mathlib-initiative/mathlib-tactics huggingface dataset:
Module: Mathlib.Order.Sublocale

Goal state before:
pp: X : Type u_1
inst✝ : Order.Frame X
a : Sublocale X
s : Set (Sublocale X)
⊢ ⨅ b ∈ s, a ⊔ b ≤ a ⊔ sInf s

Tactic:
simp [← toNucleus_le_toNucleus,
    nucleusIsoSublocale.symm_eq_toNucleus, nucleusIsoSublocale.symm.map_sup,
    nucleusIsoSublocale.symm.map_sInf, sup_iInf_eq, nucleusIsoSublocale.symm.map_iInf]

Goal state after:
Module: Mathlib.Probability.Martingale.Centering

Goal state before:
pp: Ω : Type u_1
E : Type u_2
m0 : MeasurableSpace Ω
μ : Measure Ω
inst✝² : NormedAddCommGroup E
inst✝¹ : NormedSpace ℝ E
f g : ℕ → Ω → E
ℱ : Filtration ℕ m0
inst✝ : CompleteSpace E
hfint : ∀ (n : ℕ), Integrable (f n) μ
hgint : ∀ (n : ℕ), Integrable (g n) μ
n i : ℕ
hi : i ∈ Finset.range n
⊢ μ[f (i + 1) + g (i + 1) - (f i + g i) | ↑ℱ i] =ᵐ[μ] μ[f (i + 1) - f i + (g (i + 1) - g i) | ↑ℱ i]

Tactic:
abel_nf

Goal state after:
Ω : Type u_1
E : Type u_2
m0 : MeasurableSpace Ω
μ : Measure Ω
inst✝² : NormedAddCommGroup E
inst✝¹ : NormedSpace ℝ E
f g : ℕ → Ω → E
ℱ : Filtration ℕ m0
inst✝ : CompleteSpace E
hfint : ∀ (n : ℕ), Integrable (f n) μ
hgint : ∀ (n : ℕ), Integrable (g n) μ
n i : ℕ
hi : i ∈ Finset.range n
⊢ μ[f (i + 1) + (g (i + 1) + (-1 • f i + -1 • g i)) | ↑ℱ i] =ᵐ[μ]
    μ[f (i + 1) + (g (i + 1) + (-1 • f i + -1 • g i)) | ↑ℱ i]
Module: Mathlib.Probability.Process.Stopping

Goal state before:
pp: Ω : Type u_1
ι : Type u_3
m : MeasurableSpace Ω
inst✝³ : LinearOrder ι
f : Filtration ι m
τ : Ω → WithTop ι
inst✝² : TopologicalSpace ι
inst✝¹ : OrderTopology ι
inst✝ : FirstCountableTopology ι
hτ : IsStoppingTime f τ
i : ι
⊢ MeasurableSet {ω | τ ω = ↑i}

Tactic:
by
  have : {ω | τ ω = i} = {ω | τ ω ≤ i} ∩ {ω | τ ω ≥ i} := by
    ext1 ω; simp only [Set.mem_ofPred_eq, Set.mem_inter_iff, le_antisymm_iff]
  rw [this]
  exact (hτ.measurableSet_le i).inter (hτ.measurableSet_ge i)

Goal state after:
Module: Mathlib.Probability.Process.HittingTime

Goal state before:
pp: Ω : Type u_1
β : Type u_2
ι : Type u_3
inst✝ : ConditionallyCompleteLinearOrder ι
u : ι → Ω → β
s : Set β
n : ι
ω : Ω
m₁ m₂ : ι
h : m₁ ≤ m₂
j : ι
hj₁ : j ∈ Set.Icc n m₁
hj₂ : u j ω ∈ s
i : ι
hi : i ∈ Set.Icc n m₂ ∩ {i | u i ω ∈ s}
⊢ sInf (Set.Icc n m₁ ∩ {i | u i ω ∈ s}) ≤ i

Tactic:
by_cases hi' : i ≤ m₁

Goal state after:
case pos
Ω : Type u_1
β : Type u_2
ι : Type u_3
inst✝ : ConditionallyCompleteLinearOrder ι
u : ι → Ω → β
s : Set β
n : ι
ω : Ω
m₁ m₂ : ι
h : m₁ ≤ m₂
j : ι
hj₁ : j ∈ Set.Icc n m₁
hj₂ : u j ω ∈ s
i : ι
hi : i ∈ Set.Icc n m₂ ∩ {i | u i ω ∈ s}
hi' : i ≤ m₁
⊢ sInf (Set.Icc n m₁ ∩ {i | u i ω ∈ s}) ≤ i

case neg
Ω : Type u_1
β : Type u_2
ι : Type u_3
inst✝ : ConditionallyCompleteLinearOrder ι
u : ι → Ω → β
s : Set β
n : ι
ω : Ω
m₁ m₂ : ι
h : m₁ ≤ m₂
j : ι
hj₁ : j ∈ Set.Icc n m₁
hj₂ : u j ω ∈ s
i : ι
hi : i ∈ Set.Icc n m₂ ∩ {i | u i ω ∈ s}
hi' : ¬i ≤ m₁
⊢ sInf (Set.Icc n m₁ ∩ {i | u i ω ∈ s}) ≤ i
Module: Mathlib.Probability.Martingale.Upcrossing

