InformationTheory

InformationTheory.Shannon.EPI.Stam.SupplyTwoTime

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theorem

InformationTheory.Shannon.EPIStamSupplyTwoTime.density_int_mass

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{Ω : Type u_1} [MeasurableSpace Ω] {P : MeasureTheory.Measure Ω} [MeasureTheory.IsProbabilityMeasure P] (W : Ω) (p : ) (hW : Measurable W) (hp_nn : ∀ (x : ), 0 p x) (hp_meas : Measurable p) (hp_law : MeasureTheory.Measure.map W P = MeasureTheory.volume.withDensity fun (x : ) => ENNReal.ofReal (p x)) :

Density facts from a withDensity law (probability-density normalization): if P.map W = volume.withDensity (ofReal ∘ p) with P a probability measure and p ≥ 0 measurable, then p is volume-integrable with mass 1. @audit:ok

Used by
    theorem

    InformationTheory.Shannon.EPIStamSupplyTwoTime.indepSum_density_ae

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    {Ω : Type u_1} [MeasurableSpace Ω] {P : MeasureTheory.Measure Ω} [MeasureTheory.IsProbabilityMeasure P] (X Y : Ω) (hX : Measurable X) (hY : Measurable Y) (hXY : ProbabilityTheory.IndepFun X Y P) (pX pY pXY : ) (hpX_nn : ∀ (x : ), 0 pX x) (hpX_meas : Measurable pX) (hpY_nn : ∀ (x : ), 0 pY x) (hpY_meas : Measurable pY) (hpX_law : MeasureTheory.Measure.map X P = MeasureTheory.volume.withDensity fun (x : ) => ENNReal.ofReal (pX x)) (hpY_law : MeasureTheory.Measure.map Y P = MeasureTheory.volume.withDensity fun (x : ) => ENNReal.ofReal (pY x)) (hpXY_law : MeasureTheory.Measure.map (fun (ω : Ω) => X ω + Y ω) P = MeasureTheory.volume.withDensity fun (x : ) => ENNReal.ofReal (pXY x)) (hpXY_nn : ∀ (x : ), 0 pXY x) (hpXY_meas : Measurable pXY) (_hpX_int : MeasureTheory.Integrable pX MeasureTheory.volume) (_hpY_int : MeasureTheory.Integrable pY MeasureTheory.volume) (hpXY_lmass : ∫⁻ (x : ), ENNReal.ofReal (pXY x) ) (hpX_lmass : ∫⁻ (x : ), ENNReal.ofReal (pX x) = 1) (hpY_lmass : ∫⁻ (x : ), ENNReal.ofReal (pY x) = 1) :

    The independent-sum input identity, the seam of the argument: for X ⊥ Y with Lebesgue densities pX, pY and X+Y with Lebesgue density pXY (all from probability-measure withDensity laws), the sum density equals the convolution of the addend densities a.e.: pXY =ᵐ[volume] convDensityAdd pX pY.

    Both pXY and convDensityAdd pX pY are densities of P.map (X+Y) = (P.map X) ∗ (P.map Y) (independence), and withDensity densities are a.e.-unique. This is an a.e. identity at the un-smoothed input level; the consumed density_t is pinned pointwise to the smooth convolution. @audit:ok

    Used by
      theorem

      InformationTheory.Shannon.EPIStamSupplyTwoTime.convDensityAdd_gaussian_asym_convDensityAdd_pos

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      (pX pY : ) {s t : } (hs : 0 < s) (ht : 0 < t) (hpX_nn : ∀ (x : ), 0 pX x) (hpX_meas : Measurable pX) (hpX_int : MeasureTheory.Integrable pX MeasureTheory.volume) (hpX_mass : 0 < (x : ), pX x) (hpY_nn : ∀ (x : ), 0 pY x) (hpY_meas : Measurable pY) (hpY_int : MeasureTheory.Integrable pY MeasureTheory.volume) (hpY_mass : 0 < (x : ), pY x) (z : ) :
      Used by
        theorem

