Vector valued measures #
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This file defines vector valued measures, which are σ-additive functions from a set to a add monoid
M
such that it maps the empty set and non-measurable sets to zero. In the case
that M = ℝ
, we called the vector measure a signed measure and write signed_measure α
.
Similarly, when M = ℂ
, we call the measure a complex measure and write complex_measure α
.
Main definitions #
measure_theory.vector_measure
is a vector valued, σ-additive function that maps the empty and non-measurable set to zero.measure_theory.vector_measure.map
is the pushforward of a vector measure along a function.measure_theory.vector_measure.restrict
is the restriction of a vector measure on some set.
Notation #
v ≤[i] w
means that the vector measurev
restricted on the seti
is less than or equal to the vector measurew
restricted oni
, i.e.v.restrict i ≤ w.restrict i
.
Implementation notes #
We require all non-measurable sets to be mapped to zero in order for the extensionality lemma to only compare the underlying functions for measurable sets.
We use has_sum
instead of tsum
in the definition of vector measures in comparison to measure
since this provides summablity.
Tags #
vector measure, signed measure, complex measure
- measure_of' : set α → M
- empty' : self.measure_of' ∅ = 0
- not_measurable' : ∀ ⦃i : set α⦄, ¬measurable_set i → self.measure_of' i = 0
- m_Union' : ∀ ⦃f : ℕ → set α⦄, (∀ (i : ℕ), measurable_set (f i)) → pairwise (disjoint on f) → has_sum (λ (i : ℕ), self.measure_of' (f i)) (self.measure_of' (⋃ (i : ℕ), f i))
A vector measure on a measurable space α
is a σ-additive M
-valued function (for some M
an add monoid) such that the empty set and non-measurable sets are mapped to zero.
Instances for measure_theory.vector_measure
- measure_theory.vector_measure.has_sizeof_inst
- measure_theory.vector_measure.has_coe_to_fun
- measure_theory.vector_measure.has_smul
- measure_theory.vector_measure.has_zero
- measure_theory.vector_measure.inhabited
- measure_theory.vector_measure.has_add
- measure_theory.vector_measure.add_comm_monoid
- measure_theory.vector_measure.has_neg
- measure_theory.vector_measure.has_sub
- measure_theory.vector_measure.add_comm_group
- measure_theory.vector_measure.distrib_mul_action
- measure_theory.vector_measure.module
- measure_theory.vector_measure.partial_order
- measure_theory.vector_measure.covariant_add_le
A signed_measure
is a ℝ
-vector measure.
A complex_measure
is a ℂ
-vector_measure.
Equations
Given a real number r
and a signed measure s
, smul r s
is the signed
measure corresponding to the function r • s
.
Equations
- measure_theory.vector_measure.smul r v = {measure_of' := r • ⇑v, empty' := _, not_measurable' := _, m_Union' := _}
Equations
Equations
- measure_theory.vector_measure.has_zero = {zero := {measure_of' := 0, empty' := _, not_measurable' := _, m_Union' := _}}
Equations
The sum of two vector measure is a vector measure.
Equations
- v.add w = {measure_of' := ⇑v + ⇑w, empty' := _, not_measurable' := _, m_Union' := _}
Equations
Equations
- measure_theory.vector_measure.add_comm_monoid = function.injective.add_comm_monoid coe_fn measure_theory.vector_measure.coe_injective measure_theory.vector_measure.coe_zero measure_theory.vector_measure.coe_add measure_theory.vector_measure.add_comm_monoid._proof_2
coe_fn
is an add_monoid_hom
.
Equations
The negative of a vector measure is a vector measure.
Equations
- v.neg = {measure_of' := -⇑v, empty' := _, not_measurable' := _, m_Union' := _}
Equations
The difference of two vector measure is a vector measure.
Equations
- v.sub w = {measure_of' := ⇑v - ⇑w, empty' := _, not_measurable' := _, m_Union' := _}
Equations
Equations
- measure_theory.vector_measure.add_comm_group = function.injective.add_comm_group coe_fn measure_theory.vector_measure.add_comm_group._proof_4 measure_theory.vector_measure.add_comm_group._proof_5 measure_theory.vector_measure.add_comm_group._proof_6 measure_theory.vector_measure.coe_neg measure_theory.vector_measure.coe_sub measure_theory.vector_measure.add_comm_group._proof_7 measure_theory.vector_measure.add_comm_group._proof_8
Equations
- measure_theory.vector_measure.module = function.injective.module R measure_theory.vector_measure.coe_fn_add_monoid_hom measure_theory.vector_measure.coe_injective measure_theory.vector_measure.module._proof_1
A finite measure coerced into a real function is a signed measure.
Equations
- μ.to_signed_measure = {measure_of' := λ (i : set α), ite (measurable_set i) (μ.to_outer_measure.measure_of i).to_real 0, empty' := _, not_measurable' := _, m_Union' := _}
A measure is a vector measure over ℝ≥0∞
.
Equations
- μ.to_ennreal_vector_measure = {measure_of' := λ (i : set α), ite (measurable_set i) (⇑μ i) 0, empty' := _, not_measurable' := _, m_Union' := _}
A vector measure over ℝ≥0∞
is a measure.
Equations
- v.ennreal_to_measure = measure_theory.measure.of_measurable (λ (s : set α) (_x : measurable_set s), ⇑v s) _ _
The equiv between vector_measure α ℝ≥0∞
and measure α
formed by
measure_theory.vector_measure.ennreal_to_measure
and
measure_theory.measure.to_ennreal_vector_measure
.