Goal state before:
pp: case succ
Ω : Type u_1
a b : ℝ
f : ℕ → Ω → ℝ
N n : ℕ
ω : Ω
M : ℕ
hNM : N ≤ M
k : ℕ
ih :
  upperCrossingTime a b f M k ω = upperCrossingTime a b f N k ω ∧
    lowerCrossingTime a b f M k ω = lowerCrossingTime a b f N k ω
h : lowerCrossingTime a b f N (k + 1) ω < N
h' : upperCrossingTime a b f N (k + 1) ω < N
this : upperCrossingTime a b f M k.succ ω = upperCrossingTime a b f N k.succ ω
⊢ upperCrossingTime a b f M (k + 1) ω = upperCrossingTime a b f N (k + 1) ω ∧
    lowerCrossingTime a b f M (k + 1) ω = lowerCrossingTime a b f N (k + 1) ω

Tactic:
refine ⟨this, ?_⟩

Goal state after:
case succ
Ω : Type u_1
a b : ℝ
f : ℕ → Ω → ℝ
N n : ℕ
ω : Ω
M : ℕ
hNM : N ≤ M
k : ℕ
ih :
  upperCrossingTime a b f M k ω = upperCrossingTime a b f N k ω ∧
    lowerCrossingTime a b f M k ω = lowerCrossingTime a b f N k ω
h : lowerCrossingTime a b f N (k + 1) ω < N
h' : upperCrossingTime a b f N (k + 1) ω < N
this : upperCrossingTime a b f M k.succ ω = upperCrossingTime a b f N k.succ ω
⊢ lowerCrossingTime a b f M (k + 1) ω = lowerCrossingTime a b f N (k + 1) ω
Module: Mathlib.Probability.Process.HittingTime

Goal state before:
pp: Ω : Type u_1
β : Type u_2
ι : Type u_3
inst✝ : ConditionallyCompleteLinearOrder ι
u : ι → Ω → β
s : Set β
m n n' : ι
hnn' : n ≤ n'
ω : Ω
⊢ (if ∃ j ∈ Set.Icc n m, u j ω ∈ s then sInf (Set.Icc n m ∩ {i | u i ω ∈ s}) else m) ≤
    if ∃ j ∈ Set.Icc n' m, u j ω ∈ s then sInf (Set.Icc n' m ∩ {i | u i ω ∈ s}) else m

Tactic:
split_ifs with h_n h_n' h_n'

Goal state after:
case pos
Ω : Type u_1
β : Type u_2
ι : Type u_3
inst✝ : ConditionallyCompleteLinearOrder ι
u : ι → Ω → β
s : Set β
m n n' : ι
hnn' : n ≤ n'
ω : Ω
h_n : ∃ j ∈ Set.Icc n m, u j ω ∈ s
h_n' : ∃ j ∈ Set.Icc n' m, u j ω ∈ s
⊢ sInf (Set.Icc n m ∩ {i | u i ω ∈ s}) ≤ sInf (Set.Icc n' m ∩ {i | u i ω ∈ s})

case neg
Ω : Type u_1
β : Type u_2
ι : Type u_3
inst✝ : ConditionallyCompleteLinearOrder ι
u : ι → Ω → β
s : Set β
m n n' : ι
hnn' : n ≤ n'
ω : Ω
h_n : ∃ j ∈ Set.Icc n m, u j ω ∈ s
h_n' : ¬∃ j ∈ Set.Icc n' m, u j ω ∈ s
⊢ sInf (Set.Icc n m ∩ {i | u i ω ∈ s}) ≤ m

case pos
Ω : Type u_1
β : Type u_2
ι : Type u_3
inst✝ : ConditionallyCompleteLinearOrder ι
u : ι → Ω → β
s : Set β
m n n' : ι
hnn' : n ≤ n'
ω : Ω
h_n : ¬∃ j ∈ Set.Icc n m, u j ω ∈ s
h_n' : ∃ j ∈ Set.Icc n' m, u j ω ∈ s
⊢ m ≤ sInf (Set.Icc n' m ∩ {i | u i ω ∈ s})

case neg
Ω : Type u_1
β : Type u_2
ι : Type u_3
inst✝ : ConditionallyCompleteLinearOrder ι
u : ι → Ω → β
s : Set β
m n n' : ι
hnn' : n ≤ n'
ω : Ω
h_n : ¬∃ j ∈ Set.Icc n m, u j ω ∈ s
h_n' : ¬∃ j ∈ Set.Icc n' m, u j ω ∈ s
⊢ m ≤ m
Module: Mathlib.Probability.Process.HittingTime

Goal state before:
pp: case inl
Ω : Type u_1
β : Type u_2
ι : Type u_3
m : MeasurableSpace Ω
inst✝² : ConditionallyCompleteLinearOrder ι
inst✝¹ : WellFoundedLT ι
inst✝ : Countable ι
x✝ : MeasurableSpace β
f : Filtration ι m
u : ι → Ω → β
s : Set β
n n' : ι
hu : Adapted f u
hs : MeasurableSet s
i : ι
hi : n' ≤ i
⊢ MeasurableSet {ω | (fun ω ↦ ↑(hittingBtwn u s n n' ω)) ω ≤ ↑i}

pp: case inr
Ω : Type u_1
β : Type u_2
ι : Type u_3
m : MeasurableSpace Ω
inst✝² : ConditionallyCompleteLinearOrder ι
inst✝¹ : WellFoundedLT ι
inst✝ : Countable ι
x✝ : MeasurableSpace β
f : Filtration ι m
u : ι → Ω → β
s : Set β
n n' : ι
hu : Adapted f u
hs : MeasurableSet s
i : ι
hi : i < n'
⊢ MeasurableSet {ω | (fun ω ↦ ↑(hittingBtwn u s n n' ω)) ω ≤ ↑i}

