Second estimate

The second estimate on tau-minimizers.

Assumptions:

• $X_1, X_2$ are tau-minimizers
• $X_1, X_2, \tilde X_1, \tilde X_2$ be independent random variables, with $X_1,\tilde X_1$ copies of $X_1$ and $X_2,\tilde X_2$ copies of $X_2$.
• $d[X_1;X_2] = k$
• $I_1 := I_1 [X_1+X_2 : \tilde X_1 + X_2 | X_1+X_2+\tilde X_1+\tilde X_2]$
• $I_2 := I[X_1+X_2 : X_1 + \tilde X_1 | X_1+X_2+\tilde X_1+\tilde X_2]$

Main results

• second_estimate : $$ I_2 \leq 2 \eta k + \frac{2 \eta (2 \eta k - I_1)}{1 - \eta}.$$

theorem rdist_of_sums_ge' {G : Type u_1} [AddCommGroup G] [Finite G] [hG : MeasurableSpace G] [MeasurableSingletonClass G] [Module (ZMod 2) G] [MeasurableAdd₂ G] {Ω₀₁ : Type u_2} {Ω₀₂ : Type u_3} [MeasureTheory.MeasureSpace Ω₀₁] [MeasureTheory.MeasureSpace Ω₀₂] [MeasureTheory.IsProbabilityMeasure MeasureTheory.volume] [MeasureTheory.IsProbabilityMeasure MeasureTheory.volume] (p : refPackage Ω₀₁ Ω₀₂ G) {Ω : Type u_4} [MeasureTheory.MeasureSpace Ω] [MeasureTheory.IsProbabilityMeasure MeasureTheory.volume] (X₁ X₂ X₁' X₂' : Ω → G) (hX₁ : Measurable X₁) (hX₂ : Measurable X₂) (hX₁' : Measurable X₁') (hX₂' : Measurable X₂') (h₁ : ProbabilityTheory.IdentDistrib X₁ X₁' MeasureTheory.volume MeasureTheory.volume) (h₂ : ProbabilityTheory.IdentDistrib X₂ X₂' MeasureTheory.volume MeasureTheory.volume) (h_indep : ProbabilityTheory.iIndepFun ![X₁, X₂, X₁', X₂'] MeasureTheory.volume) (h_min : TauMinimizes p X₁ X₂) : d[X₁ + X₁' # X₂ + X₂'] ≥ d[X₁ # X₂] - p.η * (d[X₁ # X₁] + d[X₂ # X₂]) / 2

$$ d[X_1+\tilde X_1; X_2+\tilde X_2] \geq k - \frac{\eta}{2} ( d[X_1; X_1] + d[X_2;X_2] ).$$

theorem second_estimate_aux {G : Type u_1} [AddCommGroup G] [Finite G] [hG : MeasurableSpace G] [MeasurableSingletonClass G] [Module (ZMod 2) G] [MeasurableAdd₂ G] {Ω₀₁ : Type u_2} {Ω₀₂ : Type u_3} [MeasureTheory.MeasureSpace Ω₀₁] [MeasureTheory.MeasureSpace Ω₀₂] [MeasureTheory.IsProbabilityMeasure MeasureTheory.volume] [MeasureTheory.IsProbabilityMeasure MeasureTheory.volume] (p : refPackage Ω₀₁ Ω₀₂ G) {Ω : Type u_4} [MeasureTheory.MeasureSpace Ω] [MeasureTheory.IsProbabilityMeasure MeasureTheory.volume] (X₁ X₂ X₁' X₂' : Ω → G) (hX₁ : Measurable X₁) (hX₂ : Measurable X₂) (hX₁' : Measurable X₁') (hX₂' : Measurable X₂') (h₁ : ProbabilityTheory.IdentDistrib X₁ X₁' MeasureTheory.volume MeasureTheory.volume) (h₂ : ProbabilityTheory.IdentDistrib X₂ X₂' MeasureTheory.volume MeasureTheory.volume) (h_indep : ProbabilityTheory.iIndepFun ![X₁, X₂, X₁', X₂'] MeasureTheory.volume) (h_min : TauMinimizes p X₁ X₂) : d[X₁ # X₁] + d[X₂ # X₂] ≤ 2 * (d[X₁ # X₂] + (2 * p.η * d[X₁ # X₂] - I[X₁ + X₂ : X₁' + X₂|X₁ + X₂ + X₁' + X₂']) / (1 - p.η))

theorem second_estimate {G : Type u_1} [AddCommGroup G] [Finite G] [hG : MeasurableSpace G] [MeasurableSingletonClass G] [Module (ZMod 2) G] [MeasurableAdd₂ G] {Ω₀₁ : Type u_2} {Ω₀₂ : Type u_3} [MeasureTheory.MeasureSpace Ω₀₁] [MeasureTheory.MeasureSpace Ω₀₂] [MeasureTheory.IsProbabilityMeasure MeasureTheory.volume] [MeasureTheory.IsProbabilityMeasure MeasureTheory.volume] (p : refPackage Ω₀₁ Ω₀₂ G) {Ω : Type u_4} [MeasureTheory.MeasureSpace Ω] [MeasureTheory.IsProbabilityMeasure MeasureTheory.volume] (X₁ X₂ X₁' X₂' : Ω → G) (hX₁ : Measurable X₁) (hX₂ : Measurable X₂) (hX₁' : Measurable X₁') (hX₂' : Measurable X₂') (h₁ : ProbabilityTheory.IdentDistrib X₁ X₁' MeasureTheory.volume MeasureTheory.volume) (h₂ : ProbabilityTheory.IdentDistrib X₂ X₂' MeasureTheory.volume MeasureTheory.volume) (h_indep : ProbabilityTheory.iIndepFun ![X₁, X₂, X₁', X₂'] MeasureTheory.volume) (h_min : TauMinimizes p X₁ X₂) : I[X₁ + X₂ : X₁' + X₁|X₁ + X₂ + X₁' + X₂'] ≤ 2 * p.η * d[X₁ # X₂] + 2 * p.η * (2 * p.η * d[X₁ # X₂] - I[X₁ + X₂ : X₁' + X₂|X₁ + X₂ + X₁' + X₂']) / (1 - p.η)

$$ I_2 \leq 2 \eta k + \frac{2 \eta (2 \eta k - I_1)}{1 - \eta}.$$