Bochner integral #
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The Bochner integral extends the definition of the Lebesgue integral to functions that map from a measure space into a Banach space (complete normed vector space). It is constructed here by extending the integral on simple functions.
Main definitions #
The Bochner integral is defined through the extension process described in the file set_to_L1
,
which follows these steps:
-
Define the integral of the indicator of a set. This is
weighted_smul μ s x = (μ s).to_real * x
.weighted_smul μ
is shown to be linear in the valuex
anddominated_fin_meas_additive
(defined in the fileset_to_L1
) with respect to the sets
. -
Define the integral on simple functions of the type
simple_func α E
(notation :α →ₛ E
) whereE
is a real normed space. (Seesimple_func.integral
for details.) -
Transfer this definition to define the integral on
L1.simple_func α E
(notation :α →₁ₛ[μ] E
), seeL1.simple_func.integral
. Show that this integral is a continuous linear map fromα →₁ₛ[μ] E
toE
. -
Define the Bochner integral on L1 functions by extending the integral on integrable simple functions
α →₁ₛ[μ] E
usingcontinuous_linear_map.extend
and the fact that the embedding ofα →₁ₛ[μ] E
intoα →₁[μ] E
is dense. -
Define the Bochner integral on functions as the Bochner integral of its equivalence class in L1 space, if it is in L1, and 0 otherwise.
The result of that construction is ∫ a, f a ∂μ
, which is definitionally equal to
set_to_fun (dominated_fin_meas_additive_weighted_smul μ) f
. Some basic properties of the integral
(like linearity) are particular cases of the properties of set_to_fun
(which are described in the
file set_to_L1
).
Main statements #
- Basic properties of the Bochner integral on functions of type
α → E
, whereα
is a measure space andE
is a real normed space.
integral_zero
:∫ 0 ∂μ = 0
integral_add
:∫ x, f x + g x ∂μ = ∫ x, f ∂μ + ∫ x, g x ∂μ
integral_neg
:∫ x, - f x ∂μ = - ∫ x, f x ∂μ
integral_sub
:∫ x, f x - g x ∂μ = ∫ x, f x ∂μ - ∫ x, g x ∂μ
integral_smul
:∫ x, r • f x ∂μ = r • ∫ x, f x ∂μ
integral_congr_ae
:f =ᵐ[μ] g → ∫ x, f x ∂μ = ∫ x, g x ∂μ
norm_integral_le_integral_norm
:‖∫ x, f x ∂μ‖ ≤ ∫ x, ‖f x‖ ∂μ
- Basic properties of the Bochner integral on functions of type
α → ℝ
, whereα
is a measure space.
integral_nonneg_of_ae
:0 ≤ᵐ[μ] f → 0 ≤ ∫ x, f x ∂μ
integral_nonpos_of_ae
:f ≤ᵐ[μ] 0 → ∫ x, f x ∂μ ≤ 0
integral_mono_ae
:f ≤ᵐ[μ] g → ∫ x, f x ∂μ ≤ ∫ x, g x ∂μ
integral_nonneg
:0 ≤ f → 0 ≤ ∫ x, f x ∂μ
integral_nonpos
:f ≤ 0 → ∫ x, f x ∂μ ≤ 0
integral_mono
:f ≤ᵐ[μ] g → ∫ x, f x ∂μ ≤ ∫ x, g x ∂μ
- Propositions connecting the Bochner integral with the integral on
ℝ≥0∞
-valued functions, which is calledlintegral
and has the notation∫⁻
.
integral_eq_lintegral_max_sub_lintegral_min
:∫ x, f x ∂μ = ∫⁻ x, f⁺ x ∂μ - ∫⁻ x, f⁻ x ∂μ
, wheref⁺
is the positive part off
andf⁻
is the negative part off
.integral_eq_lintegral_of_nonneg_ae
:0 ≤ᵐ[μ] f → ∫ x, f x ∂μ = ∫⁻ x, f x ∂μ
-
tendsto_integral_of_dominated_convergence
: the Lebesgue dominated convergence theorem -
(In the file
set_integral
) integration commutes with continuous linear maps.
