# Inner product space

An *inner product* space is a vector space *V* over the field *F* together with an *inner product*, that is a map

In the following properties, which result almost immediately from the definition of an inner product, *x*, *y* and z are arbitrary vectors, and a and b are arbitrary scalars.

Some authors, especially in physics and matrix algebra, prefer to define inner products and sesquilinear forms with linearity in the second argument rather than the first. Then the first argument becomes conjugate linear, rather than the second.

This sequence is a Cauchy sequence for the norm induced by the preceding inner product, which does not converge to a *continuous* function.

Every inner product space induces a norm, called its *canonical norm*, that is defined by

So, every general property of normed vector spaces applies to inner product spaces. In particular, one has the following properties:

The last equality is similar to the formula expressing a linear functional in terms of its real part.

Using an infinite-dimensional analog of the Gram-Schmidt process one may show:

Using the Hausdorff maximal principle and the fact that in a complete inner product space orthogonal projection onto linear subspaces is well-defined, one may also show that

The two previous theorems raise the question of whether all inner product spaces have an orthonormal basis. The answer, it turns out is negative. This is a non-trivial result, and is proved below. The following proof is taken from Halmos's *A Hilbert Space Problem Book* (see the references).^{[citation needed]}

From the point of view of inner product space theory, there is no need to distinguish between two spaces which are isometrically isomorphic. The spectral theorem provides a canonical form for symmetric, unitary and more generally normal operators on finite dimensional inner product spaces. A generalization of the spectral theorem holds for continuous normal operators in Hilbert spaces.^{[13]}

Any of the axioms of an inner product may be weakened, yielding generalized notions. The generalizations that are closest to inner products occur where bilinearity and conjugate symmetry are retained, but positive-definiteness is weakened.

This construction is used in numerous contexts. The Gelfand–Naimark–Segal construction is a particularly important example of the use of this technique. Another example is the representation of semi-definite kernels on arbitrary sets.

The inner product and outer product should not be confused with the interior product and exterior product, which are instead operations on vector fields and differential forms, or more generally on the exterior algebra.

As a further complication, in geometric algebra the inner product and the *exterior* (Grassmann) product are combined in the geometric product (the Clifford product in a Clifford algebra) – the inner product sends two vectors (1-vectors) to a scalar (a 0-vector), while the exterior product sends two vectors to a bivector (2-vector) – and in this context the exterior product is usually called the *outer product* (alternatively, *wedge product*). The inner product is more correctly called a *scalar* product in this context, as the nondegenerate quadratic form in question need not be positive definite (need not be an inner product).