Documentation

Mathlib.MeasureTheory.Measure.Prod

The product measure #

In this file we define and prove properties about the binary product measure. If α and β have s-finite measures μ resp. ν then α × β can be equipped with a s-finite measure μ.prod ν that satisfies (μ.prod ν) s = ∫⁻ x, ν {y | (x, y) ∈ s} ∂μ. We also have (μ.prod ν) (s ×ˢ t) = μ s * ν t, i.e. the measure of a rectangle is the product of the measures of the sides.

We also prove Tonelli's theorem.

Main definition #

Main results #

Implementation Notes #

Many results are proven twice, once for functions in curried form (α → β → γ) and one for functions in uncurried form (α × β → γ). The former often has an assumption Measurable (uncurry f), which could be inconvenient to discharge, but for the latter it is more common that the function has to be given explicitly, since Lean cannot synthesize the function by itself. We name the lemmas about the uncurried form with a prime. Tonelli's theorem has a different naming scheme, since the version for the uncurried version is reversed.

Tags #

product measure, Tonelli's theorem, Fubini-Tonelli theorem

theorem measurable_measure_prod_mk_left_finite {α : Type u_1} {β : Type u_2} [MeasurableSpace α] [MeasurableSpace β] {ν : MeasureTheory.Measure β} [MeasureTheory.IsFiniteMeasure ν] {s : Set (α × β)} (hs : MeasurableSet s) :
Measurable fun (x : α) => ν (Prod.mk x ⁻¹' s)

If ν is a finite measure, and s ⊆ α × β is measurable, then x ↦ ν { y | (x, y) ∈ s } is a measurable function. measurable_measure_prod_mk_left is strictly more general.

theorem measurable_measure_prod_mk_left {α : Type u_1} {β : Type u_2} [MeasurableSpace α] [MeasurableSpace β] {ν : MeasureTheory.Measure β} [MeasureTheory.SFinite ν] {s : Set (α × β)} (hs : MeasurableSet s) :
Measurable fun (x : α) => ν (Prod.mk x ⁻¹' s)

If ν is an s-finite measure, and s ⊆ α × β is measurable, then x ↦ ν { y | (x, y) ∈ s } is a measurable function.

theorem measurable_measure_prod_mk_right {α : Type u_1} {β : Type u_2} [MeasurableSpace α] [MeasurableSpace β] {μ : MeasureTheory.Measure α} [MeasureTheory.SFinite μ] {s : Set (α × β)} (hs : MeasurableSet s) :
Measurable fun (y : β) => μ ((fun (x : α) => (x, y)) ⁻¹' s)

If μ is a σ-finite measure, and s ⊆ α × β is measurable, then y ↦ μ { x | (x, y) ∈ s } is a measurable function.

theorem Measurable.map_prod_mk_right {α : Type u_1} {β : Type u_2} [MeasurableSpace α] [MeasurableSpace β] {μ : MeasureTheory.Measure α} [MeasureTheory.SFinite μ] :
Measurable fun (y : β) => MeasureTheory.Measure.map (fun (x : α) => (x, y)) μ
theorem Measurable.lintegral_prod_right' {α : Type u_1} {β : Type u_2} [MeasurableSpace α] [MeasurableSpace β] {ν : MeasureTheory.Measure β} [MeasureTheory.SFinite ν] {f : α × βENNReal} :
Measurable fMeasurable fun (x : α) => ∫⁻ (y : β), f (x, y)ν

The Lebesgue integral is measurable. This shows that the integrand of (the right-hand-side of) Tonelli's theorem is measurable.

theorem Measurable.lintegral_prod_right {α : Type u_1} {β : Type u_2} [MeasurableSpace α] [MeasurableSpace β] {ν : MeasureTheory.Measure β} [MeasureTheory.SFinite ν] {f : αβENNReal} (hf : Measurable (Function.uncurry f)) :
Measurable fun (x : α) => ∫⁻ (y : β), f x yν

The Lebesgue integral is measurable. This shows that the integrand of (the right-hand-side of) Tonelli's theorem is measurable. This version has the argument f in curried form.

theorem Measurable.lintegral_prod_left' {α : Type u_1} {β : Type u_2} [MeasurableSpace α] [MeasurableSpace β] {μ : MeasureTheory.Measure α} [MeasureTheory.SFinite μ] {f : α × βENNReal} (hf : Measurable f) :
Measurable fun (y : β) => ∫⁻ (x : α), f (x, y)μ

The Lebesgue integral is measurable. This shows that the integrand of (the right-hand-side of) the symmetric version of Tonelli's theorem is measurable.

theorem Measurable.lintegral_prod_left {α : Type u_1} {β : Type u_2} [MeasurableSpace α] [MeasurableSpace β] {μ : MeasureTheory.Measure α} [MeasureTheory.SFinite μ] {f : αβENNReal} (hf : Measurable (Function.uncurry f)) :
Measurable fun (y : β) => ∫⁻ (x : α), f x yμ

The Lebesgue integral is measurable. This shows that the integrand of (the right-hand-side of) the symmetric version of Tonelli's theorem is measurable. This version has the argument f in curried form.

The product measure #

theorem MeasureTheory.Measure.prod_def {α : Type u_4} {β : Type u_5} [MeasurableSpace α] [MeasurableSpace β] (μ : MeasureTheory.Measure α) (ν : MeasureTheory.Measure β) :
μ.prod ν = μ.bind fun (x : α) => MeasureTheory.Measure.map (Prod.mk x) ν
@[irreducible]

The binary product of measures. They are defined for arbitrary measures, but we basically prove all properties under the assumption that at least one of them is s-finite.

