Definition:Inner Product

Definition

Let $\GF$ be a subfield of $\C$.

Let $V$ be a vector space over $\GF$.

An inner product is a mapping $\innerprod \cdot \cdot: V \times V \to \GF$ that satisfies the following properties:

$(1)$	$:$	Conjugate Symmetry	$\ds \forall x, y \in V:$	$\ds \quad \innerprod x y = \overline {\innerprod y x} $
$(2)$	$:$	Linearity in first argument	$\ds \forall x, y \in V, \forall a \in \GF:$	$\ds \quad \innerprod {a x + y} z = a \innerprod x z + \innerprod y z $
$(3)$	$:$	Non-Negative Definiteness	$\ds \forall x \in V:$	$\ds \quad \innerprod x x \in \R_{\ge 0} $
$(4)$	$:$	Positiveness	$\ds \forall x \in V:$	$\ds \quad \innerprod x x = 0 \implies x = \mathbf 0_V $

That is, an inner product is a semi-inner product with the additional condition $(4)$.

If $\GF$ is a subfield of the field of real numbers $\R$, it follows from Complex Number equals Conjugate iff Wholly Real that $\overline {\innerprod y x} = \innerprod y x$ for all $x, y \in V$.

Then $(1)$ above may be replaced by:

$(1')$

$:$

$\ds \forall x, y \in V:$

$\ds \innerprod x y = \innerprod y x $

An inner product space is a vector space together with an associated inner product.

$\innerprod x y$ is also denoted as $\left \langle {x; y} \right \rangle$.

If there is more than one vector space under consideration, then the notation $\innerprod x y_V$ for a vector space $V$ is commonplace.

The most well-known example of an inner product is the dot product (see Dot Product is Inner Product).

\((1)\)	$:$	Conjugate Symmetry	\(\ds \forall x, y \in V:\)	\(\ds \quad \innerprod x y = \overline {\innerprod y x} \)
\((2)\)	$:$	Linearity in first argument	\(\ds \forall x, y \in V, \forall a \in \GF:\)	\(\ds \quad \innerprod {a x + y} z = a \innerprod x z + \innerprod y z \)
\((3)\)	$:$	Non-Negative Definiteness	\(\ds \forall x \in V:\)	\(\ds \quad \innerprod x x \in \R_{\ge 0} \)
\((4)\)	$:$	Positiveness	\(\ds \forall x \in V:\)	\(\ds \quad \innerprod x x = 0 \implies x = \mathbf 0_V \)