Tactic:
· have h_le : ∀ ω, hittingBtwn u s n n' ω ≤ i := fun x => (hittingBtwn_le x).trans hi
    simp [h_le]

Goal state after:
case inr
Ω : Type u_1
β : Type u_2
ι : Type u_3
m : MeasurableSpace Ω
inst✝² : ConditionallyCompleteLinearOrder ι
inst✝¹ : WellFoundedLT ι
inst✝ : Countable ι
x✝ : MeasurableSpace β
f : Filtration ι m
u : ι → Ω → β
s : Set β
n n' : ι
hu : Adapted f u
hs : MeasurableSet s
i : ι
hi : i < n'
⊢ MeasurableSet {ω | (fun ω ↦ ↑(hittingBtwn u s n n' ω)) ω ≤ ↑i}
Module: Mathlib.Probability.Process.Stopping

Goal state before:
pp: Ω : Type u_1
ι : Type u_3
m : MeasurableSpace Ω
inst✝⁵ : Add ι
inst✝⁴ : LinearOrder ι
inst✝³ : CanonicallyOrderedAdd ι
inst✝² : Countable ι
inst✝¹ : TopologicalSpace ι
inst✝ : OrderTopology ι
f : Filtration ι m
τ : Ω → WithTop ι
hτ : IsStoppingTime f τ
i j : ι
ω : Ω
⊢ ω ∈ {ω | τ ω + ↑i ≤ ↑j} ↔ ω ∈ ⋃ k, {ω | τ ω = ↑↑k}

Tactic:
simp only [Set.mem_ofPred_eq, Set.mem_iUnion]

Goal state after:
Ω : Type u_1
ι : Type u_3
m : MeasurableSpace Ω
inst✝⁵ : Add ι
inst✝⁴ : LinearOrder ι
inst✝³ : CanonicallyOrderedAdd ι
inst✝² : Countable ι
inst✝¹ : TopologicalSpace ι
inst✝ : OrderTopology ι
f : Filtration ι m
τ : Ω → WithTop ι
hτ : IsStoppingTime f τ
i j : ι
ω : Ω
⊢ τ ω + ↑i ≤ ↑j ↔ ∃ i_1, τ ω = ↑↑i_1
Module: Mathlib.Probability.Martingale.Upcrossing

Goal state before:
pp: case succ
Ω : Type u_1
a b : ℝ
f : ℕ → Ω → ℝ
N n : ℕ
hab : a < b
hab' : 0 < b - a
hf : ∀ (ω : Ω) (i : ℕ), b - a ≤ (f i ω - a)⁺ ↔ b ≤ f i ω
hf' : ∀ (ω : Ω) (i : ℕ), (f i ω - a)⁺ ≤ 0 ↔ f i ω ≤ a
k : ℕ
ih :
  upperCrossingTime 0 (b - a) (fun n ω ↦ (f n ω - a)⁺) N k = upperCrossingTime a b f N k ∧
    lowerCrossingTime 0 (b - a) (fun n ω ↦ (f n ω - a)⁺) N k = lowerCrossingTime a b f N k
this : upperCrossingTime 0 (b - a) (fun n ω ↦ (f n ω - a)⁺) N (k + 1) = upperCrossingTime a b f N (k + 1)
⊢ upperCrossingTime 0 (b - a) (fun n ω ↦ (f n ω - a)⁺) N (k + 1) = upperCrossingTime a b f N (k + 1) ∧
    lowerCrossingTime 0 (b - a) (fun n ω ↦ (f n ω - a)⁺) N (k + 1) = lowerCrossingTime a b f N (k + 1)

Tactic:
refine ⟨this, ?_⟩

Goal state after:
case succ
Ω : Type u_1
a b : ℝ
f : ℕ → Ω → ℝ
N n : ℕ
hab : a < b
hab' : 0 < b - a
hf : ∀ (ω : Ω) (i : ℕ), b - a ≤ (f i ω - a)⁺ ↔ b ≤ f i ω
hf' : ∀ (ω : Ω) (i : ℕ), (f i ω - a)⁺ ≤ 0 ↔ f i ω ≤ a
k : ℕ
ih :
  upperCrossingTime 0 (b - a) (fun n ω ↦ (f n ω - a)⁺) N k = upperCrossingTime a b f N k ∧
    lowerCrossingTime 0 (b - a) (fun n ω ↦ (f n ω - a)⁺) N k = lowerCrossingTime a b f N k
this : upperCrossingTime 0 (b - a) (fun n ω ↦ (f n ω - a)⁺) N (k + 1) = upperCrossingTime a b f N (k + 1)
⊢ lowerCrossingTime 0 (b - a) (fun n ω ↦ (f n ω - a)⁺) N (k + 1) = lowerCrossingTime a b f N (k + 1)
Module: Mathlib.Probability.Moments.Basic

