Complex vector space in the context of Inner product space

In mathematics, an inner product space is a real or complex vector space endowed with an operation called an inner product. The inner product of two vectors in the space is a scalar, often denoted with angle brackets such as in ${\displaystyle \langle a,b\rangle }$. Inner products allow formal definitions of intuitive geometric notions, such as lengths, angles, and orthogonality (zero inner product) of vectors. Inner product spaces generalize Euclidean vector spaces, in which the inner product is the dot product or scalar product of Cartesian coordinates. Inner product spaces of infinite dimensions are widely used in functional analysis. Inner product spaces over the field of complex numbers are sometimes referred to as unitary spaces. The first usage of the concept of a vector space with an inner product is due to Giuseppe Peano, in 1898.

An inner product naturally induces an associated norm, (denoted ${\displaystyle |x|}$ and ${\displaystyle |y|}$ in the picture); so, every inner product space is a normed vector space. If this normed space is also complete (that is, a Banach space) then the inner product space is a Hilbert space. If an inner product space H is not a Hilbert space, it can be extended by completion to a Hilbert space ${\displaystyle {\overline {H}}.}$ This means that ${\displaystyle H}$ is a linear subspace of ${\displaystyle {\overline {H}},}$ the inner product of ${\displaystyle H}$ is the restriction of that of ${\displaystyle {\overline {H}},}$ and ${\displaystyle H}$ is dense in ${\displaystyle {\overline {H}}}$ for the topology defined by the norm.

In mathematics and theoretical physics (especially twistor theory), twistor space is the complex vector space of solutions of the twistor equation ${\displaystyle \nabla _{A'}^{(A}\Omega _{^{}}^{B)}=0}$. It was described in the 1960s by Roger Penrose and Malcolm MacCallum. According to Andrew Hodges, twistor space is useful for conceptualizing the way photons travel through space, using four complex numbers. He also posits that twistor space may aid in understanding the asymmetry of the weak nuclear force.

In mathematics, a self-adjoint operator on a complex vector space ${\displaystyle V}$ with inner product ${\displaystyle \langle \cdot ,\cdot \rangle }$ is a linear map ${\displaystyle A}$ (from ${\displaystyle V}$ to itself) that is its own adjoint. That is, ${\displaystyle \langle Ax,y\rangle =\langle x,Ay\rangle }$ for all ${\displaystyle x,y\in V}$. If ${\displaystyle V}$ is finite-dimensional with a given orthonormal basis, this is equivalent to the condition that the matrix of ${\displaystyle A}$ is a Hermitian matrix, i.e., equal to its conjugate transpose ${\displaystyle A^{*}}$. By the finite-dimensional spectral theorem, ${\displaystyle V}$ has an orthonormal basis such that the matrix of ${\displaystyle A}$ relative to this basis is a diagonal matrix with entries in the real numbers. This article deals with applying generalizations of this concept to operators on Hilbert spaces of arbitrary dimension.

Self-adjoint operators are used in functional analysis and quantum mechanics. In quantum mechanics their importance lies in the Dirac–von Neumann formulation of quantum mechanics, in which physical observables such as position, momentum, angular momentum and spin are represented by self-adjoint operators on a Hilbert space. Of particular significance is the Hamiltonian operator ${\displaystyle {\hat {H}}}$ defined by