Notes #
Some tips on how to prove a proposition if the API for the Bochner integral is not enough so that you need to unfold the definition of the Bochner integral and go back to simple functions.
One method is to use the theorem integrable.induction
in the file simple_func_dense_lp
(or one
of the related results, like Lp.induction
for functions in Lp
), which allows you to prove
something for an arbitrary integrable function.
Another method is using the following steps.
See integral_eq_lintegral_max_sub_lintegral_min
for a complicated example, which proves that
∫ f = ∫⁻ f⁺ - ∫⁻ f⁻
, with the first integral sign being the Bochner integral of a real-valued
function f : α → ℝ
, and second and third integral sign being the integral on ℝ≥0∞
-valued
functions (called lintegral
). The proof of integral_eq_lintegral_max_sub_lintegral_min
is
scattered in sections with the name pos_part
.
Here are the usual steps of proving that a property p
, say ∫ f = ∫⁻ f⁺ - ∫⁻ f⁻
, holds for all
functions :
-
First go to the
L¹
space.For example, if you see
ennreal.to_real (∫⁻ a, ennreal.of_real $ ‖f a‖)
, that is the norm off
inL¹
space. Rewrite usingL1.norm_of_fun_eq_lintegral_norm
. -
Show that the set
{f ∈ L¹ | ∫ f = ∫⁻ f⁺ - ∫⁻ f⁻}
is closed inL¹
usingis_closed_eq
. -
Show that the property holds for all simple functions
s
inL¹
space.Typically, you need to convert various notions to their
simple_func
counterpart, using lemmas likeL1.integral_coe_eq_integral
. -
Since simple functions are dense in
L¹
,
univ = closure {s simple}
= closure {s simple | ∫ s = ∫⁻ s⁺ - ∫⁻ s⁻} : the property holds for all simple functions
⊆ closure {f | ∫ f = ∫⁻ f⁺ - ∫⁻ f⁻}
= {f | ∫ f = ∫⁻ f⁺ - ∫⁻ f⁻} : closure of a closed set is itself
Use is_closed_property
or dense_range.induction_on
for this argument.
Notations #
α →ₛ E
: simple functions (defined inmeasure_theory/integration
)α →₁[μ] E
: functions in L1 space, i.e., equivalence classes of integrable functions (defined inmeasure_theory/lp_space
)α →₁ₛ[μ] E
: simple functions in L1 space, i.e., equivalence classes of integrable simple functions (defined inmeasure_theory/simple_func_dense
)∫ a, f a ∂μ
: integral off
with respect to a measureμ
∫ a, f a
: integral off
with respect tovolume
, the default measure on the ambient type
We also define notations for integral on a set, which are described in the file
measure_theory/set_integral
.
Note : ₛ
is typed using \_s
. Sometimes it shows as a box if the font is missing.
Tags #
Bochner integral, simple function, function space, Lebesgue dominated convergence theorem
Given a set s
, return the continuous linear map λ x, (μ s).to_real • x
. The extension of
that set function through set_to_L1
gives the Bochner integral of L1 functions.
Equations
- measure_theory.weighted_smul μ s = (⇑μ s).to_real • continuous_linear_map.id ℝ F
Positive part of a simple function.
Equations
- f.pos_part = measure_theory.simple_func.map (λ (b : E), linear_order.max b 0) f
Negative part of a simple function.
The Bochner integral of simple functions #
Define the Bochner integral of simple functions of the type α →ₛ β
where β
is a normed group,
and prove basic property of this integral.
Bochner integral of simple functions whose codomain is a real normed_space
.
This is equal to ∑ x in f.range, (μ (f ⁻¹' {x})).to_real • x
(see integral_eq
).
The Bochner integral is equal to a sum over any set that includes f.range
(except 0
).
