formal/lean/mathlib/analysis/convolution.lean

/-
Copyright (c) 2022 Floris van Doorn. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Floris van Doorn
-/
import measure_theory.group.integration
import measure_theory.group.prod
import measure_theory.function.locally_integrable
import analysis.calculus.specific_functions
import analysis.calculus.parametric_integral

/-!
# Convolution of functions

This file defines the convolution on two functions, i.e. `x ↦ ∫ f(t)g(x - t) ∂t`.
In the general case, these functions can be vector-valued, and have an arbitrary (additive)
group as domain. We use a continuous bilinear operation `L` on these function values as
"multiplication". The domain must be equipped with a Haar measure `μ`
(though many individual results have weaker conditions on `μ`).

For many applications we can take `L = lsmul ℝ ℝ` or `L = lmul ℝ ℝ`.

We also define `convolution_exists` and `convolution_exists_at` to state that the convolution is
well-defined (everywhere or at a single point). These conditions are needed for pointwise
computations (e.g. `convolution_exists_at.distrib_add`), but are generally not stong enough for any
local (or global) properties of the convolution. For this we need stronger assumptions on `f`
and/or `g`, and generally if we impose stronger conditions on one of the functions, we can impose
weaker conditions on the other.
We have proven many of the properties of the convolution assuming one of these functions
has compact support (in which case the other function only needs to be locally integrable).
We still need to prove the properties for other pairs of conditions (e.g. both functions are
rapidly decreasing)

# Design Decisions

We use a bilinear map `L` to "multiply" the two functions in the integrand.
This generality has several advantages

* This allows us to compute the total derivative of the convolution, in case the functions are
  multivariate. The total derivative is again a convolution, but where the codomains of the
  functions can be higher-dimensional. See `has_compact_support.has_fderiv_at_convolution_right`.
* This allows us to use `@[to_additive]` everywhere (which would not be possible if we would use
  `mul`/`smul` in the integral, since `@[to_additive]` will incorrectly also try to additivize
  those definitions).
* We need to support the case where at least one of the functions is vector-valued, but if we use
  `smul` to multiply the functions, that would be an asymmetric definition.

# Main Definitions
* `convolution f g L μ x = (f ⋆[L, μ] g) x = ∫ t, L (f t) (g (x - t)) ∂μ` is the convolution of
  `f` and `g` w.r.t. the continuous bilinear map `L` and measure `μ`.
* `convolution_exists_at f g x L μ` states that the convolution `(f ⋆[L, μ] g) x` is well-defined
  (i.e. the integral exists).
* `convolution_exists f g L μ` states that the convolution `f ⋆[L, μ] g` is well-defined at each
  point.

# Main Results
* `has_compact_support.has_fderiv_at_convolution_right` and
  `has_compact_support.has_fderiv_at_convolution_left`: we can compute the total derivative
  of the convolution as a convolution with the total derivative of the right (left) function.
* `has_compact_support.cont_diff_convolution_right` and
  `has_compact_support.cont_diff_convolution_left`: the convolution is `𝒞ⁿ` if one of the functions
  is `𝒞ⁿ` with compact support and the other function in locally integrable.
* `convolution_tendsto_right`: Given a sequence of nonnegative normalized functions whose support
  tends to a small neighborhood around `0`, the convolution tends to the right argument.
  This is specialized to bump functions in `cont_diff_bump_of_inner.convolution_tendsto_right`.

# Notation
The following notations are localized in the locale `convolution`:
* `f ⋆[L, μ] g` for the convolution. Note: you have to use parentheses to apply the convolution
  to an argument: `(f ⋆[L, μ] g) x`.
* `f ⋆[L] g := f ⋆[L, volume] g`
* `f ⋆ g := f ⋆[lsmul ℝ ℝ] g`

# To do
* Prove properties about the convolution if both functions are rapidly decreasing.
* Use `@[to_additive]` everywhere
-/

open set function filter measure_theory measure_theory.measure topological_space
open continuous_linear_map metric
open_locale pointwise topological_space nnreal

variables {𝕜 G E E' E'' F F' F'' : Type*}
variables [normed_add_comm_group E] [normed_add_comm_group E'] [normed_add_comm_group E'']
  [normed_add_comm_group F] {f f' : G → E} {g g' : G → E'} {x x' : G} {y y' : E}

section nontrivially_normed_field

variables [nontrivially_normed_field 𝕜]
variables [normed_space 𝕜 E] [normed_space 𝕜 E'] [normed_space 𝕜 E''] [normed_space 𝕜 F]
variables (L : E →L[𝕜] E' →L[𝕜] F)

section no_measurability

variables [add_group G] [topological_space G]

lemma has_compact_support.convolution_integrand_bound_right (hcg : has_compact_support g)
  (hg : continuous g) {x t : G} {s : set G} (hx : x ∈ s) :
  ∥L (f t) (g (x - t))∥ ≤ (- tsupport g + s).indicator (λ t, ∥L∥ * ∥f t∥ * (⨆ i, ∥g i∥)) t :=
begin
  refine le_indicator (λ t ht, _) (λ t ht, _) t,
  { refine (L.le_op_norm₂ _ _).trans _,
    exact mul_le_mul_of_nonneg_left
        (le_csupr (hg.norm.bdd_above_range_of_has_compact_support hcg.norm) $ x - t)
        (mul_nonneg (norm_nonneg _) (norm_nonneg _)) },
  { have : x - t ∉ support g,
    { refine mt (λ hxt, _) ht, refine ⟨_, _, set.neg_mem_neg.mpr (subset_closure hxt), hx, _⟩,
      rw [neg_sub, sub_add_cancel] },
    rw [nmem_support.mp this, (L _).map_zero, norm_zero] }
end

lemma continuous.convolution_integrand_fst [has_continuous_sub G] (hg : continuous g) (t : G) :
  continuous (λ x, L (f t) (g (x - t))) :=
L.continuous₂.comp₂ continuous_const $ hg.comp $ continuous_id.sub continuous_const

lemma has_compact_support.convolution_integrand_bound_left (hcf : has_compact_support f)
  (hf : continuous f) {x t : G} {s : set G} (hx : x ∈ s) :
  ∥L (f (x - t)) (g t)∥ ≤ (- tsupport f + s).indicator (λ t, ∥L∥ * (⨆ i, ∥f i∥) * ∥g t∥) t :=
by { convert hcf.convolution_integrand_bound_right L.flip hf hx,
  simp_rw [L.op_norm_flip, mul_right_comm] }

end no_measurability

section measurability

variables [measurable_space G] {μ : measure G}

/-- The convolution of `f` and `g` exists at `x` when the function `t ↦ L (f t) (g (x - t))` is
integrable. There are various conditions on `f` and `g` to prove this. -/
def convolution_exists_at [has_sub G] (f : G → E) (g : G → E') (x : G) (L : E →L[𝕜] E' →L[𝕜] F)
  (μ : measure G . volume_tac) : Prop :=
integrable (λ t, L (f t) (g (x - t))) μ