Equations
Instances For
    Equations
    theorem MeasureTheory.Measure.volume_eq_prod (α : Type u_4) (β : Type u_5) [MeasureTheory.MeasureSpace α] [MeasureTheory.MeasureSpace β] :
    MeasureTheory.volume = MeasureTheory.volume.prod MeasureTheory.volume
    theorem MeasureTheory.Measure.prod_apply {α : Type u_1} {β : Type u_2} [MeasurableSpace α] [MeasurableSpace β] {μ : MeasureTheory.Measure α} {ν : MeasureTheory.Measure β} [MeasureTheory.SFinite ν] {s : Set (α × β)} (hs : MeasurableSet s) :
    (μ.prod ν) s = ∫⁻ (x : α), ν (Prod.mk x ⁻¹' s)μ
    @[simp]
    theorem MeasureTheory.Measure.prod_prod {α : Type u_1} {β : Type u_2} [MeasurableSpace α] [MeasurableSpace β] {μ : MeasureTheory.Measure α} {ν : MeasureTheory.Measure β} [MeasureTheory.SFinite ν] (s : Set α) (t : Set β) :
    (μ.prod ν) (s ×ˢ t) = μ s * ν t

    The product measure of the product of two sets is the product of their measures. Note that we do not need the sets to be measurable.

    @[simp]
    theorem MeasureTheory.Measure.map_fst_prod {α : Type u_1} {β : Type u_2} [MeasurableSpace α] [MeasurableSpace β] {μ : MeasureTheory.Measure α} {ν : MeasureTheory.Measure β} [MeasureTheory.SFinite ν] :
    MeasureTheory.Measure.map Prod.fst (μ.prod ν) = ν Set.univ μ
    @[simp]
    theorem MeasureTheory.Measure.map_snd_prod {α : Type u_1} {β : Type u_2} [MeasurableSpace α] [MeasurableSpace β] {μ : MeasureTheory.Measure α} {ν : MeasureTheory.Measure β} [MeasureTheory.SFinite ν] :
    MeasureTheory.Measure.map Prod.snd (μ.prod ν) = μ Set.univ ν
    instance MeasureTheory.Measure.prod.instIsOpenPosMeasure {X : Type u_4} {Y : Type u_5} [TopologicalSpace X] [TopologicalSpace Y] {m : MeasurableSpace X} {μ : MeasureTheory.Measure X} [μ.IsOpenPosMeasure] {m' : MeasurableSpace Y} {ν : MeasureTheory.Measure Y} [ν.IsOpenPosMeasure] [MeasureTheory.SFinite ν] :
    (μ.prod ν).IsOpenPosMeasure
    Equations
    • =
    instance MeasureTheory.Measure.instIsOpenPosMeasureProdVolumeOfSFinite {X : Type u_4} {Y : Type u_5} [TopologicalSpace X] [MeasureTheory.MeasureSpace X] [MeasureTheory.volume.IsOpenPosMeasure] [TopologicalSpace Y] [MeasureTheory.MeasureSpace Y] [MeasureTheory.volume.IsOpenPosMeasure] [MeasureTheory.SFinite MeasureTheory.volume] :
    MeasureTheory.volume.IsOpenPosMeasure
    Equations
    • =
    theorem MeasureTheory.Measure.ae_measure_lt_top {α : Type u_1} {β : Type u_2} [MeasurableSpace α] [MeasurableSpace β] {μ : MeasureTheory.Measure α} {ν : MeasureTheory.Measure β} [MeasureTheory.SFinite ν] {s : Set (α × β)} (hs : MeasurableSet s) (h2s : (μ.prod ν) s ) :
    ∀ᵐ (x : α) ∂μ, ν (Prod.mk x ⁻¹' s) <
    theorem MeasureTheory.Measure.measure_prod_null {α : Type u_1} {β : Type u_2} [MeasurableSpace α] [MeasurableSpace β] {μ : MeasureTheory.Measure α} {ν : MeasureTheory.Measure β} [MeasureTheory.SFinite ν] {s : Set (α × β)} (hs : MeasurableSet s) :
    (μ.prod ν) s = 0 (fun (x : α) => ν (Prod.mk x ⁻¹' s)) =ᵐ[μ] 0

    Note: the assumption hs cannot be dropped. For a counterexample, see Walter Rudin Real and Complex Analysis, example (c) in section 8.9.

    theorem MeasureTheory.Measure.measure_ae_null_of_prod_null {α : Type u_1} {β : Type u_2} [MeasurableSpace α] [MeasurableSpace β] {μ : MeasureTheory.Measure α} {ν : MeasureTheory.Measure β} [MeasureTheory.SFinite ν] {s : Set (α × β)} (h : (μ.prod ν) s = 0) :
    (fun (x : α) => ν (Prod.mk x ⁻¹' s)) =ᵐ[μ] 0

    Note: the converse is not true without assuming that s is measurable. For a counterexample, see Walter Rudin Real and Complex Analysis, example (c) in section 8.9.

