Symmetric linear maps in an inner product space #
This file defines and proves basic theorems about symmetric not necessarily bounded operators
on an inner product space, i.e linear maps T : E → E
such that ∀ x y, ⟪T x, y⟫ = ⟪x, T y⟫
.
In comparison to IsSelfAdjoint
, this definition works for non-continuous linear maps, and
doesn't rely on the definition of the adjoint, which allows it to be stated in non-complete space.
Main definitions #
LinearMap.IsSymmetric
: a (not necessarily bounded) operator on an inner product space is symmetric, if for allx
,y
, we have⟪T x, y⟫ = ⟪x, T y⟫
Main statements #
IsSymmetric.continuous
: if a symmetric operator is defined on a complete space, then it is automatically continuous.
Tags #
self-adjoint, symmetric
Symmetric operators #
A (not necessarily bounded) operator on an inner product space is symmetric, if for all
x
, y
, we have ⟪T x, y⟫ = ⟪x, T y⟫
.
Instances For
An operator T
on an inner product space is symmetric if and only if it is
LinearMap.IsSelfAdjoint
with respect to the sesquilinear form given by the inner product.
The Hellinger--Toeplitz theorem: if a symmetric operator is defined on a complete space, then it is automatically continuous.
For a symmetric operator T
, the function fun x ↦ ⟪T x, x⟫
is real-valued.
If a symmetric operator preserves a submodule, its restriction to that submodule is symmetric.
A linear operator on a complex inner product space is symmetric precisely when
⟪T v, v⟫_ℂ
is real for all v.
Polarization identity for symmetric linear maps.
See inner_map_polarization
for the complex version without the symmetric assumption.
A symmetric linear map T
is zero if and only if ⟪T x, x⟫_ℝ = 0
for all x
.
See inner_map_self_eq_zero
for the complex version without the symmetric assumption.