/-- The convolution of `f` and `g` exists when the function `t ↦ L (f t) (g (x - t))` is integrable
for all `x : G`. There are various conditions on `f` and `g` to prove this. -/
def convolution_exists [has_sub G] (f : G → E) (g : G → E') (L : E →L[𝕜] E' →L[𝕜] F)
  (μ : measure G . volume_tac) : Prop :=
∀ x : G, convolution_exists_at f g x L μ

section convolution_exists

variables {L}
lemma convolution_exists_at.integrable [has_sub G] {x : G} (h : convolution_exists_at f g x L μ) :
  integrable (λ t, L (f t) (g (x - t))) μ :=
h

variables (L)

section group

variables [add_group G]
variables [has_measurable_add₂ G] [has_measurable_neg G]

lemma measure_theory.ae_strongly_measurable.convolution_integrand' [sigma_finite μ]
  (hf : ae_strongly_measurable f μ)
  (hg : ae_strongly_measurable g $ map (λ (p : G × G), p.1 - p.2) (μ.prod μ)) :
  ae_strongly_measurable (λ p : G × G, L (f p.2) (g (p.1 - p.2))) (μ.prod μ) :=
L.ae_strongly_measurable_comp₂ hf.snd $ hg.comp_measurable $ measurable_fst.sub measurable_snd

lemma measure_theory.ae_strongly_measurable.convolution_integrand_snd'
  (hf : ae_strongly_measurable f μ) {x : G}
  (hg : ae_strongly_measurable g $ map (λ t, x - t) μ) :
  ae_strongly_measurable (λ t, L (f t) (g (x - t))) μ :=
L.ae_strongly_measurable_comp₂ hf $ hg.comp_measurable $ measurable_id.const_sub x

lemma measure_theory.ae_strongly_measurable.convolution_integrand_swap_snd'
  {x : G} (hf : ae_strongly_measurable f $ map (λ t, x - t) μ)
  (hg : ae_strongly_measurable g μ) : ae_strongly_measurable (λ t, L (f (x - t)) (g t)) μ :=
L.ae_strongly_measurable_comp₂ (hf.comp_measurable $ measurable_id.const_sub x) hg

/-- A sufficient condition to prove that `f ⋆[L, μ] g` exists.
We assume that the integrand has compact support and `g` is bounded on this support (note that
both properties hold if `g` is continuous with compact support). We also require that `f` is
integrable on the support of the integrand, and that both functions are strongly measurable.

Note: we could weaken the measurability condition to hold only for `μ.restrict s`. -/
lemma bdd_above.convolution_exists_at' {x₀ : G}
  {s : set G} (hbg : bdd_above ((λ i, ∥g i∥) '' ((λ t, - t + x₀) ⁻¹' s)))
  (hs : measurable_set s) (h2s : support (λ t, L (f t) (g (x₀ - t))) ⊆ s)
  (hf : integrable_on f s μ)
  (hmf : ae_strongly_measurable f μ)
  (hmg : ae_strongly_measurable g $ map (λ t, x₀ - t) μ) :
    convolution_exists_at f g x₀ L μ :=
begin
  set s' := (λ t, - t + x₀) ⁻¹' s,
  have : ∀ᵐ (t : G) ∂μ,
    ∥L (f t) (g (x₀ - t))∥ ≤ s.indicator (λ t, ∥L∥ * ∥f t∥ * ⨆ i : s', ∥g i∥) t,
  { refine eventually_of_forall _,
    refine le_indicator (λ t ht, _) (λ t ht, _),
    { refine (L.le_op_norm₂ _ _).trans _,
      refine mul_le_mul_of_nonneg_left
        (le_csupr_set hbg $ mem_preimage.mpr _)
        (mul_nonneg (norm_nonneg _) (norm_nonneg _)),
      rwa [neg_sub, sub_add_cancel] },
    { have : t ∉ support (λ t, L (f t) (g (x₀ - t))) := mt (λ h, h2s h) ht,
      rw [nmem_support.mp this, norm_zero] } },
  refine integrable.mono' _ _ this,
  { rw [integrable_indicator_iff hs], exact (hf.norm.const_mul _).mul_const _ },
  { exact hmf.convolution_integrand_snd' L hmg }
end

section left
variables [sigma_finite μ] [is_add_left_invariant μ]

lemma measure_theory.ae_strongly_measurable.convolution_integrand_snd
  (hf : ae_strongly_measurable f μ) (hg : ae_strongly_measurable g μ)
  (x : G) : ae_strongly_measurable (λ t, L (f t) (g (x - t))) μ :=
hf.convolution_integrand_snd' L $ hg.mono' $ map_sub_left_absolutely_continuous μ x

lemma measure_theory.ae_strongly_measurable.convolution_integrand_swap_snd
  (hf : ae_strongly_measurable f μ) (hg : ae_strongly_measurable g μ)
  (x : G) : ae_strongly_measurable (λ t, L (f (x - t)) (g t)) μ :=
(hf.mono' (map_sub_left_absolutely_continuous μ x)).convolution_integrand_swap_snd' L hg

end left

section right

variables [sigma_finite μ] [is_add_right_invariant μ]

lemma measure_theory.ae_strongly_measurable.convolution_integrand
  (hf : ae_strongly_measurable f μ) (hg : ae_strongly_measurable g μ) :
  ae_strongly_measurable (λ p : G × G, L (f p.2) (g (p.1 - p.2))) (μ.prod μ) :=
hf.convolution_integrand' L $ hg.mono' (quasi_measure_preserving_sub μ).absolutely_continuous

lemma measure_theory.integrable.convolution_integrand (hf : integrable f μ) (hg : integrable g μ) :
  integrable (λ p : G × G, L (f p.2) (g (p.1 - p.2))) (μ.prod μ) :=
begin
  have h_meas : ae_strongly_measurable (λ (p : G × G), L (f p.2) (g (p.1 - p.2))) (μ.prod μ) :=
    hf.ae_strongly_measurable.convolution_integrand L hg.ae_strongly_measurable,
  have h2_meas : ae_strongly_measurable (λ (y : G), ∫ (x : G), ∥L (f y) (g (x - y))∥ ∂μ) μ :=
    h_meas.prod_swap.norm.integral_prod_right',
  simp_rw [integrable_prod_iff' h_meas],
  refine ⟨eventually_of_forall (λ t, (L (f t)).integrable_comp (hg.comp_sub_right t)), _⟩,
  refine integrable.mono' _ h2_meas (eventually_of_forall $
    λ t, (_ : _ ≤ ∥L∥ * ∥f t∥ * ∫ x, ∥g (x - t)∥ ∂μ)),
  { simp_rw [integral_sub_right_eq_self (λ t, ∥ g t ∥)],
    exact (hf.norm.const_mul _).mul_const _ },
  { simp_rw [← integral_mul_left],
    rw [real.norm_of_nonneg],
    { exact integral_mono_of_nonneg (eventually_of_forall $ λ t, norm_nonneg _)
        ((hg.comp_sub_right t).norm.const_mul _) (eventually_of_forall $ λ t, L.le_op_norm₂ _ _) },
    exact integral_nonneg (λ x, norm_nonneg _) }
end

