Measure spaces #
The definition of a measure and a measure space are in MeasureTheory.MeasureSpaceDef
, with
only a few basic properties. This file provides many more properties of these objects.
This separation allows the measurability tactic to import only the file MeasureSpaceDef
, and to
be available in MeasureSpace
(through MeasurableSpace
).
Given a measurable space α
, a measure on α
is a function that sends measurable sets to the
extended nonnegative reals that satisfies the following conditions:
μ ∅ = 0
;μ
is countably additive. This means that the measure of a countable union of pairwise disjoint sets is equal to the measure of the individual sets.
Every measure can be canonically extended to an outer measure, so that it assigns values to all subsets, not just the measurable subsets. On the other hand, a measure that is countably additive on measurable sets can be restricted to measurable sets to obtain a measure. In this file a measure is defined to be an outer measure that is countably additive on measurable sets, with the additional assumption that the outer measure is the canonical extension of the restricted measure.
Measures on α
form a complete lattice, and are closed under scalar multiplication with ℝ≥0∞
.
Given a measure, the null sets are the sets where μ s = 0
, where μ
denotes the corresponding
outer measure (so s
might not be measurable). We can then define the completion of μ
as the
measure on the least σ
-algebra that also contains all null sets, by defining the measure to be 0
on the null sets.
Main statements #
completion
is the completion of a measure to all null measurable sets.Measure.ofMeasurable
andOuterMeasure.toMeasure
are two important ways to define a measure.
Implementation notes #
Given μ : Measure α
, μ s
is the value of the outer measure applied to s
.
This conveniently allows us to apply the measure to sets without proving that they are measurable.
We get countable subadditivity for all sets, but only countable additivity for measurable sets.
You often don't want to define a measure via its constructor. Two ways that are sometimes more convenient:
Measure.ofMeasurable
is a way to define a measure by only giving its value on measurable sets and proving the properties (1) and (2) mentioned above.OuterMeasure.toMeasure
is a way of obtaining a measure from an outer measure by showing that all measurable sets in the measurable space are Carathéodory measurable.
To prove that two measures are equal, there are multiple options:
ext
: two measures are equal if they are equal on all measurable sets.ext_of_generateFrom_of_iUnion
: two measures are equal if they are equal on a π-system generating the measurable sets, if the π-system contains a spanning increasing sequence of sets where the measures take finite value (in particular the measures are σ-finite). This is a special case of the more generalext_of_generateFrom_of_cover
ext_of_generate_finite
: two finite measures are equal if they are equal on a π-system generating the measurable sets. This is a special case ofext_of_generateFrom_of_iUnion
usingC ∪ {univ}
, but is easier to work with.
A MeasureSpace
is a class that is a measurable space with a canonical measure.
The measure is denoted volume
.
References #
- https://en.wikipedia.org/wiki/Measure_(mathematics)
- https://en.wikipedia.org/wiki/Complete_measure
- https://en.wikipedia.org/wiki/Almost_everywhere
Tags #
measure, almost everywhere, measure space, completion, null set, null measurable set
Equations
- ⋯ = ⋯
See also MeasureTheory.ae_restrict_uIoc_iff
.
The measure of an a.e. disjoint union (even uncountable) of null-measurable sets is at least the sum of the measures of the sets.
The measure of a disjoint union (even uncountable) of measurable sets is at least the sum of the measures of the sets.
If s
is a countable set, then the measure of its preimage can be found as the sum of measures
of the fibers f ⁻¹' {y}
.
If s
is a Finset
, then the measure of its preimage can be found as the sum of measures
of the fibers f ⁻¹' {y}
.
If the measure of the symmetric difference of two sets is finite, then one has infinite measure if and only if the other one does.
If the measure of the symmetric difference of two sets is finite, then one has finite measure if and only if the other one does.
If s ⊆ t
, μ t ≤ μ s
, μ t ≠ ∞
, and s
is measurable, then s =ᵐ[μ] t
.
