Documentation

PFR.Fibring

The fibring identity #

The proof of the fibring identity, which is a key component of the proof of PFR.

Main statement #

theorem rdist_of_indep_eq_sum_fibre {H : Type u_1} [AddCommGroup H] [Countable H] [hH : MeasurableSpace H] [MeasurableSingletonClass H] {H' : Type u_2} [AddCommGroup H'] [Countable H'] [hH' : MeasurableSpace H'] [MeasurableSingletonClass H'] (π : H →+ H') {Ω : Type u_3} [ : MeasurableSpace Ω] {μ : MeasureTheory.Measure Ω} [MeasureTheory.IsProbabilityMeasure μ] {Z_1 Z_2 : ΩH} (h : ProbabilityTheory.IndepFun Z_1 Z_2 μ) (h1 : Measurable Z_1) (h2 : Measurable Z_2) [FiniteRange Z_1] [FiniteRange Z_2] :
d[Z_1 ; μ # Z_2 ; μ] = d[π Z_1 ; μ # π Z_2 ; μ] + d[Z_1 | π Z_1 ; μ # Z_2 | π Z_2 ; μ] + I[Z_1 - Z_2 : π Z_1, π Z_2|π (Z_1 - Z_2);μ]

If Z1,Z2 are independent, then d[Z1;Z2] is equal to d[π(Z1);π(Z2)]+d[Z1|π(Z1);Z2|π(Z2)] plus I(Z1Z2:(π(Z1),π(Z2))|π(Z1Z2)).

theorem rdist_le_sum_fibre {H : Type u_1} [AddCommGroup H] [Countable H] [hH : MeasurableSpace H] [MeasurableSingletonClass H] {H' : Type u_2} [AddCommGroup H'] [Countable H'] [hH' : MeasurableSpace H'] [MeasurableSingletonClass H'] (π : H →+ H') {Ω : Type u_3} {Ω' : Type u_4} [ : MeasurableSpace Ω] [mΩ' : MeasurableSpace Ω'] {μ : MeasureTheory.Measure Ω} {μ' : MeasureTheory.Measure Ω'} [MeasureTheory.IsProbabilityMeasure μ] [MeasureTheory.IsProbabilityMeasure μ'] {Z_1 : ΩH} {Z_2 : Ω'H} (h1 : Measurable Z_1) (h2 : Measurable Z_2) [FiniteRange Z_1] [FiniteRange Z_2] :
d[π Z_1 ; μ # π Z_2 ; μ'] + d[Z_1 | π Z_1 ; μ # Z_2 | π Z_2 ; μ'] d[Z_1 ; μ # Z_2 ; μ']
theorem rdist_of_hom_le {H : Type u_1} [AddCommGroup H] [Countable H] [hH : MeasurableSpace H] [MeasurableSingletonClass H] {H' : Type u_2} [AddCommGroup H'] [Countable H'] [hH' : MeasurableSpace H'] [MeasurableSingletonClass H'] (π : H →+ H') {Ω : Type u_3} {Ω' : Type u_4} [ : MeasurableSpace Ω] [mΩ' : MeasurableSpace Ω'] {μ : MeasureTheory.Measure Ω} {μ' : MeasureTheory.Measure Ω'} [MeasureTheory.IsProbabilityMeasure μ] [MeasureTheory.IsProbabilityMeasure μ'] {Z_1 : ΩH} {Z_2 : Ω'H} (h1 : Measurable Z_1) (h2 : Measurable Z_2) [FiniteRange Z_1] [FiniteRange Z_2] :
d[π Z_1 ; μ # π Z_2 ; μ'] d[Z_1 ; μ # Z_2 ; μ']

[d[X;Y]\geq d[\pi(X);\pi(Y)].]

theorem sum_of_rdist_eq_step_condRuzsaDist {G : Type u_1} [AddCommGroup G] [Fintype G] [hG : MeasurableSpace G] [MeasurableSingletonClass G] {Ω : Type u_2} [ : MeasurableSpace Ω] {μ : MeasureTheory.Measure Ω} [MeasureTheory.IsProbabilityMeasure μ] {Y : Fin 4ΩG} (h_indep : ProbabilityTheory.iIndepFun Y μ) (h_meas : ∀ (i : Fin 4), Measurable (Y i)) :
d[Y 0, Y 2 | Y 0 - Y 2 ; μ # Y 1, Y 3 | Y 1 - Y 3 ; μ] = d[Y 0 | Y 0 - Y 2 ; μ # Y 1 | Y 1 - Y 3 ; μ]

