the Hilbert space $L^2(\X)$ of square integrable functions $f : \X \rightarrow \R$ is defined as
$$
\inner{f}{g}_{L^2(\X)} = \int_{\X} f(\g x)g(\g x) \ d\g x .
$$

### Cauchy-Schwarz inequality

Inner products satisfy the Cauchy-Schwarz inequality: for all $(u,v) \in\X^2$,
$$
\left|\inner{u}{v}_{\X} \right|^2 \leq \inner{u}{u}_{\X} \inner{v}{v}_{\X} ,
$$
or, with the norm $\|\cdot\|_{\X}$ induced by the inner product as above,
$$
\left|\inner{u}{v}_{\X} \right| \leq \|u\|_{\X} \|v\|_{\X} .
$$