    theorem MeasureTheory.Measure.AbsolutelyContinuous.prod {α : Type u_1} {β : Type u_2} [MeasurableSpace α] [MeasurableSpace β] {μ μ' : MeasureTheory.Measure α} {ν ν' : MeasureTheory.Measure β} [MeasureTheory.SFinite ν] [MeasureTheory.SFinite ν'] (h1 : μ.AbsolutelyContinuous μ') (h2 : ν.AbsolutelyContinuous ν') :
    (μ.prod ν).AbsolutelyContinuous (μ'.prod ν')
    theorem MeasureTheory.Measure.ae_ae_of_ae_prod {α : Type u_1} {β : Type u_2} [MeasurableSpace α] [MeasurableSpace β] {μ : MeasureTheory.Measure α} {ν : MeasureTheory.Measure β} [MeasureTheory.SFinite ν] {p : α × βProp} (h : ∀ᵐ (z : α × β) ∂μ.prod ν, p z) :
    ∀ᵐ (x : α) ∂μ, ∀ᵐ (y : β) ∂ν, p (x, y)

    Note: the converse is not true. For a counterexample, see Walter Rudin Real and Complex Analysis, example (c) in section 8.9. It is true if the set is measurable, see ae_prod_mem_iff_ae_ae_mem.

    theorem MeasureTheory.Measure.ae_ae_eq_curry_of_prod {α : Type u_1} {β : Type u_2} [MeasurableSpace α] [MeasurableSpace β] {μ : MeasureTheory.Measure α} {ν : MeasureTheory.Measure β} [MeasureTheory.SFinite ν] {γ : Type u_4} {f g : α × βγ} (h : f =ᵐ[μ.prod ν] g) :
    ∀ᵐ (x : α) ∂μ, Function.curry f x =ᵐ[ν] Function.curry g x
    theorem MeasureTheory.Measure.ae_ae_eq_of_ae_eq_uncurry {α : Type u_1} {β : Type u_2} [MeasurableSpace α] [MeasurableSpace β] {μ : MeasureTheory.Measure α} {ν : MeasureTheory.Measure β} [MeasureTheory.SFinite ν] {γ : Type u_4} {f g : αβγ} (h : Function.uncurry f =ᵐ[μ.prod ν] Function.uncurry g) :
    ∀ᵐ (x : α) ∂μ, f x =ᵐ[ν] g x
    theorem MeasureTheory.Measure.ae_prod_iff_ae_ae {α : Type u_1} {β : Type u_2} [MeasurableSpace α] [MeasurableSpace β] {μ : MeasureTheory.Measure α} {ν : MeasureTheory.Measure β} [MeasureTheory.SFinite ν] {p : α × βProp} (hp : MeasurableSet {x : α × β | p x}) :
    (∀ᵐ (z : α × β) ∂μ.prod ν, p z) ∀ᵐ (x : α) ∂μ, ∀ᵐ (y : β) ∂ν, p (x, y)
    theorem MeasureTheory.Measure.ae_prod_mem_iff_ae_ae_mem {α : Type u_1} {β : Type u_2} [MeasurableSpace α] [MeasurableSpace β] {μ : MeasureTheory.Measure α} {ν : MeasureTheory.Measure β} [MeasureTheory.SFinite ν] {s : Set (α × β)} (hs : MeasurableSet s) :
    (∀ᵐ (z : α × β) ∂μ.prod ν, z s) ∀ᵐ (x : α) ∂μ, ∀ᵐ (y : β) ∂ν, (x, y) s
    theorem MeasureTheory.Measure.set_prod_ae_eq {α : Type u_1} {β : Type u_2} [MeasurableSpace α] [MeasurableSpace β] {μ : MeasureTheory.Measure α} {ν : MeasureTheory.Measure β} [MeasureTheory.SFinite ν] {s s' : Set α} {t t' : Set β} (hs : s =ᵐ[μ] s') (ht : t =ᵐ[ν] t') :
    s ×ˢ t =ᵐ[μ.prod ν] s' ×ˢ t'
    theorem MeasureTheory.Measure.measure_prod_compl_eq_zero {α : Type u_1} {β : Type u_2} [MeasurableSpace α] [MeasurableSpace β] {μ : MeasureTheory.Measure α} {ν : MeasureTheory.Measure β} [MeasureTheory.SFinite ν] {s : Set α} {t : Set β} (s_ae_univ : μ s = 0) (t_ae_univ : ν t = 0) :
    (μ.prod ν) (s ×ˢ t) = 0

    If s ×ˢ t is a null measurable set and μ s ≠ 0, then t is a null measurable set.

    If Prod.snd ⁻¹' t is a null measurable set and μ ≠ 0, then t is a null measurable set.

    Prod.snd ⁻¹' t is null measurable w.r.t. μ.prod ν iff t is null measurable w.r.t. ν provided that μ ≠ 0.

    noncomputable def MeasureTheory.Measure.FiniteSpanningSetsIn.prod {α : Type u_1} {β : Type u_2} [MeasurableSpace α] [MeasurableSpace β] {μ : MeasureTheory.Measure α} {ν : MeasureTheory.Measure β} {C : Set (Set α)} {D : Set (Set β)} (hμ : μ.FiniteSpanningSetsIn C) (hν : ν.FiniteSpanningSetsIn D) :
    (μ.prod ν).FiniteSpanningSetsIn (Set.image2 (fun (x1 : Set α) (x2 : Set β) => x1 ×ˢ x2) C D)

    μ.prod ν has finite spanning sets in rectangles of finite spanning sets.