Goal state before:
pp: Ω : Type u_1
m : MeasurableSpace Ω
μ : Measure Ω
t : ℝ
inst✝ : IsFiniteMeasure μ
hμ : μ ≠ 0
c : ℝ
⊢ μ.real Set.univ ≠ 0

Tactic:
Ne,

Goal state after:
Ω : Type u_1
m : MeasurableSpace Ω
μ : Measure Ω
t : ℝ
inst✝ : IsFiniteMeasure μ
hμ : μ ≠ 0
c : ℝ
⊢ ¬μ.real Set.univ = 0
Module: Mathlib.Probability.Moments.IntegrableExpMul

Goal state before:
pp: case inr
Ω : Type u_1
m : MeasurableSpace Ω
X : Ω → ℝ
μ : Measure Ω
t₁ : ℝ
ht₁ : t₁ ∈ integrableExpSet X μ
t₂ : ℝ
ht₂ : t₂ ∈ integrableExpSet X μ
a b : ℝ
ha : 0 ≤ a
hb : 0 ≤ b
hab : a + b = 1
this :
  ∀ {Ω : Type u_1} {m : MeasurableSpace Ω} {X : Ω → ℝ} {μ : Measure Ω} ⦃t₁ : ℝ⦄,
    t₁ ∈ integrableExpSet X μ →
      ∀ ⦃t₂ : ℝ⦄,
        t₂ ∈ integrableExpSet X μ →
          ∀ ⦃a b : ℝ⦄, 0 ≤ a → 0 ≤ b → a + b = 1 → t₁ ≤ t₂ → a • t₁ + b • t₂ ∈ integrableExpSet X μ
h_le : t₂ < t₁
⊢ a • t₁ + b • t₂ ∈ integrableExpSet X μ

Tactic:
rw [add_comm] at hab ⊢
    exact this ht₂ ht₁ hb ha hab h_le.le

Goal state after:
Module: Mathlib.Probability.Moments.Basic

Goal state before:
pp: 𝕜 : Type u_1
E : Type u_2
F : Type u_3
inst✝¹³ : RCLike 𝕜
inst✝¹² : NormedAddCommGroup E
inst✝¹¹ : NormedAddCommGroup F
inst✝¹⁰ : NormedSpace 𝕜 E
inst✝⁹ : NormedSpace ℝ E
inst✝⁸ : NormedSpace 𝕜 F
inst✝⁷ : NormedSpace ℝ F
inst✝⁶ : CompleteSpace E
inst✝⁵ : CompleteSpace F
inst✝⁴ : MeasurableSpace E
μ : Measure E
inst✝³ : OpensMeasurableSpace E
inst✝² : MeasurableSpace F
inst✝¹ : BorelSpace F
inst✝ : SecondCountableTopology F
h : Integrable id μ
L : E →L[𝕜] F
⊢ ∫ (x : F), x ∂Measure.map (⇑L) μ = L (∫ (x : E), x ∂μ)

Tactic:
rw [integral_map (by fun_prop) (by fun_prop)]

Goal state after:
𝕜 : Type u_1
E : Type u_2
F : Type u_3
inst✝¹³ : RCLike 𝕜
inst✝¹² : NormedAddCommGroup E
inst✝¹¹ : NormedAddCommGroup F
inst✝¹⁰ : NormedSpace 𝕜 E
inst✝⁹ : NormedSpace ℝ E
inst✝⁸ : NormedSpace 𝕜 F
inst✝⁷ : NormedSpace ℝ F
inst✝⁶ : CompleteSpace E
inst✝⁵ : CompleteSpace F
inst✝⁴ : MeasurableSpace E
μ : Measure E
inst✝³ : OpensMeasurableSpace E
inst✝² : MeasurableSpace F
inst✝¹ : BorelSpace F
inst✝ : SecondCountableTopology F
h : Integrable id μ
L : E →L[𝕜] F
⊢ ∫ (x : E), L x ∂μ = L (∫ (x : E), x ∂μ)
Module: Mathlib.Probability.Moments.IntegrableExpMul

Goal state before:
pp: case refine_2
x t p : ℝ
hp : 0 ≤ p
ht : 0 < t
hp_zero : ¬p = 0
h_x_le : ∀ (c : ℝ), 0 < c → x ≤ c⁻¹ * rexp (c * x)
h_neg_x_le : ∀ (c : ℝ), 0 < c → -x ≤ c⁻¹ * rexp (-c * x)
c : ℝ
hc : 0 < c
⊢ x ≤ c⁻¹ * max (rexp (c * x)) (rexp (-c * x))

Tactic:
· refine (h_x_le c hc).trans ?_
      gcongr
      exact le_max_left _ _

Goal state after:
Module: Mathlib.Probability.Distributions.Gaussian.Real

Goal state before:
pp: μ : ℝ
v : ℝ≥0
x y : ℝ
⊢ (√(2 * π * ↑v))⁻¹ * rexp (-(x - y - μ) ^ 2 / (2 * ↑v)) = (√(2 * π * ↑v))⁻¹ * rexp (-(x - (μ + y)) ^ 2 / (2 * ↑v))