Pigeonhole principle for measure spaces: if ∑' i, μ (s i) > μ univ
, then
one of the intersections s i ∩ s j
is not empty.
Pigeonhole principle for measure spaces: if s
is a Finset
and
∑ i ∈ s, μ (t i) > μ univ
, then one of the intersections t i ∩ t j
is not empty.
If two sets s
and t
are included in a set u
, and μ s + μ t > μ u
,
then s
intersects t
. Version assuming that t
is measurable.
If two sets s
and t
are included in a set u
, and μ s + μ t > μ u
,
then s
intersects t
. Version assuming that s
is measurable.
Continuity from below: the measure of the union of a directed sequence of (not necessarily measurable) sets is the supremum of the measures.
Alias of Directed.measure_iUnion
.
Continuity from below: the measure of the union of a directed sequence of (not necessarily measurable) sets is the supremum of the measures.
Continuity from below:
the measure of the union of a monotone family of sets is equal to the supremum of their measures.
The theorem assumes that the atTop
filter on the index set is countably generated,
so it works for a family indexed by a countable type, as well as ℝ
.
Continuity from below: the measure of the union of a sequence of (not necessarily measurable) sets is the supremum of the measures of the partial unions.
Alias of MeasureTheory.measure_iUnion_eq_iSup_accumulate
.
Continuity from below: the measure of the union of a sequence of (not necessarily measurable) sets is the supremum of the measures of the partial unions.
Continuity from above: the measure of the intersection of a decreasing sequence of measurable sets is the infimum of the measures.
Continuity from above: the measure of the intersection of a sequence of measurable sets is the infimum of the measures of the partial intersections.
Continuity from below: the measure of the union of an increasing sequence of (not necessarily measurable) sets is the limit of the measures.
Alias of MeasureTheory.tendsto_measure_iUnion_atTop
.
Continuity from below: the measure of the union of an increasing sequence of (not necessarily measurable) sets is the limit of the measures.
Continuity from below: the measure of the union of a sequence of (not necessarily measurable) sets is the limit of the measures of the partial unions.
Alias of MeasureTheory.tendsto_measure_iUnion_accumulate
.
Continuity from below: the measure of the union of a sequence of (not necessarily measurable) sets is the limit of the measures of the partial unions.
Continuity from above: the measure of the intersection of a decreasing sequence of measurable sets is the limit of the measures.
Continuity from above: the measure of the intersection of a sequence of measurable sets such that one has finite measure is the limit of the measures of the partial intersections.
The measure of the intersection of a decreasing sequence of measurable sets indexed by a linear order with first countable topology is the limit of the measures.
Obtain a measure by giving an outer measure where all sets in the σ-algebra are Carathéodory measurable.
Equations
- m.toMeasure h = MeasureTheory.Measure.ofMeasurable (fun (s : Set α) (x : MeasurableSet s) => m s) ⋯ ⋯
Instances For
If u
is a superset of t
with the same (finite) measure (both sets possibly non-measurable),
then for any measurable set s
one also has μ (t ∩ s) = μ (u ∩ s)
.
The measurable superset toMeasurable μ t
of t
(which has the same measure as t
)
satisfies, for any measurable set s
, the equality μ (toMeasurable μ t ∩ s) = μ (u ∩ s)
.
Here, we require that the measure of t
is finite. The conclusion holds without this assumption
when the measure is s-finite (for example when it is σ-finite),
see measure_toMeasurable_inter_of_sFinite
.