    Equations
    • .prod = { set := fun (n : ) => .set (Nat.unpair n).1 ×ˢ .set (Nat.unpair n).2, set_mem := , finite := , spanning := }
    Instances For
      theorem MeasureTheory.Measure.prod_sum_left {α : Type u_1} {β : Type u_2} [MeasurableSpace α] [MeasurableSpace β] {ι : Type u_4} (m : ιMeasureTheory.Measure α) (μ : MeasureTheory.Measure β) [MeasureTheory.SFinite μ] :
      (MeasureTheory.Measure.sum m).prod μ = MeasureTheory.Measure.sum fun (i : ι) => (m i).prod μ
      theorem MeasureTheory.Measure.prod_sum_right {α : Type u_1} {β : Type u_2} [MeasurableSpace α] [MeasurableSpace β] {ι' : Type u_4} [Countable ι'] (m : MeasureTheory.Measure α) (m' : ι'MeasureTheory.Measure β) [∀ (n : ι'), MeasureTheory.SFinite (m' n)] :
      m.prod (MeasureTheory.Measure.sum m') = MeasureTheory.Measure.sum fun (p : ι') => m.prod (m' p)
      theorem MeasureTheory.Measure.prod_sum {α : Type u_1} {β : Type u_2} [MeasurableSpace α] [MeasurableSpace β] {ι : Type u_4} {ι' : Type u_5} [Countable ι'] (m : ιMeasureTheory.Measure α) (m' : ι'MeasureTheory.Measure β) [∀ (n : ι'), MeasureTheory.SFinite (m' n)] :
      (MeasureTheory.Measure.sum m).prod (MeasureTheory.Measure.sum m') = MeasureTheory.Measure.sum fun (p : ι × ι') => (m p.1).prod (m' p.2)
      Equations
      • =
      Equations
      • =
      instance MeasureTheory.Measure.instSFiniteProdVolume {α : Type u_4} {β : Type u_5} [MeasureTheory.MeasureSpace α] [MeasureTheory.SFinite MeasureTheory.volume] [MeasureTheory.MeasureSpace β] [MeasureTheory.SFinite MeasureTheory.volume] :
      MeasureTheory.SFinite MeasureTheory.volume
      Equations
      • =
      theorem MeasureTheory.Measure.prod_eq_generateFrom {α : Type u_1} {β : Type u_2} [MeasurableSpace α] [MeasurableSpace β] {μ : MeasureTheory.Measure α} {ν : MeasureTheory.Measure β} {C : Set (Set α)} {D : Set (Set β)} (hC : MeasurableSpace.generateFrom C = inst✝) (hD : MeasurableSpace.generateFrom D = inst✝¹) (h2C : IsPiSystem C) (h2D : IsPiSystem D) (h3C : μ.FiniteSpanningSetsIn C) (h3D : ν.FiniteSpanningSetsIn D) {μν : MeasureTheory.Measure (α × β)} (h₁ : sC, tD, μν (s ×ˢ t) = μ s * ν t) :
      μ.prod ν = μν

      A measure on a product space equals the product measure if they are equal on rectangles with as sides sets that generate the corresponding σ-algebras.

      theorem MeasureTheory.Measure.prod_eq {α : Type u_1} {β : Type u_2} [MeasurableSpace α] [MeasurableSpace β] {μ : MeasureTheory.Measure α} [MeasureTheory.SigmaFinite μ] {ν : MeasureTheory.Measure β} [MeasureTheory.SigmaFinite ν] {μν : MeasureTheory.Measure (α × β)} (h : ∀ (s : Set α) (t : Set β), MeasurableSet sMeasurableSet tμν (s ×ˢ t) = μ s * ν t) :
      μ.prod ν = μν

      A measure on a product space equals the product measure of sigma-finite measures if they are equal on rectangles.

      theorem MeasureTheory.Measure.prod_apply_symm {α : Type u_1} {β : Type u_2} [MeasurableSpace α] [MeasurableSpace β] {μ : MeasureTheory.Measure α} {ν : MeasureTheory.Measure β} [MeasureTheory.SFinite ν] [MeasureTheory.SFinite μ] {s : Set (α × β)} (hs : MeasurableSet s) :
      (μ.prod ν) s = ∫⁻ (y : β), μ ((fun (x : α) => (x, y)) ⁻¹' s)ν
      theorem MeasureTheory.Measure.ae_ae_comm {α : Type u_1} {β : Type u_2} [MeasurableSpace α] [MeasurableSpace β] {μ : MeasureTheory.Measure α} {ν : MeasureTheory.Measure β} [MeasureTheory.SFinite ν] [MeasureTheory.SFinite μ] {p : αβProp} (h : MeasurableSet {x : α × β | p x.1 x.2}) :
      (∀ᵐ (x : α) ∂μ, ∀ᵐ (y : β) ∂ν, p x y) ∀ᵐ (y : β) ∂ν, ∀ᵐ (x : α) ∂μ, p x y

      If s ×ˢ t is a null measurable set and ν t ≠ 0, then s is a null measurable set.

      If Prod.fst ⁻¹' s is a null measurable set and ν ≠ 0, then s is a null measurable set.

      Prod.fst ⁻¹' s is null measurable w.r.t. μ.prod ν iff s is null measurable w.r.t. μ provided that ν ≠ 0.

      The product of two non-null sets is null measurable if and only if both of them are null measurable.