lemma measure_theory.integrable.ae_convolution_exists (hf : integrable f μ) (hg : integrable g μ) :
  ∀ᵐ x ∂μ, convolution_exists_at f g x L μ :=
((integrable_prod_iff $ hf.ae_strongly_measurable.convolution_integrand L
  hg.ae_strongly_measurable).mp $ hf.convolution_integrand L hg).1

end right

variables [topological_space G] [topological_add_group G] [borel_space G]
  [second_countable_topology G] [sigma_compact_space G]

lemma has_compact_support.convolution_exists_at {x₀ : G}
  (h : has_compact_support (λ t, L (f t) (g (x₀ - t)))) (hf : locally_integrable f μ)
  (hg : continuous g) : convolution_exists_at f g x₀ L μ :=
((((homeomorph.neg G).trans $ homeomorph.add_right x₀).compact_preimage.mpr h).bdd_above_image
  hg.norm.continuous_on).convolution_exists_at' L is_closed_closure.measurable_set subset_closure
  (hf h) hf.ae_strongly_measurable hg.ae_strongly_measurable

lemma has_compact_support.convolution_exists_right
  (hcg : has_compact_support g) (hf : locally_integrable f μ) (hg : continuous g) :
  convolution_exists f g L μ :=
begin
  intro x₀,
  refine has_compact_support.convolution_exists_at L _ hf hg,
  refine (hcg.comp_homeomorph (homeomorph.sub_left x₀)).mono _,
  refine λ t, mt (λ ht : g (x₀ - t) = 0, _),
  simp_rw [ht, (L _).map_zero]
end

lemma has_compact_support.convolution_exists_left_of_continuous_right
  (hcf : has_compact_support f) (hf : locally_integrable f μ) (hg : continuous g) :
  convolution_exists f g L μ :=
begin
  intro x₀,
  refine has_compact_support.convolution_exists_at L _ hf hg,
  refine hcf.mono _,
  refine λ t, mt (λ ht : f t = 0, _),
  simp_rw [ht, L.map_zero₂]
end

end group

section comm_group

variables [add_comm_group G]

section measurable_group

variables [has_measurable_add₂ G] [has_measurable_neg G] [is_add_left_invariant μ]

/-- A sufficient condition to prove that `f ⋆[L, μ] g` exists.
We assume that the integrand has compact support and `g` is bounded on this support (note that
both properties hold if `g` is continuous with compact support). We also require that `f` is
integrable on the support of the integrand, and that both functions are strongly measurable.

This is a variant of `bdd_above.convolution_exists_at'` in an abelian group with a left-invariant
measure. This allows us to state the boundedness and measurability of `g` in a more natural way. -/
lemma bdd_above.convolution_exists_at [sigma_finite μ] {x₀ : G}
  {s : set G} (hbg : bdd_above ((λ i, ∥g i∥) '' ((λ t, x₀ - t) ⁻¹' s)))
  (hs : measurable_set s) (h2s : support (λ t, L (f t) (g (x₀ - t))) ⊆ s)
  (hf : integrable_on f s μ)
  (hmf : ae_strongly_measurable f μ)
  (hmg : ae_strongly_measurable g μ) :
    convolution_exists_at f g x₀ L μ :=
begin
  refine bdd_above.convolution_exists_at' L _ hs h2s hf hmf _,
  { simp_rw [← sub_eq_neg_add, hbg] },
  { exact hmg.mono' (map_sub_left_absolutely_continuous μ x₀) }
end

variables {L} [is_neg_invariant μ]

lemma convolution_exists_at_flip :
  convolution_exists_at g f x L.flip μ ↔ convolution_exists_at f g x L μ :=
by simp_rw [convolution_exists_at, ← integrable_comp_sub_left (λ t, L (f t) (g (x - t))) x,
  sub_sub_cancel, flip_apply]

lemma convolution_exists_at.integrable_swap (h : convolution_exists_at f g x L μ) :
  integrable (λ t, L (f (x - t)) (g t)) μ :=
by { convert h.comp_sub_left x, simp_rw [sub_sub_self] }

lemma convolution_exists_at_iff_integrable_swap :
  convolution_exists_at f g x L μ ↔ integrable (λ t, L (f (x - t)) (g t)) μ :=
convolution_exists_at_flip.symm

end measurable_group

variables [topological_space G] [topological_add_group G] [borel_space G]
  [second_countable_topology G] [is_add_left_invariant μ] [is_neg_invariant μ]
  [sigma_compact_space G]

lemma has_compact_support.convolution_exists_left
  (hcf : has_compact_support f) (hf : continuous f) (hg : locally_integrable g μ) :
  convolution_exists f g L μ :=
λ x₀, convolution_exists_at_flip.mp $ hcf.convolution_exists_right L.flip hg hf x₀

lemma has_compact_support.convolution_exists_right_of_continuous_left
  (hcg : has_compact_support g) (hf : continuous f) (hg : locally_integrable g μ) :
  convolution_exists f g L μ :=
λ x₀, convolution_exists_at_flip.mp $
  hcg.convolution_exists_left_of_continuous_right L.flip hg hf x₀

end comm_group

end convolution_exists

variables [normed_space ℝ F] [complete_space F]

/-- The convolution of two functions `f` and `g` with respect to a continuous bilinear map `L` and
measure `μ`. It is defined to be `(f ⋆[L, μ] g) x = ∫ t, L (f t) (g (x - t)) ∂μ`. -/
noncomputable def convolution [has_sub G] (f : G → E) (g : G → E') (L : E →L[𝕜] E' →L[𝕜] F)
  (μ : measure G . volume_tac) : G → F :=
λ x, ∫ t, L (f t) (g (x - t)) ∂μ

localized "notation f ` ⋆[`:67 L:67 `, ` μ:67 `] `:0 g:66 := convolution f g L μ" in convolution
localized "notation f ` ⋆[`:67 L:67 `]`:0 g:66 := convolution f g L
  measure_theory.measure_space.volume" in convolution
localized "notation f ` ⋆ `:67 g:66 := convolution f g (continuous_linear_map.lsmul ℝ ℝ)
  measure_theory.measure_space.volume" in convolution

lemma convolution_def [has_sub G] : (f ⋆[L, μ] g) x = ∫ t, L (f t) (g (x - t)) ∂μ := rfl