Tactic:
rw [sub_add_eq_sub_sub_swap]

Goal state after:
Module: Mathlib.Probability.Distributions.Gaussian.Real

Goal state before:
pp: μ : ℝ
v : ℝ≥0
hv : v ≠ 0
x : ℝ
⊢ 0 < gaussianPDF μ v x

Tactic:
rw [gaussianPDF, ENNReal.ofReal_pos]

Goal state after:
μ : ℝ
v : ℝ≥0
hv : v ≠ 0
x : ℝ
⊢ 0 < gaussianPDFReal μ v x
Module: Mathlib.Probability.Moments.IntegrableExpMul

Goal state before:
pp: l u v : ℝ
hv : v ∈ Set.Ioo l u
h_pos : 0 < min (v - l) (u - v)
⊢ v + min (v - l) (u - v) ≤ v + (u - v)

Tactic:
by gcongr; exact inf_le_right

Goal state after:
Module: Mathlib.Probability.Distributions.Gaussian.Basic

Goal state before:
pp: E : Type u_1
inst✝³ : TopologicalSpace E
inst✝² : AddCommMonoid E
inst✝¹ : Module ℝ E
mE : MeasurableSpace E
inst✝ : OpensMeasurableSpace E
μ : Measure E
h : ∀ (L : E →L[ℝ] ℝ), IsGaussian (Measure.map (⇑L) μ)
⊢ IsGaussian μ

Tactic:
refine ⟨fun L ↦ ?_⟩
  rw [(h L).eq_gaussianReal, integral_map, variance_map]
  · simp
  all_goals fun_prop

Goal state after:
Module: Mathlib.Probability.Distributions.Gaussian.Real

Goal state before:
pp: μ : ℝ
v : ℝ≥0
⊢ ∫ (ω : ℝ), (ω - μ) ^ 2 ∂gaussianReal μ v = ∫ (ω : ℝ), ω ^ 2 ∂Measure.map (fun x ↦ x - μ) (gaussianReal μ v)

Tactic:
rw [integral_map (by fun_prop) (by fun_prop)]

Goal state after:
Module: Mathlib.Probability.Distributions.Fernique

Goal state before:
pp: E : Type u_1
inst✝¹ : SeminormedAddCommGroup E
inst✝ : NormedSpace ℝ E
θ : ℝ
x y : E × E
⊢ (Real.cos θ • x.1 + Real.cos θ • y.1 + (Real.sin θ • x.2 + Real.sin θ • y.2),
      -(Real.sin θ • x.1) + -(Real.sin θ • y.1) + (Real.cos θ • x.2 + Real.cos θ • y.2)) =
    (Real.cos θ • x.1 + Real.sin θ • x.2 + (Real.cos θ • y.1 + Real.sin θ • y.2),
      -(Real.sin θ • x.1) + Real.cos θ • x.2 + (-(Real.sin θ • y.1) + Real.cos θ • y.2))

Tactic:
abel_nf

Goal state after:
Module: Mathlib.Probability.Distributions.Fernique

Goal state before:

Tactic:
μ {x | ‖x‖ ≤ a} * μ {x | b < ‖x‖}
  _ = (μ.prod μ) ({x | ‖x‖ ≤ a} ×ˢ {y | b < ‖y‖}) := by rw [Measure.prod_prod]
    -- This is the measure of two bands in the plane (draw a picture!)
  _ = (μ.prod μ) {p | ‖p.1‖ ≤ a ∧ b < ‖p.2‖} := rfl
  _ = ((μ.prod μ).map (ContinuousLinearMap.rotation (-(π / 4)))) {p | ‖p.1‖ ≤ a ∧ b < ‖p.2‖} := by
    -- We can rotate the bands since `μ.prod μ` is invariant under rotation
    rw [h]
  _ = (μ.prod μ) {p | ‖p.1 - p.2‖ / √2 ≤ a ∧ b < ‖p.1 + p.2‖ / √2} := by
    rw [Measure.map_apply (by fun_prop)]
    swap
    · refine MeasurableSet.inter ?_ ?_
      · change MeasurableSet {p : E × E | ‖p.1‖ ≤ a}
        exact measurableSet_le (by fun_prop) (by fun_prop)
      · change MeasurableSet {p : E × E | b < ‖p.2‖}
        exact measurableSet_lt (by fun_prop) (by fun_prop)
    congr 1
    simp only [Set.preimage_ofPred_eq, ContinuousLinearMap.rotation_apply, Real.cos_neg,
      Real.cos_pi_div_four, Real.sin_neg, Real.sin_pi_div_four, neg_smul, neg_neg]
    have h_twos : ‖2⁻¹ * √2‖ = (√2)⁻¹ := by
      simp only [norm_mul, norm_inv, Real.norm_ofNat, Real.norm_eq_abs]
      rw [abs_of_nonneg (by positivity)]
      nth_rw 1 [← Real.sq_sqrt (by simp : (0 : ℝ) ≤ 2)]
      rw [pow_two, mul_inv, mul_assoc, inv_mul_cancel₀ (by positivity), mul_one]
    congr! with p
    · rw [← sub_eq_add_neg, ← smul_sub, norm_smul, div_eq_inv_mul, div_eq_inv_mul, h_twos]
    · rw [← smul_add, norm_smul, div_eq_inv_mul, div_eq_inv_mul, h_twos]
  _ ≤ (μ.prod μ) {p | (b - a) / √2 < ‖p.1‖ ∧ (b - a) / √2 < ‖p.2‖} := by
    -- The rotated bands are contained in quadrants.
    refine measure_mono fun p ↦ ?_
    simp only [Set.mem_ofPred_eq, and_imp]
    intro hp1 hp2
    suffices (b - a) / √2 < min ‖p.1‖ ‖p.2‖ from lt_min_iff.mp this
    calc (b - a) / √2
    _ < (‖p.1 + p.2‖ - ‖p.1 - p.2‖) / 2 := by
      suffices b - a < ‖p.1 + p.2‖ / √2 - ‖p.1 - p.2‖ / √2 by
        calc (b - a) / √2 < (‖p.1 + p.2‖ / √2 - ‖p.1 - p.2‖ / √2) / √2 := by gcongr
        _ = (‖p.1 + p.2‖ - ‖p.1 - p.2‖) / 2 := by
          field_simp; rw [Real.sq_sqrt (by positivity)]; ring
      calc b - a < ‖p.1 + p.2‖ / √2 - a := by gcongr
      _ ≤ ‖p.1 + p.2‖ / √2 - ‖p.1 - p.2‖ / √2 := by gcongr
    _ ≤ min ‖p.1‖ ‖p.2‖ := by
      have := norm_add_sub_norm_sub_le_two_mul_min p.1 p.2
      linarith
  _ = (μ.prod μ) ({x | (b - a) / √2 < ‖x‖} ×ˢ {y | (b - a) / √2 < ‖y‖}) := rfl
  _ ≤ μ {x | (b - a) / √2 < ‖x‖} ^ 2 := by rw [Measure.prod_prod, pow_two]