      The product of two sets is null measurable if and only if both of them are null measurable or one of them has measure zero.

      theorem MeasureTheory.Measure.prodAssoc_prod {α : Type u_1} {β : Type u_2} {γ : Type u_3} [MeasurableSpace α] [MeasurableSpace β] [MeasurableSpace γ] {μ : MeasureTheory.Measure α} {ν : MeasureTheory.Measure β} {τ : MeasureTheory.Measure γ} [MeasureTheory.SFinite ν] [MeasureTheory.SFinite μ] [MeasureTheory.SFinite τ] :
      MeasureTheory.Measure.map (⇑MeasurableEquiv.prodAssoc) ((μ.prod ν).prod τ) = μ.prod (ν.prod τ)

      The product of specific measures #

      theorem MeasureTheory.Measure.prod_restrict {α : Type u_1} {β : Type u_2} [MeasurableSpace α] [MeasurableSpace β] {μ : MeasureTheory.Measure α} {ν : MeasureTheory.Measure β} [MeasureTheory.SFinite ν] [MeasureTheory.SFinite μ] (s : Set α) (t : Set β) :
      (μ.restrict s).prod (ν.restrict t) = (μ.prod ν).restrict (s ×ˢ t)
      theorem MeasureTheory.Measure.restrict_prod_eq_prod_univ {α : Type u_1} {β : Type u_2} [MeasurableSpace α] [MeasurableSpace β] {μ : MeasureTheory.Measure α} {ν : MeasureTheory.Measure β} [MeasureTheory.SFinite ν] [MeasureTheory.SFinite μ] (s : Set α) :
      (μ.restrict s).prod ν = (μ.prod ν).restrict (s ×ˢ Set.univ)
      theorem MeasureTheory.Measure.prod_dirac {α : Type u_1} {β : Type u_2} [MeasurableSpace α] [MeasurableSpace β] {μ : MeasureTheory.Measure α} [MeasureTheory.SFinite μ] (y : β) :
      μ.prod (MeasureTheory.Measure.dirac y) = MeasureTheory.Measure.map (fun (x : α) => (x, y)) μ
      theorem MeasureTheory.Measure.prod_add {α : Type u_1} {β : Type u_2} [MeasurableSpace α] [MeasurableSpace β] {μ : MeasureTheory.Measure α} {ν : MeasureTheory.Measure β} [MeasureTheory.SFinite ν] [MeasureTheory.SFinite μ] (ν' : MeasureTheory.Measure β) [MeasureTheory.SFinite ν'] :
      μ.prod (ν + ν') = μ.prod ν + μ.prod ν'
      theorem MeasureTheory.Measure.add_prod {α : Type u_1} {β : Type u_2} [MeasurableSpace α] [MeasurableSpace β] {μ : MeasureTheory.Measure α} {ν : MeasureTheory.Measure β} [MeasureTheory.SFinite ν] [MeasureTheory.SFinite μ] (μ' : MeasureTheory.Measure α) [MeasureTheory.SFinite μ'] :
      (μ + μ').prod ν = μ.prod ν + μ'.prod ν
      @[simp]
      theorem MeasureTheory.Measure.prod_zero {α : Type u_1} {β : Type u_2} [MeasurableSpace α] [MeasurableSpace β] (μ : MeasureTheory.Measure α) :
      μ.prod 0 = 0
      theorem MeasureTheory.Measure.map_prod_map {α : Type u_1} {β : Type u_2} {γ : Type u_3} [MeasurableSpace α] [MeasurableSpace β] [MeasurableSpace γ] {δ : Type u_4} [MeasurableSpace δ] {f : αβ} {g : γδ} (μa : MeasureTheory.Measure α) (μc : MeasureTheory.Measure γ) [MeasureTheory.SFinite μa] [MeasureTheory.SFinite μc] (hf : Measurable f) (hg : Measurable g) :
      theorem MeasureTheory.MeasurePreserving.skew_product {α : Type u_1} {β : Type u_2} {γ : Type u_3} [MeasurableSpace α] [MeasurableSpace β] [MeasurableSpace γ] {δ : Type u_4} [MeasurableSpace δ] {μa : MeasureTheory.Measure α} {μb : MeasureTheory.Measure β} {μc : MeasureTheory.Measure γ} {μd : MeasureTheory.Measure δ} [MeasureTheory.SFinite μa] [MeasureTheory.SFinite μc] {f : αβ} (hf : MeasureTheory.MeasurePreserving f μa μb) {g : αγδ} (hgm : Measurable (Function.uncurry g)) (hg : ∀ᵐ (a : α) ∂μa, MeasureTheory.Measure.map (g a) μc = μd) :
      MeasureTheory.MeasurePreserving (fun (p : α × γ) => (f p.1, g p.1 p.2)) (μa.prod μc) (μb.prod μd)

      Let f : α → β be a measure preserving map. For a.e. all a, let g a : γ → δ be a measure preserving map. Also suppose that g is measurable as a function of two arguments. Then the map fun (a, c) ↦ (f a, g a c) is a measure preserving map for the product measures on α × γ and β × δ.

      Some authors call a map of the form fun (a, c) ↦ (f a, g a c) a skew product over f, thus the choice of a name.

      theorem MeasureTheory.MeasurePreserving.prod {α : Type u_1} {β : Type u_2} {γ : Type u_3} [MeasurableSpace α] [MeasurableSpace β] [MeasurableSpace γ] {δ : Type u_4} [MeasurableSpace δ] {μa : MeasureTheory.Measure α} {μb : MeasureTheory.Measure β} {μc : MeasureTheory.Measure γ} {μd : MeasureTheory.Measure δ} [MeasureTheory.SFinite μa] [MeasureTheory.SFinite μc] {f : αβ} {g : γδ} (hf : MeasureTheory.MeasurePreserving f μa μb) (hg : MeasureTheory.MeasurePreserving g μc μd) :
      MeasureTheory.MeasurePreserving (Prod.map f g) (μa.prod μc) (μb.prod μd)