/-- The definition of convolution where the bilinear operator is scalar multiplication.
Note: it often helps the elaborator to give the type of the convolution explicitly. -/
lemma convolution_lsmul [has_sub G] {f : G → 𝕜} {g : G → F} :
  (f ⋆[lsmul 𝕜 𝕜, μ] g : G → F) x = ∫ t, f t • g (x - t) ∂μ := rfl

/-- The definition of convolution where the bilinear operator is multiplication. -/
lemma convolution_lmul [has_sub G] [normed_space ℝ 𝕜] [complete_space 𝕜] {f : G → 𝕜} {g : G → 𝕜} :
  (f ⋆[lmul 𝕜 𝕜, μ] g) x = ∫ t, f t * g (x - t) ∂μ := rfl

section group

variables {L} [add_group G]

lemma smul_convolution [smul_comm_class ℝ 𝕜 F]
  {y : 𝕜} : (y • f) ⋆[L, μ] g = y • (f ⋆[L, μ] g) :=
by { ext, simp only [pi.smul_apply, convolution_def, ← integral_smul, L.map_smul₂] }

lemma convolution_smul [smul_comm_class ℝ 𝕜 F]
  {y : 𝕜} : f ⋆[L, μ] (y • g) = y • (f ⋆[L, μ] g) :=
by { ext, simp only [pi.smul_apply, convolution_def, ← integral_smul, (L _).map_smul] }

lemma zero_convolution : 0 ⋆[L, μ] g = 0 :=
by { ext, simp_rw [convolution_def, pi.zero_apply, L.map_zero₂, integral_zero] }

lemma convolution_zero : f ⋆[L, μ] 0 = 0 :=
by { ext, simp_rw [convolution_def, pi.zero_apply, (L _).map_zero, integral_zero] }

lemma convolution_exists_at.distrib_add {x : G} (hfg : convolution_exists_at f g x L μ)
  (hfg' : convolution_exists_at f g' x L μ) :
  (f ⋆[L, μ] (g + g')) x = (f ⋆[L, μ] g) x + (f ⋆[L, μ] g') x :=
by simp only [convolution_def, (L _).map_add, pi.add_apply, integral_add hfg hfg']

lemma convolution_exists.distrib_add (hfg : convolution_exists f g L μ)
  (hfg' : convolution_exists f g' L μ) : f ⋆[L, μ] (g + g') = f ⋆[L, μ] g + f ⋆[L, μ] g' :=
by { ext, exact (hfg x).distrib_add (hfg' x) }

lemma convolution_exists_at.add_distrib {x : G} (hfg : convolution_exists_at f g x L μ)
  (hfg' : convolution_exists_at f' g x L μ) :
  ((f + f') ⋆[L, μ] g) x = (f ⋆[L, μ] g) x + (f' ⋆[L, μ] g) x :=
by simp only [convolution_def, L.map_add₂, pi.add_apply, integral_add hfg hfg']

lemma convolution_exists.add_distrib (hfg : convolution_exists f g L μ)
  (hfg' : convolution_exists f' g L μ) : (f + f') ⋆[L, μ] g = f ⋆[L, μ] g + f' ⋆[L, μ] g :=
by { ext, exact (hfg x).add_distrib (hfg' x) }

variables (L)

lemma convolution_congr [has_measurable_add G] [has_measurable_neg G] [is_add_left_invariant μ]
  [is_neg_invariant μ] (h1 : f =ᵐ[μ] f') (h2 : g =ᵐ[μ] g') :
  f ⋆[L, μ] g = f' ⋆[L, μ] g' :=
begin
  ext x,
  apply integral_congr_ae,
  exact (h1.prod_mk $ h2.comp_tendsto (map_sub_left_ae μ x).le).fun_comp ↿(λ x y, L x y)
end

lemma support_convolution_subset_swap : support (f ⋆[L, μ] g) ⊆ support g + support f :=
begin
  intros x h2x,
  by_contra hx,
  apply h2x,
  simp_rw [set.mem_add, not_exists, not_and_distrib, nmem_support] at hx,
  rw [convolution_def],
  convert integral_zero G F,
  ext t,
  rcases hx (x - t) t with h|h|h,
  { rw [h, (L _).map_zero] },
  { rw [h, L.map_zero₂] },
  { exact (h $ sub_add_cancel x t).elim }
end

variables [topological_space G]
variables [topological_add_group G]

lemma has_compact_support.convolution [t2_space G] (hcf : has_compact_support f)
  (hcg : has_compact_support g) : has_compact_support (f ⋆[L, μ] g) :=
compact_of_is_closed_subset (hcg.is_compact.add hcf) is_closed_closure $ closure_minimal
  ((support_convolution_subset_swap L).trans $ add_subset_add subset_closure subset_closure)
  (hcg.is_compact.add hcf).is_closed

variables [borel_space G] [second_countable_topology G]

/-- The convolution is continuous if one function is locally integrable and the other has compact
support and is continuous. -/
lemma has_compact_support.continuous_convolution_right [locally_compact_space G] [t2_space G]
  (hcg : has_compact_support g) (hf : locally_integrable f μ)
  (hg : continuous g) : continuous (f ⋆[L, μ] g) :=
begin
  refine continuous_iff_continuous_at.mpr (λ x₀, _),
  obtain ⟨K, hK, h2K⟩ := exists_compact_mem_nhds x₀,
  let K' := - tsupport g + K,
  have hK' : is_compact K' := hcg.neg.add hK,
  have : ∀ᶠ x in 𝓝 x₀, ∀ᵐ (t : G) ∂μ,
    ∥L (f t) (g (x - t))∥ ≤ K'.indicator (λ t, ∥L∥ * ∥f t∥ * (⨆ i, ∥g i∥)) t :=
  eventually_of_mem h2K (λ x hx, eventually_of_forall $
    λ t, hcg.convolution_integrand_bound_right L hg hx),
  refine continuous_at_of_dominated _ this _ _,
  { exact eventually_of_forall
      (λ x, hf.ae_strongly_measurable.convolution_integrand_snd' L hg.ae_strongly_measurable) },
  { rw [integrable_indicator_iff hK'.measurable_set],
    exact ((hf hK').norm.const_mul _).mul_const _ },
  { exact eventually_of_forall (λ t, (L.continuous₂.comp₂ continuous_const $
      hg.comp $ continuous_id.sub $ by apply continuous_const).continuous_at) }
end

