Positive linear maps #
This file generalises the notion of positivity to linear maps. We follow the same definition as continuous_linear_map.isPositive
but change the self-adjoinnt
property to is_symmertric
, i.e., a linear map is positive if it is symmetric and ∀ x, 0 ≤ re ⟪T x, x⟫
Main statements #
for linear maps:
linear_map.isPositive.conj_adjoint
: ifT : E →ₗ[𝕜] E
andE
is a finite-dimensional space, then for anyS : E →ₗ[𝕜] F
, we haveS.comp (T.comp S.adjoint)
is also positive.
T
is (semi-definite) positive if T
is symmetric
and ∀ x : V, 0 ≤ re ⟪x, T x⟫
Instances For
a linear projection onto U
along its complement V
is positive if
and only if U
and V
are pairwise orthogonal
the spectrum of a positive linear map is non-negative
given a symmetric linear map with a non-negative spectrum,
we can write T x = ∑ i, √α i • √α i • ⟪e i, x⟫
for any x ∈ E
,
where α i
are the eigenvalues of T
and e i
are the respective eigenvectors
that form an eigenbasis (isSymmetric.eigenvector_basis
)
given a symmetric linear map T
and a real number r
,
we can define a linear map S
such that S = T ^ r
Equations
- One or more equations did not get rendered due to their size.
Instances For
Equations
- One or more equations did not get rendered due to their size.
Instances For
the square root of a symmetric linear map can then directly be defined with re_pow
Equations
- T.sqrt h = T.rePow h (1 / 2)
Instances For
the square root of a symmetric linear map T
is written as T x = ∑ i, √ (α i) • ⟪e i, x⟫ • e i
for any x ∈ E
,
where α i
are the eigenvalues of T
and e i
are the respective eigenvectors
that form an eigenbasis (isSymmetric.eigenvector_basis
)
given a symmetric linear map T
with a non-negative spectrum,
the square root of T
composed with itself equals itself, i.e., T.sqrt ^ 2 = T
given a symmetric linear map T
, we have that its root is positive
T
is positive if and only if T
is symmetric
(which is automatic from the definition of positivity)
and has a non-negative spectrum
T
is positive if and only if there exists a
linear map S
such that T = S.adjoint * S
for spaces V
over ℂ
, it suffices to define positivity with
0 ≤ ⟪v, T v⟫_ℂ
for all v ∈ V
we have (T.adjoint.comp T).sqrt
is positive, given any linear map T
given any linear map T
and x ∈ E
we have
‖(T.adjoint.comp T).sqrt x‖ = ‖T x‖
Equations
- LinearMap.IsPositive.rePowIsInvertible T hT r = { invOf := T.rePow ⋯ (-r), invOf_mul_self := ⋯, mul_invOf_self := ⋯ }