Goal state after:
Module: Mathlib.Probability.Moments.CovarianceBilinDual

Goal state before:
pp: case neg.inr.inr
E : Type u_1
inst✝¹ : NormedAddCommGroup E
mE : MeasurableSpace E
μ : Measure E
inst✝ : NormedSpace ℝ E
c : E := ∫ (x : E), x ∂μ
this✝ : id = fun x ↦ x - c + c
hx : ¬c = 0
I : Integrable (fun x ↦ ‖x‖) μ
y : E
p : ℝ≥0
h_Lp : MemLp (fun x ↦ x - c) (↑p) μ
hp0 : ↑p ≠ 0
this : Integrable (fun x ↦ 2 ^ (↑p).toReal * ‖x - c‖ ^ (↑p).toReal) μ
⊢ ‖‖c‖ ^ (↑p).toReal‖ ≤
    ((fun x ↦ 2 * ‖c‖ ^ ((↑p).toReal - 1) * ‖x‖) + fun x ↦ 2 ^ (↑p).toReal * ‖x - c‖ ^ (↑p).toReal) y

Tactic:
simp only [ENNReal.coe_toReal, Real.norm_eq_abs, Pi.add_apply]

Goal state after:
case neg.inr.inr
E : Type u_1
inst✝¹ : NormedAddCommGroup E
mE : MeasurableSpace E
μ : Measure E
inst✝ : NormedSpace ℝ E
c : E := ∫ (x : E), x ∂μ
this✝ : id = fun x ↦ x - c + c
hx : ¬c = 0
I : Integrable (fun x ↦ ‖x‖) μ
y : E
p : ℝ≥0
h_Lp : MemLp (fun x ↦ x - c) (↑p) μ
hp0 : ↑p ≠ 0
this : Integrable (fun x ↦ 2 ^ (↑p).toReal * ‖x - c‖ ^ (↑p).toReal) μ
⊢ |‖c‖ ^ ↑p| ≤ 2 * ‖c‖ ^ (↑p - 1) * ‖y‖ + 2 ^ ↑p * ‖y - c‖ ^ ↑p
Module: Mathlib.Probability.Moments.CovarianceBilinDual

Goal state before:
pp: E : Type u_1
inst✝¹ : NormedAddCommGroup E
mE : MeasurableSpace E
μ : Measure E
inst✝ : NormedSpace ℝ E
c : E := ∫ (x : E), x ∂μ
this✝ : id = fun x ↦ x - c + c
hx : ¬c = 0
I : Integrable (fun x ↦ ‖x‖) μ
y : E
p : ℝ≥0
h_Lp : MemLp (fun x ↦ x - c) (↑p) μ
hp0 : ↑p ≠ 0
this : Integrable (fun x ↦ 2 ^ (↑p).toReal * ‖x - c‖ ^ (↑p).toReal) μ
h✝ : ‖y‖ ≤ ‖c‖ / 2
⊢ ‖c‖ = ‖y - (y - c)‖

Tactic:
abel_nf

Goal state after:
Module: Mathlib.Probability.Moments.CovarianceBilinDual

Goal state before:
pp: E : Type u_1
inst✝¹ : NormedAddCommGroup E
mE : MeasurableSpace E
μ : Measure E
inst✝ : NormedSpace ℝ E
c : E := ∫ (x : E), x ∂μ
this✝ : id = fun x ↦ x - c + c
hx : ¬c = 0
I : Integrable (fun x ↦ ‖x‖) μ
y : E
p : ℝ≥0
h_Lp : MemLp (fun x ↦ x - c) (↑p) μ
hp0 : ↑p ≠ 0
this : Integrable (fun x ↦ 2 ^ (↑p).toReal * ‖x - c‖ ^ (↑p).toReal) μ
h✝ : ‖c‖ / 2 ≤ ‖y‖
⊢ ‖c‖ ^ ↑p = ‖c‖ ^ (↑p - 1 + 1)