/-- The convolution is continuous if one function is integrable and the other is bounded and
continuous. -/
lemma bdd_above.continuous_convolution_right_of_integrable
  (hbg : bdd_above (range (λ x, ∥g x∥))) (hf : integrable f μ) (hg : continuous g) :
    continuous (f ⋆[L, μ] g) :=
begin
  refine continuous_iff_continuous_at.mpr (λ x₀, _),
  have : ∀ᶠ x in 𝓝 x₀, ∀ᵐ (t : G) ∂μ,
    ∥L (f t) (g (x - t))∥ ≤ ∥L∥ * ∥f t∥ * (⨆ i, ∥g i∥),
  { refine eventually_of_forall (λ x, eventually_of_forall $ λ t, _),
    refine (L.le_op_norm₂ _ _).trans _,
    exact mul_le_mul_of_nonneg_left (le_csupr hbg $ x - t)
      (mul_nonneg (norm_nonneg _) (norm_nonneg _)) },
  refine continuous_at_of_dominated _ this _ _,
  { exact eventually_of_forall
      (λ x, hf.ae_strongly_measurable.convolution_integrand_snd' L hg.ae_strongly_measurable) },
  { exact (hf.norm.const_mul _).mul_const _ },
  { exact eventually_of_forall (λ t, (L.continuous₂.comp₂ continuous_const $
      hg.comp $ continuous_id.sub $ by apply continuous_const).continuous_at) }
end

/-- A version of `has_compact_support.continuous_convolution_right` that works if `G` is
not locally compact but requires that `g` is integrable. -/
lemma has_compact_support.continuous_convolution_right_of_integrable
  (hcg : has_compact_support g) (hf : integrable f μ) (hg : continuous g) :
    continuous (f ⋆[L, μ] g) :=
(hg.norm.bdd_above_range_of_has_compact_support hcg.norm).continuous_convolution_right_of_integrable
  L hf hg

variables [sigma_finite μ] [is_add_right_invariant μ]

lemma measure_theory.integrable.integrable_convolution (hf : integrable f μ) (hg : integrable g μ) :
  integrable (f ⋆[L, μ] g) μ :=
(hf.convolution_integrand L hg).integral_prod_left

end group

section comm_group

variables [add_comm_group G]

lemma support_convolution_subset : support (f ⋆[L, μ] g) ⊆ support f + support g :=
(support_convolution_subset_swap L).trans (add_comm _ _).subset

variables [topological_space G]
variables [topological_add_group G]
variables [borel_space G]
variables [is_add_left_invariant μ]  [is_neg_invariant μ]

variable (L)
/-- Commutativity of convolution -/
lemma convolution_flip : g ⋆[L.flip, μ] f = f ⋆[L, μ] g :=
begin
  ext1 x,
  simp_rw [convolution_def],
  rw [← integral_sub_left_eq_self _ μ x],
  simp_rw [sub_sub_self, flip_apply]
end

/-- The symmetric definition of convolution. -/
lemma convolution_eq_swap : (f ⋆[L, μ] g) x = ∫ t, L (f (x - t)) (g t) ∂μ :=
by { rw [← convolution_flip], refl }

/-- The symmetric definition of convolution where the bilinear operator is scalar multiplication. -/
lemma convolution_lsmul_swap {f : G → 𝕜} {g : G → F}:
  (f ⋆[lsmul 𝕜 𝕜, μ] g : G → F) x = ∫ t, f (x - t) • g t ∂μ :=
convolution_eq_swap _

/-- The symmetric definition of convolution where the bilinear operator is multiplication. -/
lemma convolution_lmul_swap [normed_space ℝ 𝕜] [complete_space 𝕜] {f : G → 𝕜} {g : G → 𝕜} :
  (f ⋆[lmul 𝕜 𝕜, μ] g) x = ∫ t, f (x - t) * g t ∂μ :=
convolution_eq_swap _

variables [second_countable_topology G]

lemma has_compact_support.continuous_convolution_left [locally_compact_space G] [t2_space G]
  (hcf : has_compact_support f) (hf : continuous f) (hg : locally_integrable g μ) :
    continuous (f ⋆[L, μ] g) :=
by { rw [← convolution_flip], exact hcf.continuous_convolution_right L.flip hg hf }

lemma bdd_above.continuous_convolution_left_of_integrable
  (hbf : bdd_above (range (λ x, ∥f x∥))) (hf : continuous f) (hg : integrable g μ) :
    continuous (f ⋆[L, μ] g) :=
by { rw [← convolution_flip], exact hbf.continuous_convolution_right_of_integrable L.flip hg hf }

/-- A version of `has_compact_support.continuous_convolution_left` that works if `G` is
not locally compact but requires that `g` is integrable. -/
lemma has_compact_support.continuous_convolution_left_of_integrable
  (hcf : has_compact_support f) (hf : continuous f) (hg : integrable g μ) :
    continuous (f ⋆[L, μ] g) :=
by { rw [← convolution_flip], exact hcf.continuous_convolution_right_of_integrable L.flip hg hf }

end comm_group

section normed_add_comm_group

variables [seminormed_add_comm_group G]

/-- Compute `(f ⋆ g) x₀` if the support of the `f` is within `metric.ball 0 R`, and `g` is constant
on `metric.ball x₀ R`.

We can simplify the RHS further if we assume `f` is integrable, but also if `L = (•)` or more
generally if `L` has a `antilipschitz_with`-condition. -/
lemma convolution_eq_right' {x₀ : G} {R : ℝ}
  (hf : support f ⊆ ball (0 : G) R)
  (hg : ∀ x ∈ ball x₀ R, g x = g x₀) : (f ⋆[L, μ] g) x₀ = ∫ t, L (f t) (g x₀) ∂μ :=
begin
  have h2 : ∀ t, L (f t) (g (x₀ - t)) = L (f t) (g x₀),
  { intro t, by_cases ht : t ∈ support f,
    { have h2t := hf ht,
      rw [mem_ball_zero_iff] at h2t,
      specialize hg (x₀ - t),
      rw [sub_eq_add_neg, add_mem_ball_iff_norm, norm_neg, ← sub_eq_add_neg] at hg,
      rw [hg h2t] },
    { rw [nmem_support] at ht,
      simp_rw [ht, L.map_zero₂] } },
  simp_rw [convolution_def, h2],
end

variables [borel_space G] [second_countable_topology G]
variables [is_add_left_invariant μ] [sigma_finite μ]

/-- Approximate `(f ⋆ g) x₀` if the support of the `f` is bounded within a ball, and `g` is near
`g x₀` on a ball with the same radius around `x₀`. See `dist_convolution_le` for a special case.