The ℝ≥0∞
-module of measures #
Equations
- MeasureTheory.Measure.instZero = { zero := { toOuterMeasure := 0, m_iUnion := ⋯, trim_le := ⋯ } }
Equations
- ⋯ = ⋯
Equations
- MeasureTheory.Measure.instInhabited = { default := 0 }
Equations
- MeasureTheory.Measure.instAdd = { add := fun (μ₁ μ₂ : MeasureTheory.Measure α) => { toOuterMeasure := μ₁.toOuterMeasure + μ₂.toOuterMeasure, m_iUnion := ⋯, trim_le := ⋯ } }
Equations
- MeasureTheory.Measure.instSMul = { smul := fun (c : R) (μ : MeasureTheory.Measure α) => { toOuterMeasure := c • μ.toOuterMeasure, m_iUnion := ⋯, trim_le := ⋯ } }
Equations
- ⋯ = ⋯
Equations
- ⋯ = ⋯
Equations
- ⋯ = ⋯
Equations
- ⋯ = ⋯
Equations
- MeasureTheory.Measure.instMulAction = Function.Injective.mulAction MeasureTheory.Measure.toOuterMeasure ⋯ ⋯
Equations
- MeasureTheory.Measure.instAddCommMonoid = Function.Injective.addCommMonoid MeasureTheory.Measure.toOuterMeasure ⋯ ⋯ ⋯ ⋯
Coercion to function as an additive monoid homomorphism.
Equations
- MeasureTheory.Measure.coeAddHom = { toFun := DFunLike.coe, map_zero' := ⋯, map_add' := ⋯ }
Instances For
Equations
- MeasureTheory.Measure.instDistribMulAction = Function.Injective.distribMulAction { toFun := MeasureTheory.Measure.toOuterMeasure, map_zero' := ⋯, map_add' := ⋯ } ⋯ ⋯
Equations
- MeasureTheory.Measure.instModule = Function.Injective.module R { toFun := MeasureTheory.Measure.toOuterMeasure, map_zero' := ⋯, map_add' := ⋯ } ⋯ ⋯
The complete lattice of measures #
Measures are partially ordered.
Equations
- MeasureTheory.Measure.instPartialOrder = PartialOrder.mk ⋯
Equations
- ⋯ = ⋯
Equations
- MeasureTheory.Measure.instInfSet = { sInf := fun (m : Set (MeasureTheory.Measure α)) => (sInf (MeasureTheory.Measure.toOuterMeasure '' m)).toMeasure ⋯ }
Equations
- MeasureTheory.Measure.instCompleteSemilatticeInf = CompleteSemilatticeInf.mk ⋯ ⋯
Equations
- MeasureTheory.Measure.instCompleteLattice = CompleteLattice.mk ⋯ ⋯ ⋯ ⋯ ⋯ ⋯
Equations
- ⋯ = ⋯
Pushforward and pullback #
Lift a linear map between OuterMeasure
spaces such that for each measure μ
every measurable
set is caratheodory-measurable w.r.t. f μ
to a linear map between Measure
spaces.
Equations
- MeasureTheory.Measure.liftLinear f hf = { toFun := fun (μ : MeasureTheory.Measure α) => (f μ.toOuterMeasure).toMeasure ⋯, map_add' := ⋯, map_smul' := ⋯ }
Instances For
The pushforward of a measure as a linear map. It is defined to be 0
if f
is not
a measurable function.
Equations
- MeasureTheory.Measure.mapₗ f = if hf : Measurable f then MeasureTheory.Measure.liftLinear (MeasureTheory.OuterMeasure.map f) ⋯ else 0
Instances For
The pushforward of a measure. It is defined to be 0
if f
is not an almost everywhere
measurable function.
Instances For
We can evaluate the pushforward on measurable sets. For non-measurable sets, see
MeasureTheory.Measure.le_map_apply
and MeasurableEquiv.map_apply
.
If map f μ = μ
, then the measure of the preimage of any null measurable set s
is equal to the measure of s
.
Note that this lemma does not assume (a.e.) measurability of f
.
Even if s
is not measurable, we can bound map f μ s
from below.
See also MeasurableEquiv.map_apply
.
Even if s
is not measurable, map f μ s = 0
implies that μ (f ⁻¹' s) = 0
.