Tactic:
abel_nf

Goal state after:
Module: Mathlib.Probability.Distributions.Gaussian.Fernique

Goal state before:
pp: E : Type u_1
inst✝⁵ : NormedAddCommGroup E
inst✝⁴ : NormedSpace ℝ E
inst✝³ : MeasurableSpace E
inst✝² : BorelSpace E
μ : Measure E
inst✝¹ : IsGaussian μ
inst✝ : SecondCountableTopology E
L : StrongDual ℝ E
⊢ ∫ (x : E), L x ∂μ + ∫ (y : E), L y ∂Measure.map (⇑(ContinuousLinearEquiv.neg ℝ)) μ = 0

Tactic:
rw [integral_map (by fun_prop) (by fun_prop)]

Goal state after:
E : Type u_1
inst✝⁵ : NormedAddCommGroup E
inst✝⁴ : NormedSpace ℝ E
inst✝³ : MeasurableSpace E
inst✝² : BorelSpace E
μ : Measure E
inst✝¹ : IsGaussian μ
inst✝ : SecondCountableTopology E
L : StrongDual ℝ E
⊢ ∫ (x : E), L x ∂μ + ∫ (x : E), L ((ContinuousLinearEquiv.neg ℝ) x) ∂μ = 0
Module: Mathlib.Probability.Moments.CovarianceBilinDual

Goal state before:
pp: E : Type u_1
inst✝² : NormedAddCommGroup E
mE : MeasurableSpace E
μ : Measure E
inst✝¹ : NormedSpace ℝ E
inst✝ : BorelSpace E
h : ¬MemLp (fun x ↦ x - ∫ (y : E), y ∂μ) 2 μ
L₁ L₂ : StrongDual ℝ E
⊢ ((covarianceBilinDual μ) L₁) L₂ = 0

Tactic:
by
  rw [covarianceBilinDual, uncenteredCovarianceBilinDual_of_not_memLp]
  rw [(measurableEmbedding_subRight _).memLp_map_measure_iff]
  exact h

Goal state after:
Module: Mathlib.Probability.Distributions.Gaussian.CharFun

Goal state before:
pp: E : Type u_1
inst✝⁷ : NormedAddCommGroup E
inst✝⁶ : SecondCountableTopology E
inst✝⁵ : CompleteSpace E
inst✝⁴ : MeasurableSpace E
inst✝³ : BorelSpace E
μ : Measure E
inst✝² : NormedSpace ℝ E
ν : Measure E
inst✝¹ : IsGaussian μ
inst✝ : IsGaussian ν
hm : ∫ (x : E), id x ∂μ = ∫ (x : E), id x ∂ν
hv : covarianceBilinDual μ = covarianceBilinDual ν
L : StrongDual ℝ E
⊢ charFunDual μ L = charFunDual ν L

Tactic:
simp_rw [IsGaussian.charFunDual_eq', hm, hv]

Goal state after:
Module: Mathlib.Probability.Distributions.Gaussian.Multivariate

Goal state before:
pp: ι : Type u_1
inst✝ : Fintype ι
t : EuclideanSpace ℝ ι
⊢ charFun (Measure.map (toLp 2) (Measure.pi fun x ↦ gaussianReal 0 1)) t = charFun (stdGaussian (EuclideanSpace ℝ ι)) t

Tactic:
charFun_stdGaussian,

Goal state after:
ι : Type u_1
inst✝ : Fintype ι
t : EuclideanSpace ℝ ι
⊢ charFun (Measure.map (toLp 2) (Measure.pi fun x ↦ gaussianReal 0 1)) t = cexp (-↑‖t‖ ^ 2 / 2)
Module: Mathlib.Probability.BrownianMotion.GaussianProjectiveFamily

Goal state before:
pp: I : Finset ℝ≥0
f : (↥I → ℝ) → ℝ
⊢ Var[f; projectiveFamily I] = Var[f ∘ ofLp; multivariateGaussian 0 (covMatrix I)]

Tactic:
rw [projectiveFamily, variance_map_equiv]

Goal state after:
I : Finset ℝ≥0
f : (↥I → ℝ) → ℝ
⊢ Var[f ∘ ⇑(MeasurableEquiv.toLp 2 (↥I → ℝ)).symm; multivariateGaussian 0 (covMatrix I)] =
    Var[f ∘ ofLp; multivariateGaussian 0 (covMatrix I)]
Module: Mathlib.Probability.Distributions.Fernique