We can simplify the second argument of `dist` further if we assume `f` is integrable, but also if
`L = (•)` or more generally if `L` has a `antilipschitz_with`-condition. -/
lemma dist_convolution_le' {x₀ : G} {R ε : ℝ}
  (hε : 0 ≤ ε)
  (hif : integrable f μ)
  (hf : support f ⊆ ball (0 : G) R)
  (hmg : ae_strongly_measurable g μ)
  (hg : ∀ x ∈ ball x₀ R, dist (g x) (g x₀) ≤ ε) :
  dist ((f ⋆[L, μ] g : G → F) x₀) (∫ t, L (f t) (g x₀) ∂μ) ≤ ∥L∥ * ∫ x, ∥f x∥ ∂μ * ε :=
begin
  have hfg : convolution_exists_at f g x₀ L μ,
  { refine bdd_above.convolution_exists_at L _ metric.is_open_ball.measurable_set
    (subset_trans _ hf) hif.integrable_on hif.ae_strongly_measurable hmg,
    swap, { refine λ t, mt (λ ht : f t = 0, _), simp_rw [ht, L.map_zero₂] },
    rw [bdd_above_def],
    refine ⟨∥g x₀∥ + ε, _⟩,
    rintro _ ⟨x, hx, rfl⟩,
    refine norm_le_norm_add_const_of_dist_le (hg x _),
    rwa [mem_ball_iff_norm, norm_sub_rev, ← mem_ball_zero_iff] },
  have h2 : ∀ t, dist (L (f t) (g (x₀ - t))) (L (f t) (g x₀)) ≤ ∥L (f t)∥ * ε,
  { intro t, by_cases ht : t ∈ support f,
    { have h2t := hf ht,
      rw [mem_ball_zero_iff] at h2t,
      specialize hg (x₀ - t),
      rw [sub_eq_add_neg, add_mem_ball_iff_norm, norm_neg, ← sub_eq_add_neg] at hg,
      refine ((L (f t)).dist_le_op_norm _ _).trans _,
      exact mul_le_mul_of_nonneg_left (hg h2t) (norm_nonneg _) },
    { rw [nmem_support] at ht,
      simp_rw [ht, L.map_zero₂, L.map_zero, norm_zero, zero_mul, dist_self] } },
  simp_rw [convolution_def],
  simp_rw [dist_eq_norm] at h2 ⊢,
  rw [← integral_sub hfg.integrable], swap, { exact (L.flip (g x₀)).integrable_comp hif },
  refine (norm_integral_le_of_norm_le ((L.integrable_comp hif).norm.mul_const ε)
    (eventually_of_forall h2)).trans _,
  rw [integral_mul_right],
  refine mul_le_mul_of_nonneg_right _ hε,
  have h3 : ∀ t, ∥L (f t)∥ ≤ ∥L∥ * ∥f t∥ := λ t, L.le_op_norm (f t),
  refine (integral_mono (L.integrable_comp hif).norm (hif.norm.const_mul _) h3).trans_eq _,
  rw [integral_mul_left]
end

variables [normed_space ℝ E] [normed_space ℝ E'] [complete_space E']

/-- Approximate `f ⋆ g` if the support of the `f` is bounded within a ball, and `g` is near `g x₀`
on a ball with the same radius around `x₀`.

This is a special case of `dist_convolution_le'` where `L` is `(•)`, `f` has integral 1 and `f` is
nonnegative. -/
lemma dist_convolution_le {f : G → ℝ} {x₀ : G} {R ε : ℝ}
  (hε : 0 ≤ ε)
  (hf : support f ⊆ ball (0 : G) R)
  (hnf : ∀ x, 0 ≤ f x)
  (hintf : ∫ x, f x ∂μ = 1)
  (hmg : ae_strongly_measurable g μ)
  (hg : ∀ x ∈ ball x₀ R, dist (g x) (g x₀) ≤ ε) :
  dist ((f ⋆[lsmul ℝ ℝ, μ] g : G → E') x₀) (g x₀) ≤ ε :=
begin
  have hif : integrable f μ,
  { by_contra hif, exact zero_ne_one ((integral_undef hif).symm.trans hintf) },
  convert (dist_convolution_le' _ hε hif hf hmg hg).trans _,
  { simp_rw [lsmul_apply, integral_smul_const, hintf, one_smul] },
  { simp_rw [real.norm_of_nonneg (hnf _), hintf, mul_one],
    exact (mul_le_mul_of_nonneg_right op_norm_lsmul_le hε).trans_eq (one_mul ε) }
end

/-- `(φ i ⋆ g) x₀` tends to `g x₀` if `φ` is a sequence of nonnegative functions with integral 1
whose support tends to small neighborhoods around `(0 : G)` and `g` is continuous at `x₀`.

See also `cont_diff_bump_of_inner.convolution_tendsto_right'`. -/
lemma convolution_tendsto_right {ι} {l : filter ι} {φ : ι → G → ℝ}
  (hnφ : ∀ i x, 0 ≤ φ i x)
  (hiφ : ∀ i, ∫ s, φ i s ∂μ = 1)
  (hφ : tendsto (λ n, support (φ n)) l (𝓝 0).small_sets)
  (hmg : ae_strongly_measurable g μ) {x₀ : G} (hcg : continuous_at g x₀) :
  tendsto (λ i, (φ i ⋆[lsmul ℝ ℝ, μ] g : G → E') x₀) l (𝓝 (g x₀)) :=
begin
  simp_rw [tendsto_small_sets_iff] at hφ,
  rw [metric.continuous_at_iff] at hcg,
  rw [metric.tendsto_nhds],
  intros ε hε,
  rcases hcg (ε / 2) (half_pos hε) with ⟨δ, hδ, hgδ⟩,
  refine (hφ (ball (0 : G) δ) $ ball_mem_nhds _ hδ).mono (λ i hi, _),
  exact (dist_convolution_le (half_pos hε).le hi (hnφ i) (hiφ i) hmg (λ x hx, (hgδ hx.out).le))
    .trans_lt (half_lt_self hε)
end

end normed_add_comm_group

namespace cont_diff_bump_of_inner

variables {n : with_top ℕ}
variables [normed_space ℝ E']
variables [inner_product_space ℝ G]
variables [complete_space E']
variables {a : G} {φ : cont_diff_bump_of_inner (0 : G)}

/-- If `φ` is a bump function, compute `(φ ⋆ g) x₀` if `g` is constant on `metric.ball x₀ φ.R`. -/
lemma convolution_eq_right {x₀ : G}
  (hg : ∀ x ∈ ball x₀ φ.R, g x = g x₀) : (φ ⋆[lsmul ℝ ℝ, μ] g : G → E') x₀ = integral μ φ • g x₀ :=
by simp_rw [convolution_eq_right' _ φ.support_eq.subset hg, lsmul_apply, integral_smul_const]

variables [borel_space G]
variables [is_locally_finite_measure μ] [is_open_pos_measure μ]
variables [finite_dimensional ℝ G]