The conditional Ruzsa Distance step of sum_of_rdist_eq

theorem sum_of_rdist_eq_step_condMutualInfo {G : Type u_1} [AddCommGroup G] [Fintype G] [hG : MeasurableSpace G] [MeasurableSingletonClass G] {Ω : Type u_2} [ : MeasurableSpace Ω] {μ : MeasureTheory.Measure Ω} [MeasureTheory.IsProbabilityMeasure μ] {Y : Fin 4ΩG} (h_meas : ∀ (i : Fin 4), Measurable (Y i)) :
I[Y 0 - Y 1, Y 2 - Y 3 : Y 0 - Y 2, Y 1 - Y 3|Y 0 - Y 1 - (Y 2 - Y 3);μ] = I[Y 0 - Y 1 : Y 1 - Y 3|Y 0 - Y 1 - Y 2 + Y 3;μ]

The conditional mutual information step of sum_of_rdist_eq

theorem sum_of_rdist_eq {G : Type u_1} [AddCommGroup G] [Fintype G] [hG : MeasurableSpace G] [MeasurableSingletonClass G] {Ω : Type u_2} [ : MeasurableSpace Ω] {μ : MeasureTheory.Measure Ω} [MeasureTheory.IsProbabilityMeasure μ] (Y : Fin 4ΩG) (h_indep : ProbabilityTheory.iIndepFun Y μ) (h_meas : ∀ (i : Fin 4), Measurable (Y i)) :
d[Y 0 ; μ # Y 1 ; μ] + d[Y 2 ; μ # Y 3 ; μ] = d[Y 0 - Y 2 ; μ # Y 1 - Y 3 ; μ] + d[Y 0 | Y 0 - Y 2 ; μ # Y 1 | Y 1 - Y 3 ; μ] + I[Y 0 - Y 1 : Y 1 - Y 3|Y 0 - Y 1 - Y 2 + Y 3;μ]

Let Y1,Y2,Y3 and Y4 be independent G-valued random variables. Then d[Y1Y3;Y2Y4]+d[Y1|Y1Y3;Y2|Y2Y4] +I[Y1Y2:Y2Y4|Y1Y2Y3+Y4]=d[Y1;Y2]+d[Y3;Y4].

theorem sum_of_rdist_eq_char_2 {G : Type u_1} [AddCommGroup G] [Fintype G] [hG : MeasurableSpace G] [MeasurableSingletonClass G] {Ω : Type u_2} [ : MeasurableSpace Ω] {μ : MeasureTheory.Measure Ω} [MeasureTheory.IsProbabilityMeasure μ] [Module (ZMod 2) G] (Y : Fin 4ΩG) (h_indep : ProbabilityTheory.iIndepFun Y μ) (h_meas : ∀ (i : Fin 4), Measurable (Y i)) :
d[Y 0 ; μ # Y 1 ; μ] + d[Y 2 ; μ # Y 3 ; μ] = d[Y 0 + Y 2 ; μ # Y 1 + Y 3 ; μ] + d[Y 0 | Y 0 + Y 2 ; μ # Y 1 | Y 1 + Y 3 ; μ] + I[Y 0 + Y 1 : Y 1 + Y 3|Y 0 + Y 1 + Y 2 + Y 3;μ]

Let Y1,Y2,Y3 and Y4 be independent G-valued random variables. Then d[Y1+Y3;Y2+Y4]+d[Y1|Y1+Y3;Y2|Y2+Y4] +I[Y1+Y2:Y2+Y4|Y1+Y2+Y3+Y4]=d[Y1;Y2]+d[Y3;Y4].

theorem sum_of_rdist_eq_char_2' {G : Type u_1} [AddCommGroup G] [Fintype G] [hG : MeasurableSpace G] [MeasurableSingletonClass G] {Ω : Type u_2} [ : MeasurableSpace Ω] {μ : MeasureTheory.Measure Ω} [MeasureTheory.IsProbabilityMeasure μ] [Module (ZMod 2) G] (X Y X' Y' : ΩG) (h_indep : ProbabilityTheory.iIndepFun ![X, Y, X', Y'] μ) (hX : Measurable X) (hY : Measurable Y) (hX' : Measurable X') (hY' : Measurable Y') :
d[X ; μ # Y ; μ] + d[X' ; μ # Y' ; μ] = d[X + X' ; μ # Y + Y' ; μ] + d[X | X + X' ; μ # Y | Y + Y' ; μ] + I[X + Y : Y + Y'|X + Y + X' + Y';μ]