Calculate the integral of g ∘ f : α →ₛ F
, where f
is an integrable function from α
to E
and g
is a function from E
to F
. We require g 0 = 0
so that g ∘ f
is integrable.
simple_func.integral
and simple_func.lintegral
agree when the integrand has type
α →ₛ ℝ≥0∞
. But since ℝ≥0∞
is not a normed_space
, we need some form of coercion.
See integral_eq_lintegral
for a simpler version.
simple_func.bintegral
and simple_func.integral
agree when the integrand has type
α →ₛ ℝ≥0∞
. But since ℝ≥0∞
is not a normed_space
, we need some form of coercion.
Positive part of a simple function in L1 space.
Equations
Negative part of a simple function in L1 space.
The Bochner integral of L1
#
Define the Bochner integral on α →₁ₛ[μ] E
by extension from the simple functions α →₁ₛ[μ] E
,
and prove basic properties of this integral.
The Bochner integral over simple functions in L1 space.
The Bochner integral over simple functions in L1 space as a continuous linear map.
Equations
- measure_theory.L1.simple_func.integral_clm' α E 𝕜 μ = {to_fun := measure_theory.L1.simple_func.integral _inst_5, map_add' := _, map_smul' := _}.mk_continuous 1 _
The Bochner integral over simple functions in L1 space as a continuous linear map over ℝ.
Equations
The Bochner integral in L1 space as a continuous linear map.
Equations
- measure_theory.L1.integral_clm' 𝕜 = (measure_theory.L1.simple_func.integral_clm' α E 𝕜 μ).extend (measure_theory.Lp.simple_func.coe_to_Lp α E 𝕜) measure_theory.L1.integral_clm'._proof_4 measure_theory.L1.integral_clm'._proof_5
The Bochner integral in L1 space as a continuous linear map over ℝ.
The Bochner integral in L1 space
Equations
The Bochner integral on functions #
Define the Bochner integral on functions generally to be the L1
Bochner integral, for integrable
functions, and 0 otherwise; prove its basic properties.
The Bochner integral
Equations
- measure_theory.integral μ f = dite (measure_theory.integrable f μ) (λ (hf : measure_theory.integrable f μ), measure_theory.L1.integral (measure_theory.integrable.to_L1 f hf)) (λ (hf : ¬measure_theory.integrable f μ), 0)
In the notation for integrals, an expression like ∫ x, g ‖x‖ ∂μ
will not be parsed correctly,
and needs parentheses. We do not set the binding power of r
to 0
, because then
∫ x, f x = 0
will be parsed incorrectly.
If f
has finite integral, then ∫ x in s, f x ∂μ
is absolutely continuous in s
: it tends
to zero as μ s
tends to zero.
If f
is integrable, then ∫ x in s, f x ∂μ
is absolutely continuous in s
: it tends
to zero as μ s
tends to zero.
If F i → f
in L1
, then ∫ x, F i x ∂μ → ∫ x, f x ∂μ
.
Lebesgue dominated convergence theorem provides sufficient conditions under which almost
everywhere convergence of a sequence of functions implies the convergence of their integrals.
We could weaken the condition bound_integrable
to require has_finite_integral bound μ
instead
(i.e. not requiring that bound
is measurable), but in all applications proving integrability
is easier.
Lebesgue dominated convergence theorem for filters with a countable basis
Lebesgue dominated convergence theorem for series.
The Bochner integral of a real-valued function f : α → ℝ
is the difference between the
integral of the positive part of f
and the integral of the negative part of f
.
Hölder's inequality for the integral of a product of norms. The integral of the product of two
norms of functions is bounded by the product of their ℒp
and ℒq
seminorms when p
and q
are
conjugate exponents.
Hölder's inequality for functions α → ℝ
. The integral of the product of two nonnegative
functions is bounded by the product of their ℒp
and ℒq
seminorms when p
and q
are conjugate
exponents.
Simple function seen as simple function of a larger measurable_space
.
Equations
- measure_theory.simple_func.to_larger_space hm f = {to_fun := f.to_fun, measurable_set_fiber' := _, finite_range' := _}