Pullback of a Measure
as a linear map. If f
sends each measurable set to a measurable
set, then for each measurable set s
we have comapₗ f μ s = μ (f '' s)
.
Note that if f
is not injective, this definition assigns Set.univ
measure zero.
If the linearity is not needed, please use comap
instead, which works for a larger class of
functions. comapₗ
is an auxiliary definition and most lemmas deal with comap.
Equations
- One or more equations did not get rendered due to their size.
Instances For
Pullback of a Measure
. If f
sends each measurable set to a null-measurable set,
then for each measurable set s
we have comap f μ s = μ (f '' s)
.
Note that if f
is not injective, this definition assigns Set.univ
measure zero.
Equations
- One or more equations did not get rendered due to their size.
Instances For
Sum of an indexed family of measures.
Equations
- MeasureTheory.Measure.sum f = (MeasureTheory.OuterMeasure.sum fun (i : ι) => (f i).toOuterMeasure).toMeasure ⋯
Instances For
For the next theorem, the countability assumption is necessary. For a counterexample, consider
an uncountable space, with a distinguished point x₀
, and the sigma-algebra made of countable sets
not containing x₀
, and their complements. All points but x₀
are measurable.
Consider the sum of the Dirac masses at points different from x₀
, and s = x₀
. For any Dirac mass
δ_x
, we have δ_x (x₀) = 0
, so ∑' x, δ_x (x₀) = 0
. On the other hand, the measure sum δ_x
gives mass one to each point different from x₀
, so it gives infinite mass to any measurable set
containing x₀
(as such a set is uncountable), and by outer regularity one get sum δ_x {x₀} = ∞
.
Alias of MeasureTheory.Measure.sum_of_isEmpty
.
Absolute continuity #
We say that μ
is absolutely continuous with respect to ν
, or that μ
is dominated by ν
,
if ν(A) = 0
implies that μ(A) = 0
.
Instances For
We say that μ
is absolutely continuous with respect to ν
, or that μ
is dominated by ν
,
if ν(A) = 0
implies that μ(A) = 0
.
Equations
- MeasureTheory.«term_≪_» = Lean.ParserDescr.trailingNode `MeasureTheory.term_≪_ 50 50 (Lean.ParserDescr.binary `andthen (Lean.ParserDescr.symbol " ≪ ") (Lean.ParserDescr.cat `term 51))
Instances For
Equations
- ⋯ = ⋯
Alias of the forward direction of MeasureTheory.Measure.ae_le_iff_absolutelyContinuous
.
Alias of the reverse direction of MeasureTheory.Measure.ae_le_iff_absolutelyContinuous
.
Alias of the reverse direction of MeasureTheory.Measure.ae_le_iff_absolutelyContinuous
.
Alias of the reverse direction of MeasureTheory.Measure.ae_le_iff_absolutelyContinuous
.
Quasi measure preserving maps (a.k.a. non-singular maps) #
A map f : α → β
is said to be quasi measure preserving (a.k.a. non-singular) w.r.t. measures
μa
and μb
if it is measurable and μb s = 0
implies μa (f ⁻¹' s) = 0
.
- measurable : Measurable f
- absolutelyContinuous : (MeasureTheory.Measure.map f μa).AbsolutelyContinuous μb
Instances For
The preimage of a null measurable set under a (quasi) measure preserving map is a null measurable set.
For a quasi measure preserving self-map f
, if a null measurable set s
is a.e. invariant,
then it is a.e. equal to a measurable invariant set.
The filter of sets s
such that sᶜ
has finite measure.
Equations
- μ.cofinite = Filter.comk (fun (x : Set α) => μ x < ⊤) ⋯ ⋯ ⋯
Instances For
Equations
- ⋯ = ⋯
Equations
- ⋯ = ⋯
Interactions of measurable equivalences and measures
If we map a measure along a measurable equivalence, we can compute the measure on all sets (not just the measurable ones).