      If f : α → β sends the measure μa to μb and g : γ → δ sends the measure μc to μd, then Prod.map f g sends μa.prod μc to μb.prod μd.

      theorem MeasureTheory.QuasiMeasurePreserving.prod_of_right {α : Type u_1} {β : Type u_2} {γ : Type u_3} [MeasurableSpace α] [MeasurableSpace β] [MeasurableSpace γ] {f : α × βγ} {μ : MeasureTheory.Measure α} {ν : MeasureTheory.Measure β} {τ : MeasureTheory.Measure γ} (hf : Measurable f) [MeasureTheory.SFinite ν] (h2f : ∀ᵐ (x : α) ∂μ, MeasureTheory.Measure.QuasiMeasurePreserving (fun (y : β) => f (x, y)) ν τ) :
      theorem MeasureTheory.QuasiMeasurePreserving.prod_of_left {α : Type u_4} {β : Type u_5} {γ : Type u_6} [MeasurableSpace α] [MeasurableSpace β] [MeasurableSpace γ] {f : α × βγ} {μ : MeasureTheory.Measure α} {ν : MeasureTheory.Measure β} {τ : MeasureTheory.Measure γ} (hf : Measurable f) [MeasureTheory.SFinite μ] [MeasureTheory.SFinite ν] (h2f : ∀ᵐ (y : β) ∂ν, MeasureTheory.Measure.QuasiMeasurePreserving (fun (x : α) => f (x, y)) μ τ) :
      theorem AEMeasurable.prod_swap {α : Type u_1} {β : Type u_2} {γ : Type u_3} [MeasurableSpace α] [MeasurableSpace β] [MeasurableSpace γ] {μ : MeasureTheory.Measure α} {ν : MeasureTheory.Measure β} [MeasureTheory.SFinite μ] [MeasureTheory.SFinite ν] {f : β × αγ} (hf : AEMeasurable f (ν.prod μ)) :
      AEMeasurable (fun (z : α × β) => f z.swap) (μ.prod ν)
      theorem AEMeasurable.fst {α : Type u_1} {β : Type u_2} {γ : Type u_3} [MeasurableSpace α] [MeasurableSpace β] [MeasurableSpace γ] {μ : MeasureTheory.Measure α} {ν : MeasureTheory.Measure β} [MeasureTheory.SFinite ν] {f : αγ} (hf : AEMeasurable f μ) :
      AEMeasurable (fun (z : α × β) => f z.1) (μ.prod ν)
      theorem AEMeasurable.snd {α : Type u_1} {β : Type u_2} {γ : Type u_3} [MeasurableSpace α] [MeasurableSpace β] [MeasurableSpace γ] {μ : MeasureTheory.Measure α} {ν : MeasureTheory.Measure β} [MeasureTheory.SFinite ν] {f : βγ} (hf : AEMeasurable f ν) :
      AEMeasurable (fun (z : α × β) => f z.2) (μ.prod ν)

      The Lebesgue integral on a product #

      theorem MeasureTheory.lintegral_prod_swap {α : Type u_1} {β : Type u_2} [MeasurableSpace α] [MeasurableSpace β] {μ : MeasureTheory.Measure α} {ν : MeasureTheory.Measure β} [MeasureTheory.SFinite ν] [MeasureTheory.SFinite μ] (f : α × βENNReal) :
      ∫⁻ (z : β × α), f z.swapν.prod μ = ∫⁻ (z : α × β), f zμ.prod ν
      theorem MeasureTheory.lintegral_prod_of_measurable {α : Type u_1} {β : Type u_2} [MeasurableSpace α] [MeasurableSpace β] {μ : MeasureTheory.Measure α} {ν : MeasureTheory.Measure β} [MeasureTheory.SFinite ν] (f : α × βENNReal) :
      Measurable f∫⁻ (z : α × β), f zμ.prod ν = ∫⁻ (x : α), ∫⁻ (y : β), f (x, y)νμ

      Tonelli's Theorem: For ℝ≥0∞-valued measurable functions on α × β, the integral of f is equal to the iterated integral.

      theorem MeasureTheory.lintegral_prod {α : Type u_1} {β : Type u_2} [MeasurableSpace α] [MeasurableSpace β] {μ : MeasureTheory.Measure α} {ν : MeasureTheory.Measure β} [MeasureTheory.SFinite ν] (f : α × βENNReal) (hf : AEMeasurable f (μ.prod ν)) :
      ∫⁻ (z : α × β), f zμ.prod ν = ∫⁻ (x : α), ∫⁻ (y : β), f (x, y)νμ

      Tonelli's Theorem: For ℝ≥0∞-valued almost everywhere measurable functions on α × β, the integral of f is equal to the iterated integral.

      theorem MeasureTheory.lintegral_prod_symm {α : Type u_1} {β : Type u_2} [MeasurableSpace α] [MeasurableSpace β] {μ : MeasureTheory.Measure α} {ν : MeasureTheory.Measure β} [MeasureTheory.SFinite ν] [MeasureTheory.SFinite μ] (f : α × βENNReal) (hf : AEMeasurable f (μ.prod ν)) :
      ∫⁻ (z : α × β), f zμ.prod ν = ∫⁻ (y : β), ∫⁻ (x : α), f (x, y)μν

      The symmetric version of Tonelli's Theorem: For ℝ≥0∞-valued almost everywhere measurable functions on α × β, the integral of f is equal to the iterated integral, in reverse order.