Equations
- measure_theory.vector_measure.equiv_measure = {to_fun := measure_theory.vector_measure.ennreal_to_measure _inst_1, inv_fun := measure_theory.measure.to_ennreal_vector_measure _inst_1, left_inv := _, right_inv := _}
The pushforward of a vector measure along a function.
Equations
- v.map f = dite (measurable f) (λ (hf : measurable f), {measure_of' := λ (s : set β), ite (measurable_set s) (⇑v (f ⁻¹' s)) 0, empty' := _, not_measurable' := _, m_Union' := _}) (λ (hf : ¬measurable f), 0)
Given a vector measure v
on M
and a continuous add_monoid_hom f : M → N
, f ∘ v
is a
vector measure on N
.
Equations
- v.map_range f hf = {measure_of' := λ (s : set α), ⇑f (⇑v s), empty' := _, not_measurable' := _, m_Union' := _}
Given a continuous add_monoid_hom f : M → N
, map_range_hom
is the add_monoid_hom mapping the
vector measure v
on M
to the vector measure f ∘ v
on N
.
Equations
- measure_theory.vector_measure.map_range_hom f hf = {to_fun := λ (v : measure_theory.vector_measure α M), v.map_range f hf, map_zero' := _, map_add' := _}
Given a continuous linear map f : M → N
, map_rangeₗ
is the linear map mapping the
vector measure v
on M
to the vector measure f ∘ v
on N
.
Equations
- measure_theory.vector_measure.map_rangeₗ f hf = {to_fun := λ (v : measure_theory.vector_measure α M), v.map_range f.to_add_monoid_hom hf, map_add' := _, map_smul' := _}
The restriction of a vector measure on some set.
Equations
- v.restrict i = dite (measurable_set i) (λ (hi : measurable_set i), {measure_of' := λ (s : set α), ite (measurable_set s) (⇑v (s ∩ i)) 0, empty' := _, not_measurable' := _, m_Union' := _}) (λ (hi : ¬measurable_set i), 0)
vector_measure.map
as an additive monoid homomorphism.
Equations
- measure_theory.vector_measure.map_gm f = {to_fun := λ (v : measure_theory.vector_measure α M), v.map f, map_zero' := _, map_add' := _}
vector_measure.restrict
as an additive monoid homomorphism.
Equations
- measure_theory.vector_measure.restrict_gm i = {to_fun := λ (v : measure_theory.vector_measure α M), v.restrict i, map_zero' := _, map_add' := _}
vector_measure.map
as a linear map.
Equations
- measure_theory.vector_measure.mapₗ f = {to_fun := λ (v : measure_theory.vector_measure α M), v.map f, map_add' := _, map_smul' := _}
vector_measure.restrict
as an additive monoid homomorphism.
Equations
- measure_theory.vector_measure.restrictₗ i = {to_fun := λ (v : measure_theory.vector_measure α M), v.restrict i, map_add' := _, map_smul' := _}
Vector measures over a partially ordered monoid is partially ordered.
This definition is consistent with measure.partial_order
.
Equations
- measure_theory.vector_measure.partial_order = {le := λ (v w : measure_theory.vector_measure α M), ∀ (i : set α), measurable_set i → ⇑v i ≤ ⇑w i, lt := preorder.lt._default (λ (v w : measure_theory.vector_measure α M), ∀ (i : set α), measurable_set i → ⇑v i ≤ ⇑w i), le_refl := _, le_trans := _, lt_iff_le_not_le := _, le_antisymm := _}
A vector measure v
is absolutely continuous with respect to a measure μ
if for all sets
s
, μ s = 0
, we have v s = 0
.
Two vector measures v
and w
are said to be mutually singular if there exists a measurable
set s
, such that for all t ⊆ s
, v t = 0
and for all t ⊆ sᶜ
, w t = 0
.
We note that we do not require the measurability of t
in the definition since this makes it easier
to use. This is equivalent to the definition which requires measurability. To prove
mutually_singular
with the measurability condition, use
measure_theory.vector_measure.mutually_singular.mk
.
Restriction of a vector measure onto a sub-σ-algebra.
Equations
- v.trim hle = {measure_of' := λ (i : set α), ite (measurable_set i) (⇑v i) 0, empty' := _, not_measurable' := _, m_Union' := _}
The underlying function for signed_measure.to_measure_of_zero_le
.
Equations
- s.to_measure_of_zero_le' i hi j hj = ↑⟨⇑(measure_theory.vector_measure.restrict s i) j, _⟩
Given a signed measure s
and a positive measurable set i
, to_measure_of_zero_le
provides the measure, mapping measurable sets j
to s (i ∩ j)
.
Equations
- s.to_measure_of_zero_le i hi₁ hi₂ = measure_theory.measure.of_measurable (s.to_measure_of_zero_le' i hi₂) _ _
Instances for measure_theory.signed_measure.to_measure_of_zero_le
Given a signed measure s
and a negative measurable set i
, to_measure_of_le_zero
provides the measure, mapping measurable sets j
to -s (i ∩ j)
.
Equations
- s.to_measure_of_le_zero i hi₁ hi₂ = (-s).to_measure_of_zero_le i hi₁ _
Instances for measure_theory.signed_measure.to_measure_of_le_zero
signed_measure.to_measure_of_zero_le
is a finite measure.
signed_measure.to_measure_of_le_zero
is a finite measure.