/-- If `φ` is a normed bump function, compute `φ ⋆ g` if `g` is constant on `metric.ball x₀ φ.R`. -/
lemma normed_convolution_eq_right {x₀ : G}
  (hg : ∀ x ∈ ball x₀ φ.R, g x = g x₀) : (φ.normed μ ⋆[lsmul ℝ ℝ, μ] g : G → E') x₀ = g x₀ :=
by { simp_rw [convolution_eq_right' _ φ.support_normed_eq.subset hg, lsmul_apply],
  exact integral_normed_smul φ μ (g x₀) }

variables [is_add_left_invariant μ]

/-- If `φ` is a normed bump function, approximate `(φ ⋆ g) x₀` if `g` is near `g x₀` on a ball with
radius `φ.R` around `x₀`. -/
lemma dist_normed_convolution_le {x₀ : G} {ε : ℝ}
  (hmg : ae_strongly_measurable g μ)
  (hg : ∀ x ∈ ball x₀ φ.R, dist (g x) (g x₀) ≤ ε) :
  dist ((φ.normed μ ⋆[lsmul ℝ ℝ, μ] g : G → E') x₀) (g x₀) ≤ ε :=
dist_convolution_le (by simp_rw [← dist_self (g x₀), hg x₀ (mem_ball_self φ.R_pos)])
  φ.support_normed_eq.subset φ.nonneg_normed φ.integral_normed hmg hg

/-- If `φ i` is a sequence of normed bump function, `(φ i ⋆ g) x₀` tends to `g x₀` if `(φ i).R`
tends to `0` and `g` is continuous at `x₀`. -/
lemma convolution_tendsto_right' {ι} {φ : ι → cont_diff_bump_of_inner (0 : G)}
  {l : filter ι} (hφ : tendsto (λ i, (φ i).R) l (𝓝 0))
  (hmg : ae_strongly_measurable g μ) {x₀ : G} (hcg : continuous_at g x₀) :
  tendsto (λ i, ((λ x, (φ i).normed μ x) ⋆[lsmul ℝ ℝ, μ] g : G → E') x₀) l (𝓝 (g x₀)) :=
begin
  refine convolution_tendsto_right (λ i, (φ i).nonneg_normed) (λ i, (φ i).integral_normed)
    _ hmg hcg,
  rw [normed_add_comm_group.tendsto_nhds_zero] at hφ,
  rw [tendsto_small_sets_iff],
  intros t ht,
  rcases metric.mem_nhds_iff.mp ht with ⟨ε, hε, ht⟩,
  refine (hφ ε hε).mono (λ i hi, subset_trans _ ht),
  simp_rw [(φ i).support_normed_eq],
  rw [real.norm_eq_abs, abs_eq_self.mpr (φ i).R_pos.le] at hi,
  exact ball_subset_ball hi.le
end

/-- Special case of `cont_diff_bump_of_inner.convolution_tendsto_right'` where `g` is continuous. -/
lemma convolution_tendsto_right {ι} {φ : ι → cont_diff_bump_of_inner (0 : G)}
  {l : filter ι} (hφ : tendsto (λ i, (φ i).R) l (𝓝 0))
  (hg : continuous g) (x₀ : G) :
  tendsto (λ i, ((λ x, (φ i).normed μ x) ⋆[lsmul ℝ ℝ, μ] g : G → E') x₀) l (𝓝 (g x₀)) :=
convolution_tendsto_right' hφ hg.ae_strongly_measurable hg.continuous_at

end cont_diff_bump_of_inner

end measurability

end nontrivially_normed_field

open_locale convolution


section is_R_or_C

variables [is_R_or_C 𝕜]
variables [normed_space 𝕜 E]
variables [normed_space 𝕜 E']
variables [normed_space 𝕜 E'']
variables [normed_space ℝ F] [normed_space 𝕜 F]
variables {n : with_top ℕ}
variables [complete_space F]
variables [measurable_space G] {μ : measure G}
variables (L : E →L[𝕜] E' →L[𝕜] F)

section assoc
variables [normed_add_comm_group F'] [normed_space ℝ F'] [normed_space 𝕜 F'] [complete_space F']
variables [normed_add_comm_group F''] [normed_space ℝ F''] [normed_space 𝕜 F''] [complete_space F'']
variables {k : G → E''}
variables (L₂ : F →L[𝕜] E'' →L[𝕜] F')
variables (L₃ : E →L[𝕜] F'' →L[𝕜] F')
variables (L₄ : E' →L[𝕜] E'' →L[𝕜] F'')
variables [add_group G] [has_measurable_add G]
variables [sigma_finite μ]
variables {ν : measure G} [sigma_finite ν] [is_add_right_invariant ν]

/-- Convolution is associative.
To do: prove that `hi` follows from simpler conditions. -/
lemma convolution_assoc (hL : ∀ (x : E) (y : E') (z : E''), L₂ (L x y) z = L₃ x (L₄ y z))
  {x₀ : G}
  (h₄ : convolution_exists g k L₄ ν)
  (h₁ : convolution_exists f g L μ)
  (hi : integrable (uncurry (λ x y, (L₃ (f y)) ((L₄ (g (x - y))) (k (x₀ - x))))) (ν.prod μ)) :
  ((f ⋆[L, μ] g) ⋆[L₂, ν] k) x₀ = (f ⋆[L₃, μ] (g ⋆[L₄, ν] k)) x₀ :=
begin
  have h1 := λ t, (L₂.flip (k (x₀ - t))).integral_comp_comm (h₁ t),
  dsimp only [flip_apply] at h1,
  simp_rw [convolution_def, ← (L₃ (f _)).integral_comp_comm (h₄ (x₀ - _)), ← h1, hL],
  rw [integral_integral_swap hi],
  congr', ext t,
  rw [eq_comm, ← integral_sub_right_eq_self _ t],
  { simp_rw [sub_sub_sub_cancel_right] },
  { apply_instance },
end

end assoc

variables [normed_add_comm_group G] [borel_space G]
variables [second_countable_topology G] [sigma_compact_space G]

lemma convolution_precompR_apply {g : G → E'' →L[𝕜] E'}
  (hf : locally_integrable f μ) (hcg : has_compact_support g) (hg : continuous g)
  (x₀ : G) (x : E'') : (f ⋆[L.precompR E'', μ] g) x₀ x = (f ⋆[L, μ] (λ a, g a x)) x₀  :=
begin
  have := hcg.convolution_exists_right (L.precompR E'') hf hg x₀,
  simp_rw [convolution_def, continuous_linear_map.integral_apply this],
  refl,
end

variables [sigma_finite μ] [is_add_left_invariant μ]
variables [normed_space 𝕜 G] [proper_space G]