      theorem MeasureTheory.lintegral_prod_symm' {α : Type u_1} {β : Type u_2} [MeasurableSpace α] [MeasurableSpace β] {μ : MeasureTheory.Measure α} {ν : MeasureTheory.Measure β} [MeasureTheory.SFinite ν] [MeasureTheory.SFinite μ] (f : α × βENNReal) (hf : Measurable f) :
      ∫⁻ (z : α × β), f zμ.prod ν = ∫⁻ (y : β), ∫⁻ (x : α), f (x, y)μν

      The symmetric version of Tonelli's Theorem: For ℝ≥0∞-valued measurable functions on α × β, the integral of f is equal to the iterated integral, in reverse order.

      theorem MeasureTheory.lintegral_lintegral {α : Type u_1} {β : Type u_2} [MeasurableSpace α] [MeasurableSpace β] {μ : MeasureTheory.Measure α} {ν : MeasureTheory.Measure β} [MeasureTheory.SFinite ν] ⦃f : αβENNReal (hf : AEMeasurable (Function.uncurry f) (μ.prod ν)) :
      ∫⁻ (x : α), ∫⁻ (y : β), f x yνμ = ∫⁻ (z : α × β), f z.1 z.2μ.prod ν

      The reversed version of Tonelli's Theorem. In this version f is in curried form, which makes it easier for the elaborator to figure out f automatically.

      theorem MeasureTheory.lintegral_lintegral_symm {α : Type u_1} {β : Type u_2} [MeasurableSpace α] [MeasurableSpace β] {μ : MeasureTheory.Measure α} {ν : MeasureTheory.Measure β} [MeasureTheory.SFinite ν] [MeasureTheory.SFinite μ] ⦃f : αβENNReal (hf : AEMeasurable (Function.uncurry f) (μ.prod ν)) :
      ∫⁻ (x : α), ∫⁻ (y : β), f x yνμ = ∫⁻ (z : β × α), f z.2 z.1ν.prod μ

      The reversed version of Tonelli's Theorem (symmetric version). In this version f is in curried form, which makes it easier for the elaborator to figure out f automatically.

      theorem MeasureTheory.lintegral_lintegral_swap {α : Type u_1} {β : Type u_2} [MeasurableSpace α] [MeasurableSpace β] {μ : MeasureTheory.Measure α} {ν : MeasureTheory.Measure β} [MeasureTheory.SFinite ν] [MeasureTheory.SFinite μ] ⦃f : αβENNReal (hf : AEMeasurable (Function.uncurry f) (μ.prod ν)) :
      ∫⁻ (x : α), ∫⁻ (y : β), f x yνμ = ∫⁻ (y : β), ∫⁻ (x : α), f x yμν

      Change the order of Lebesgue integration.

      theorem MeasureTheory.lintegral_prod_mul {α : Type u_1} {β : Type u_2} [MeasurableSpace α] [MeasurableSpace β] {μ : MeasureTheory.Measure α} {ν : MeasureTheory.Measure β} [MeasureTheory.SFinite ν] {f : αENNReal} {g : βENNReal} (hf : AEMeasurable f μ) (hg : AEMeasurable g ν) :
      ∫⁻ (z : α × β), f z.1 * g z.2μ.prod ν = (∫⁻ (x : α), f xμ) * ∫⁻ (y : β), g yν

      Marginals of a measure defined on a product #

      noncomputable def MeasureTheory.Measure.fst {α : Type u_1} {β : Type u_2} [MeasurableSpace α] [MeasurableSpace β] (ρ : MeasureTheory.Measure (α × β)) :

      Marginal measure on α obtained from a measure ρ on α × β, defined by ρ.map Prod.fst.

      Equations
      Instances For
        theorem MeasureTheory.Measure.fst_apply {α : Type u_1} {β : Type u_2} [MeasurableSpace α] [MeasurableSpace β] {ρ : MeasureTheory.Measure (α × β)} {s : Set α} (hs : MeasurableSet s) :
        ρ.fst s = ρ (Prod.fst ⁻¹' s)
        theorem MeasureTheory.Measure.fst_univ {α : Type u_1} {β : Type u_2} [MeasurableSpace α] [MeasurableSpace β] {ρ : MeasureTheory.Measure (α × β)} :
        ρ.fst Set.univ = ρ Set.univ
        theorem MeasureTheory.Measure.fst_map_prod_mk₀ {α : Type u_1} {β : Type u_2} {γ : Type u_3} [MeasurableSpace α] [MeasurableSpace β] [MeasurableSpace γ] {X : αβ} {Y : αγ} {μ : MeasureTheory.Measure α} (hY : AEMeasurable Y μ) :
        (MeasureTheory.Measure.map (fun (a : α) => (X a, Y a)) μ).fst = MeasureTheory.Measure.map X μ
        theorem MeasureTheory.Measure.fst_map_prod_mk {α : Type u_1} {β : Type u_2} {γ : Type u_3} [MeasurableSpace α] [MeasurableSpace β] [MeasurableSpace γ] {X : αβ} {Y : αγ} {μ : MeasureTheory.Measure α} (hY : Measurable Y) :
        (MeasureTheory.Measure.map (fun (a : α) => (X a, Y a)) μ).fst = MeasureTheory.Measure.map X μ
        @[simp]
        theorem MeasureTheory.Measure.fst_add {α : Type u_1} {β : Type u_2} [MeasurableSpace α] [MeasurableSpace β] {μ ν : MeasureTheory.Measure (α × β)} :
        (μ + ν).fst = μ.fst + ν.fst
        theorem MeasureTheory.Measure.fst_sum {α : Type u_1} {β : Type u_2} [MeasurableSpace α] [MeasurableSpace β] {ι : Type u_4} (μ : ιMeasureTheory.Measure (α × β)) :
        (MeasureTheory.Measure.sum μ).fst = MeasureTheory.Measure.sum fun (n : ι) => (μ n).fst
        theorem MeasureTheory.Measure.fst_mono {α : Type u_1} {β : Type u_2} [MeasurableSpace α] [MeasurableSpace β] {ρ μ : MeasureTheory.Measure (α × β)} (h : ρ μ) :
        ρ.fst μ.fst
        noncomputable def MeasureTheory.Measure.snd {α : Type u_1} {β : Type u_2} [MeasurableSpace α] [MeasurableSpace β] (ρ : MeasureTheory.Measure (α × β)) :