Goal state before:
pp: case neg
E : Type u_1
inst✝⁵ : SeminormedAddCommGroup E
inst✝⁴ : NormedSpace ℝ E
inst✝³ : SecondCountableTopology E
inst✝² : MeasurableSpace E
inst✝¹ : BorelSpace E
μ : Measure E
a : ℝ
inst✝ : IsProbabilityMeasure μ
h_rot : Measure.map (⇑(ContinuousLinearMap.rotation (-(π / 4)))) (μ.prod μ) = μ.prod μ
ha_pos : 0 < a
c' : ℝ≥0∞
hc' : c' ≤ μ {x | ‖x‖ ≤ a}
hc'_gt : 2⁻¹ < c'
t : ℕ → ℝ := normThreshold a
c : ℝ≥0∞ := μ {x | ‖x‖ ≤ a}
C : ℝ := logRatio c' * a⁻¹ ^ 2
hc'_le : c' ≤ 1
ht_int_zero :
  ∫⁻ (x : E) in closedBall 0 a, ENNReal.ofReal (rexp (C * ‖x‖ ^ 2)) ∂μ ≤
    μ {x | ‖x‖ ≤ a} * ENNReal.ofReal (rexp (logRatio c'))
ha : ¬μ {x | ‖x‖ ≤ a} = 1
ha_lt : μ {x | ‖x‖ ≤ a} < 1
hc'_lt : c' < 1
h_iUnion : Set.univ = closedBall 0 a ∪ ⋃ n, closedBall 0 (t (n + 1)) \ closedBall 0 (t n)
this :
  ∫⁻ (x : E) in closedBall 0 (t 0) ∪ ⋃ n, closedBall 0 (t (n + 1)) \ closedBall 0 (t n),
      ENNReal.ofReal (rexp (C * ‖x‖ ^ 2)) ∂μ ≤
    ∫⁻ (x : E) in closedBall 0 (t 0), ENNReal.ofReal (rexp (C * ‖x‖ ^ 2)) ∂μ +
      ∑' (i : ℕ), ∫⁻ (x : E) in closedBall 0 (t (i + 1)) \ closedBall 0 (t i), ENNReal.ofReal (rexp (C * ‖x‖ ^ 2)) ∂μ
⊢ ∫⁻ (x : E) in closedBall 0 a ∪ ⋃ n, closedBall 0 (t (n + 1)) \ closedBall 0 (t n),
      ENNReal.ofReal (rexp (C * ‖x‖ ^ 2)) ∂μ ≤
    c *
      (ENNReal.ofReal (rexp (logRatio c')) +
        ∑' (n : ℕ), ENNReal.ofReal (rexp (-2⁻¹ * Real.log (c' / (1 - c')).toReal * 2 ^ n)))

Tactic:
refine this.trans ?_

Goal state after:
case neg
E : Type u_1
inst✝⁵ : SeminormedAddCommGroup E
inst✝⁴ : NormedSpace ℝ E
inst✝³ : SecondCountableTopology E
inst✝² : MeasurableSpace E
inst✝¹ : BorelSpace E
μ : Measure E
a : ℝ
inst✝ : IsProbabilityMeasure μ
h_rot : Measure.map (⇑(ContinuousLinearMap.rotation (-(π / 4)))) (μ.prod μ) = μ.prod μ
ha_pos : 0 < a
c' : ℝ≥0∞
hc' : c' ≤ μ {x | ‖x‖ ≤ a}
hc'_gt : 2⁻¹ < c'
t : ℕ → ℝ := normThreshold a
c : ℝ≥0∞ := μ {x | ‖x‖ ≤ a}
C : ℝ := logRatio c' * a⁻¹ ^ 2
hc'_le : c' ≤ 1
ht_int_zero :
  ∫⁻ (x : E) in closedBall 0 a, ENNReal.ofReal (rexp (C * ‖x‖ ^ 2)) ∂μ ≤
    μ {x | ‖x‖ ≤ a} * ENNReal.ofReal (rexp (logRatio c'))
ha : ¬μ {x | ‖x‖ ≤ a} = 1
ha_lt : μ {x | ‖x‖ ≤ a} < 1
hc'_lt : c' < 1
h_iUnion : Set.univ = closedBall 0 a ∪ ⋃ n, closedBall 0 (t (n + 1)) \ closedBall 0 (t n)
this :
  ∫⁻ (x : E) in closedBall 0 (t 0) ∪ ⋃ n, closedBall 0 (t (n + 1)) \ closedBall 0 (t n),
      ENNReal.ofReal (rexp (C * ‖x‖ ^ 2)) ∂μ ≤
    ∫⁻ (x : E) in closedBall 0 (t 0), ENNReal.ofReal (rexp (C * ‖x‖ ^ 2)) ∂μ +
      ∑' (i : ℕ), ∫⁻ (x : E) in closedBall 0 (t (i + 1)) \ closedBall 0 (t i), ENNReal.ofReal (rexp (C * ‖x‖ ^ 2)) ∂μ
⊢ ∫⁻ (x : E) in closedBall 0 (t 0), ENNReal.ofReal (rexp (C * ‖x‖ ^ 2)) ∂μ +
      ∑' (i : ℕ), ∫⁻ (x : E) in closedBall 0 (t (i + 1)) \ closedBall 0 (t i), ENNReal.ofReal (rexp (C * ‖x‖ ^ 2)) ∂μ ≤
    c *
      (ENNReal.ofReal (rexp (logRatio c')) +
        ∑' (n : ℕ), ENNReal.ofReal (rexp (-2⁻¹ * Real.log (c' / (1 - c')).toReal * 2 ^ n)))