/-- Compute the total derivative of `f ⋆ g` if `g` is `C^1` with compact support and `f` is locally
integrable. To write down the total derivative as a convolution, we use
`continuous_linear_map.precompR`. -/
lemma has_compact_support.has_fderiv_at_convolution_right
  (hcg : has_compact_support g) (hf : locally_integrable f μ) (hg : cont_diff 𝕜 1 g) (x₀ : G) :
  has_fderiv_at (f ⋆[L, μ] g) ((f ⋆[L.precompR G, μ] fderiv 𝕜 g) x₀) x₀ :=
begin
  set L' := L.precompR G,
  have h1 : ∀ᶠ x in 𝓝 x₀, ae_strongly_measurable (λ t, L (f t) (g (x - t))) μ :=
  eventually_of_forall
    (hf.ae_strongly_measurable.convolution_integrand_snd L hg.continuous.ae_strongly_measurable),
  have h2 : ∀ x, ae_strongly_measurable (λ t, L' (f t) (fderiv 𝕜 g (x - t))) μ,
  { exact hf.ae_strongly_measurable.convolution_integrand_snd L'
      (hg.continuous_fderiv le_rfl).ae_strongly_measurable },
  have h3 : ∀ x t, has_fderiv_at (λ x, g (x - t)) (fderiv 𝕜 g (x - t)) x,
  { intros x t,
    simpa using (hg.differentiable le_rfl).differentiable_at.has_fderiv_at.comp x
      ((has_fderiv_at_id x).sub (has_fderiv_at_const t x)) },
  let K' := - tsupport (fderiv 𝕜 g) + closed_ball x₀ 1,
  have hK' : is_compact K' := (hcg.fderiv 𝕜).neg.add (is_compact_closed_ball x₀ 1),
  refine has_fderiv_at_integral_of_dominated_of_fderiv_le
    zero_lt_one h1 _ (h2 x₀) _ _ _,
  { exact K'.indicator (λ t, ∥L'∥ * ∥f t∥ * (⨆ x, ∥fderiv 𝕜 g x∥)) },
  { exact hcg.convolution_exists_right L hf hg.continuous x₀ },
  { refine eventually_of_forall (λ t x hx, _),
    exact (hcg.fderiv 𝕜).convolution_integrand_bound_right L'
      (hg.continuous_fderiv le_rfl) (ball_subset_closed_ball hx) },
  { rw [integrable_indicator_iff hK'.measurable_set],
    exact ((hf hK').norm.const_mul _).mul_const _ },
  { exact eventually_of_forall (λ t x hx, (L _).has_fderiv_at.comp x (h3 x t)) },
end

lemma has_compact_support.has_fderiv_at_convolution_left [is_neg_invariant μ]
  (hcf : has_compact_support f) (hf : cont_diff 𝕜 1 f) (hg : locally_integrable g μ) (x₀ : G) :
  has_fderiv_at (f ⋆[L, μ] g) ((fderiv 𝕜 f ⋆[L.precompL G, μ] g) x₀) x₀ :=
begin
  simp only [← convolution_flip] {single_pass := tt},
  exact hcf.has_fderiv_at_convolution_right L.flip hg hf x₀,
end

lemma has_compact_support.cont_diff_convolution_right [finite_dimensional 𝕜 G]
  (hcg : has_compact_support g) (hf : locally_integrable f μ) (hg : cont_diff 𝕜 n g) :
  cont_diff 𝕜 n (f ⋆[L, μ] g) :=
begin
  induction n using with_top.nat_induction with n ih ih generalizing g,
  { rw [cont_diff_zero] at hg ⊢,
    exact hcg.continuous_convolution_right L hf hg },
  { have h : ∀ x, has_fderiv_at (f ⋆[L, μ] g) ((f ⋆[L.precompR G, μ] fderiv 𝕜 g) x) x :=
      hcg.has_fderiv_at_convolution_right L hf hg.one_of_succ,
    rw cont_diff_succ_iff_fderiv_apply,
    split,
    { exact λ x₀, ⟨_, h x₀⟩ },
    { simp_rw [fderiv_eq h, convolution_precompR_apply L hf (hcg.fderiv 𝕜)
        (hg.one_of_succ.continuous_fderiv le_rfl)],
      intro x,
      refine ih _ _,
      { refine @has_compact_support.comp_left _ _ _ _ _ _ (λ (G : _ →L[𝕜] _), G x) _
          (hcg.fderiv 𝕜) (continuous_linear_map.zero_apply x) },
      { revert x, rw [← cont_diff_clm_apply],
        exact (cont_diff_succ_iff_fderiv.mp hg).2 } } },
  { rw [cont_diff_top] at hg ⊢, exact λ n, ih n hcg (hg n) }
end

lemma has_compact_support.cont_diff_convolution_left [finite_dimensional 𝕜 G] [is_neg_invariant μ]
  (hcf : has_compact_support f) (hf : cont_diff 𝕜 n f) (hg : locally_integrable g μ) :
  cont_diff 𝕜 n (f ⋆[L, μ] g) :=
by { rw [← convolution_flip], exact hcf.cont_diff_convolution_right L.flip hg hf }

end is_R_or_C

section real
/-! The one-variable case -/

variables [is_R_or_C 𝕜]
variables [normed_space 𝕜 E]
variables [normed_space 𝕜 E']
variables [normed_space ℝ F] [normed_space 𝕜 F]
variables {f₀ : 𝕜 → E} {g₀ : 𝕜 → E'}
variables {n : with_top ℕ}
variables (L : E →L[𝕜] E' →L[𝕜] F)
variables [complete_space F]
variables {μ : measure 𝕜}
variables [is_add_left_invariant μ] [sigma_finite μ]

lemma has_compact_support.has_deriv_at_convolution_right
  (hf : locally_integrable f₀ μ) (hcg : has_compact_support g₀) (hg : cont_diff 𝕜 1 g₀)
  (x₀ : 𝕜) :
  has_deriv_at (f₀ ⋆[L, μ] g₀) ((f₀ ⋆[L, μ] deriv g₀) x₀) x₀ :=
begin
  convert (hcg.has_fderiv_at_convolution_right L hf hg x₀).has_deriv_at,
  rw [convolution_precompR_apply L hf (hcg.fderiv 𝕜) (hg.continuous_fderiv le_rfl)],
  refl,
end

lemma has_compact_support.has_deriv_at_convolution_left [is_neg_invariant μ]
  (hcf : has_compact_support f₀) (hf : cont_diff 𝕜 1 f₀)
  (hg : locally_integrable g₀ μ) (x₀ : 𝕜) :
  has_deriv_at (f₀ ⋆[L, μ] g₀) ((deriv f₀ ⋆[L, μ] g₀) x₀) x₀ :=
begin
  simp only [← convolution_flip] {single_pass := tt},
  exact hcf.has_deriv_at_convolution_right L.flip hg hf x₀,
end

end real