        Marginal measure on β obtained from a measure on ρ α × β, defined by ρ.map Prod.snd.

        Equations
        Instances For
          theorem MeasureTheory.Measure.snd_apply {α : Type u_1} {β : Type u_2} [MeasurableSpace α] [MeasurableSpace β] {ρ : MeasureTheory.Measure (α × β)} {s : Set β} (hs : MeasurableSet s) :
          ρ.snd s = ρ (Prod.snd ⁻¹' s)
          theorem MeasureTheory.Measure.snd_univ {α : Type u_1} {β : Type u_2} [MeasurableSpace α] [MeasurableSpace β] {ρ : MeasureTheory.Measure (α × β)} :
          ρ.snd Set.univ = ρ Set.univ
          theorem MeasureTheory.Measure.snd_map_prod_mk₀ {α : Type u_1} {β : Type u_2} {γ : Type u_3} [MeasurableSpace α] [MeasurableSpace β] [MeasurableSpace γ] {X : αβ} {Y : αγ} {μ : MeasureTheory.Measure α} (hX : AEMeasurable X μ) :
          (MeasureTheory.Measure.map (fun (a : α) => (X a, Y a)) μ).snd = MeasureTheory.Measure.map Y μ
          theorem MeasureTheory.Measure.snd_map_prod_mk {α : Type u_1} {β : Type u_2} {γ : Type u_3} [MeasurableSpace α] [MeasurableSpace β] [MeasurableSpace γ] {X : αβ} {Y : αγ} {μ : MeasureTheory.Measure α} (hX : Measurable X) :
          (MeasureTheory.Measure.map (fun (a : α) => (X a, Y a)) μ).snd = MeasureTheory.Measure.map Y μ
          @[simp]
          theorem MeasureTheory.Measure.snd_add {α : Type u_1} {β : Type u_2} [MeasurableSpace α] [MeasurableSpace β] {μ ν : MeasureTheory.Measure (α × β)} :
          (μ + ν).snd = μ.snd + ν.snd
          theorem MeasureTheory.Measure.snd_sum {α : Type u_1} {β : Type u_2} [MeasurableSpace α] [MeasurableSpace β] {ι : Type u_4} (μ : ιMeasureTheory.Measure (α × β)) :
          (MeasureTheory.Measure.sum μ).snd = MeasureTheory.Measure.sum fun (n : ι) => (μ n).snd
          theorem MeasureTheory.Measure.snd_mono {α : Type u_1} {β : Type u_2} [MeasurableSpace α] [MeasurableSpace β] {ρ μ : MeasureTheory.Measure (α × β)} (h : ρ μ) :
          ρ.snd μ.snd
          @[simp]
          theorem MeasureTheory.Measure.fst_map_swap {α : Type u_1} {β : Type u_2} [MeasurableSpace α] [MeasurableSpace β] {ρ : MeasureTheory.Measure (α × β)} :
          (MeasureTheory.Measure.map Prod.swap ρ).fst = ρ.snd
          @[simp]
          theorem MeasureTheory.Measure.snd_map_swap {α : Type u_1} {β : Type u_2} [MeasurableSpace α] [MeasurableSpace β] {ρ : MeasureTheory.Measure (α × β)} :
          (MeasureTheory.Measure.map Prod.swap ρ).snd = ρ.fst
          theorem MeasureTheory.measurePreserving_prodAssoc {α : Type u_1} {β : Type u_2} {γ : Type u_3} [MeasurableSpace α] [MeasurableSpace β] [MeasurableSpace γ] (μa : MeasureTheory.Measure α) (μb : MeasureTheory.Measure β) (μc : MeasureTheory.Measure γ) [MeasureTheory.SFinite μb] [MeasureTheory.SFinite μc] :
          MeasureTheory.MeasurePreserving (⇑MeasurableEquiv.prodAssoc) ((μa.prod μb).prod μc) (μa.prod (μb.prod μc))

          The measurable equiv induced by the equiv (α × β) × γ ≃ α × (β × γ) is measure preserving.

          theorem MeasureTheory.volume_preserving_prodAssoc {α₁ : Type u_4} {β₁ : Type u_5} {γ₁ : Type u_6} [MeasureTheory.MeasureSpace α₁] [MeasureTheory.MeasureSpace β₁] [MeasureTheory.MeasureSpace γ₁] [MeasureTheory.SFinite MeasureTheory.volume] [MeasureTheory.SFinite MeasureTheory.volume] :
          MeasureTheory.MeasurePreserving (⇑MeasurableEquiv.prodAssoc) MeasureTheory.volume MeasureTheory.volume