Bochner integral #
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 using
the L1 Bochner integral constructed in the file Mathlib.MeasureTheory.Integral.BochnerL1
.
Main definitions #
The Bochner integral is defined through the extension process described in the file
Mathlib.MeasureTheory.Integral.SetToL1
, which follows these steps:
MeasureTheory.integral
: the Bochner integral on functions defined 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
setToFun (dominatedFinMeasAdditive_weightedSMul μ) f
. Some basic properties of the integral
(like linearity) are particular cases of the properties of setToFun
(which are described in the
file Mathlib.MeasureTheory.Integral.SetToL1
).
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_pos_part_sub_lintegral_neg_part
:∫ 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
(In the file
Mathlib.MeasureTheory.Integral.DominatedConvergence
)tendsto_integral_of_dominated_convergence
: the Lebesgue dominated convergence theorem(In the file
Mathlib.MeasureTheory.Integral.SetIntegral
) integration commutes with continuous linear maps.
ContinuousLinearMap.integral_comp_comm
LinearIsometry.integral_comp_comm
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
Mathlib.MeasureTheory.Function.SimpleFuncDenseLp
(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_pos_part_sub_lintegral_neg_part
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_pos_part_sub_lintegral_neg_part
is scattered in sections with the name posPart
.
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.toReal (∫⁻ a, ENNReal.ofReal <| ‖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
usingisClosed_eq
.Show that the property holds for all simple functions
s
inL¹
space.Typically, you need to convert various notions to their
SimpleFunc
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 isClosed_property
or DenseRange.induction_on
for this argument.
Notations #
α →ₛ E
: simple functions (defined inMathlib/MeasureTheory/Function/SimpleFunc.lean
)α →₁[μ] E
: functions in L1 space, i.e., equivalence classes of integrable functions (defined inMathlib/MeasureTheory/Function/LpSpace/Basic.lean
)∫ 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
Mathlib/MeasureTheory/Integral/SetIntegral.lean
.
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
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
- MeasureTheory.integral μ f = if x : CompleteSpace G then if hf : MeasureTheory.Integrable f μ then MeasureTheory.L1.integral (MeasureTheory.Integrable.toL1 f hf) else 0 else 0
Instances For
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.
The Bochner integral
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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
.
If F i → f
in L1
, then ∫ x, F i x ∂μ → ∫ x, f x ∂μ
.
If F i → f
in L1
, then ∫ x in s, F i x ∂μ → ∫ x in s, f x ∂μ
.
If F i → f
in L1
, then ∫ x in s, F i x ∂μ → ∫ x in s, f x ∂μ
.
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
.
Alias of MeasureTheory.ofReal_integral_norm_eq_lintegral_enorm
.
Monotone convergence theorem for real-valued functions and Bochner integrals
Monotone convergence theorem for real-valued functions and Bochner integrals
If a monotone sequence of functions has an upper bound and the sequence of integrals of these functions tends to the integral of the upper bound, then the sequence of functions converges almost everywhere to the upper bound.
If an antitone sequence of functions has a lower bound and the sequence of integrals of these functions tends to the integral of the lower bound, then the sequence of functions converges almost everywhere to the lower bound.
Alias of Topology.IsClosedEmbedding.integral_map
.
Markov's inequality also known as Chebyshev's first inequality.
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 MeasurableSpace
.
Equations
- MeasureTheory.SimpleFunc.toLargerSpace hm f = { toFun := f.toFun, measurableSet_fiber' := ⋯, finite_range' := ⋯ }
Instances For
Positivity extension for integrals.
This extension only proves non-negativity, strict positivity is more delicate for integration and requires more assumptions.