Density of simple functions #
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Show that each Lᵖ Borel measurable function can be approximated in Lᵖ norm
by a sequence of simple functions.
Main definitions #
measure_theory.Lp.simple_func, the type ofLpsimple functionscoe_to_Lp, the embedding ofLp.simple_func E p μintoLp E p μ
Main results #
tendsto_approx_on_univ_Lp(Lᵖ convergence): IfEis anormed_add_comm_groupandfis measurable andmem_ℒp(forp < ∞), then the simple functionssimple_func.approx_on f hf s 0 h₀ nmay be considered as elements ofLp E p μ, and they tend in Lᵖ tof.Lp.simple_func.dense_embedding: the embeddingcoe_to_Lpof theLpsimple functions intoLpis dense.Lp.simple_func.induction,Lp.induction,mem_ℒp.induction,integrable.induction: to prove a predicate for all elements of one of these classes of functions, it suffices to check that it behaves correctly on simple functions.
TODO #
For E finite-dimensional, simple functions α →ₛ E are dense in L^∞ -- prove this.
Notations #
α →ₛ β(local notation): the type of simple functionsα → β.α →₁ₛ[μ] E: the type ofL1simple functionsα → β.
Lp approximation by simple functions #
Any function in ℒp can be approximated by a simple function if p < ∞.
L1 approximation by simple functions #
Properties of simple functions in Lp spaces #
A simple function f : α →ₛ E into a normed group E verifies, for a measure μ:
mem_ℒp f 0 μandmem_ℒp f ∞ μ, sincefis a.e.-measurable and bounded,- for
0 < p < ∞,mem_ℒp f p μ ↔ integrable f μ ↔ f.fin_meas_supp μ ↔ ∀ y ≠ 0, μ (f ⁻¹' {y}) < ∞.
Construction of the space of Lp simple functions, and its dense embedding into Lp.
Lp.simple_func is a subspace of Lp consisting of equivalence classes of an integrable simple
function.
Equations
- measure_theory.Lp.simple_func E p μ = {carrier := {f : ↥(measure_theory.Lp E p μ) | ∃ (s : measure_theory.simple_func α E), measure_theory.ae_eq_fun.mk ⇑s _ = ↑f}, add_mem' := _, zero_mem' := _, neg_mem' := _}
Instances for ↥measure_theory.Lp.simple_func
Simple functions in Lp space form a normed_space.
Implementation note: If Lp.simple_func E p μ were defined as a 𝕜-submodule of Lp E p μ,
then the next few lemmas, putting a normed 𝕜-group structure on Lp.simple_func E p μ, would be
unnecessary. But instead, Lp.simple_func E p μ is defined as an add_subgroup of Lp E p μ,
which does not permit this (but has the advantage of working when E itself is a normed group,
i.e. has no scalar action).
If E is a normed space, Lp.simple_func E p μ is a has_smul. Not declared as an
instance as it is (as of writing) used only in the construction of the Bochner integral.
Equations
- measure_theory.Lp.simple_func.has_smul = {smul := λ (k : 𝕜) (f : ↥(measure_theory.Lp.simple_func E p μ)), ⟨k • ↑f, _⟩}
If E is a normed space, Lp.simple_func E p μ is a module. Not declared as an
instance as it is (as of writing) used only in the construction of the Bochner integral.
Equations
- measure_theory.Lp.simple_func.module = {to_distrib_mul_action := {to_mul_action := {to_has_smul := measure_theory.Lp.simple_func.has_smul _inst_6, one_smul := _, mul_smul := _}, smul_zero := _, smul_add := _}, add_smul := _, zero_smul := _}
If E is a normed space, Lp.simple_func E p μ is a normed space. Not declared as an
instance as it is (as of writing) used only in the construction of the Bochner integral.
If E is a normed space, Lp.simple_func E p μ is a normed space. Not declared as an
instance as it is (as of writing) used only in the construction of the Bochner integral.
Equations
- measure_theory.Lp.simple_func.normed_space = {to_module := measure_theory.Lp.simple_func.module measure_theory.Lp.simple_func.normed_space._proof_1, norm_smul_le := _}
Construct the equivalence class [f] of a simple function f satisfying mem_ℒp.
Equations
Find a representative of a Lp.simple_func.
Equations
(to_simple_func f) is measurable.
to_simple_func f satisfies the predicate mem_ℒp.
The characteristic function of a finite-measure measurable set s, as an Lp simple function.
Equations
To prove something for an arbitrary Lp simple function, with 0 < p < ∞, it suffices to show
that the property holds for (multiples of) characteristic functions of finite-measure measurable
sets and is closed under addition (of functions with disjoint support).
The embedding of Lp simple functions into Lp functions, as a continuous linear map.
Equations
- measure_theory.Lp.simple_func.coe_to_Lp α E 𝕜 = {to_linear_map := {to_fun := (measure_theory.Lp.simple_func E p μ).subtype.to_fun, map_add' := _, map_smul' := _}, cont := _}
Coercion from nonnegative simple functions of Lp to nonnegative functions of Lp.
Equations
- measure_theory.Lp.simple_func.coe_simple_func_nonneg_to_Lp_nonneg p μ G = λ (g : {g // 0 ≤ g}), ⟨↑g, _⟩
To prove something for an arbitrary Lp function in a second countable Borel normed group, it
suffices to show that
- the property holds for (multiples of) characteristic functions;
- is closed under addition;
- the set of functions in
Lpfor which the property holds is closed.
To prove something for an arbitrary mem_ℒp function in a second countable
Borel normed group, it suffices to show that
- the property holds for (multiples of) characteristic functions;
- is closed under addition;
- the set of functions in the
Lᵖspace for which the property holds is closed. - the property is closed under the almost-everywhere equal relation.
It is possible to make the hypotheses in the induction steps a bit stronger, and such conditions
can be added once we need them (for example in h_add it is only necessary to consider the sum of
a simple function with a multiple of a characteristic function and that the intersection
of their images is a subset of {0}).
If a set of ae strongly measurable functions is stable under addition and approximates
characteristic functions in ℒp, then it is dense in ℒp.
To prove something for an arbitrary integrable function in a normed group, it suffices to show that
- the property holds for (multiples of) characteristic functions;
- is closed under addition;
- the set of functions in the
L¹space for which the property holds is closed. - the property is closed under the almost-everywhere equal relation.
It is possible to make the hypotheses in the induction steps a bit stronger, and such conditions
can be added once we need them (for example in h_add it is only necessary to consider the sum of
a simple function with a multiple of a characteristic function and that the intersection
of their images is a subset of {0}).