        InformationTheory.Shannon.EPIStamSupplyTwoTime.convDensityAdd_gaussian_asym_integrable_deriv_mul

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        Used by
          theorem

          InformationTheory.Shannon.EPIStamSupplyTwoTime.convDensityAdd_gaussian_asym_integrable_mul_deriv

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          Used by
            theorem

            InformationTheory.Shannon.EPIStamSupplyTwoTime.convDensityAdd_gaussian_asym_condDensityX_integrable

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            Used by
              theorem

              InformationTheory.Shannon.EPIStamSupplyTwoTime.convDensityAdd_gaussian_asym_integrable_scoreWeight_mul_condDensityX

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              Used by
                theorem

                InformationTheory.Shannon.EPIStamSupplyTwoTime.convDensityAdd_gaussian_asym_integrable_scoreWeight_sq_mul_condDensityX

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                (pX pY : ) {s t : } (hs : 0 < s) (ht : 0 < t) (hpX_nn : ∀ (x : ), 0 pX x) (hpX_meas : Measurable pX) (hpX_int : MeasureTheory.Integrable pX MeasureTheory.volume) (hpX_mass : 0 < (x : ), pX x) (hpX_norm : (x : ), pX x = 1) (hpY_nn : ∀ (x : ), 0 pY x) (hpY_meas : Measurable pY) (hpY_int : MeasureTheory.Integrable pY MeasureTheory.volume) (hpY_mass : 0 < (x : ), pY x) (hpY_norm : (x : ), pY x = 1) (lam z : ) :
                Used by
                  theorem

                  InformationTheory.Shannon.EPIStamSupplyTwoTime.convDensityAdd_gaussian_asym_integrable_inner_scoreWeight_sq

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                  Used by
                    theorem

                    InformationTheory.Shannon.EPIStamSupplyTwoTime.convDensityAdd_gaussian_asym_fisher_integrand_integrable

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                    Used by
                      theorem

                      InformationTheory.Shannon.EPIStamSupplyTwoTime.convDensityAdd_gaussian_asym_integrable_prod_logDeriv_sq_mul

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                      Used by
                        theorem

                        InformationTheory.Shannon.EPIStamSupplyTwoTime.convDensityAdd_gaussian_asym_integrable_prod_logDeriv_sq_shift_mul

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                        Used by
                          theorem

                          InformationTheory.Shannon.EPIStamSupplyTwoTime.convDensityAdd_gaussian_asym_integrable_prod_deriv_mul

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                          (pX pY : ) {s t : } (hs : 0 < s) (ht : 0 < t) (hpX_nn : ∀ (x : ), 0 pX x) (hpX_meas : Measurable pX) (hpX_int : MeasureTheory.Integrable pX MeasureTheory.volume) (hpX_mass : 0 < (x : ), pX x) (hpY_nn : ∀ (x : ), 0 pY x) (hpY_meas : Measurable pY) (hpY_int : MeasureTheory.Integrable pY MeasureTheory.volume) (hpY_mass : 0 < (x : ), pY x) :
                          Used by
                            theorem

                            InformationTheory.Shannon.EPIStamSupplyTwoTime.isBlachmanConvReady_convDensityAdd_gaussian_asym

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                            (pX pY : ) {s t : } (hs : 0 < s) (ht : 0 < t) (hpX_nn : ∀ (x : ), 0 pX x) (hpX_meas : Measurable pX) (hpX_int : MeasureTheory.Integrable pX MeasureTheory.volume) (hpX_mass : 0 < (x : ), pX x) (hpX_norm : (x : ), pX x = 1) (hpY_nn : ∀ (x : ), 0 pY x) (hpY_meas : Measurable pY) (hpY_int : MeasureTheory.Integrable pY MeasureTheory.volume) (hpY_mass : 0 < (x : ), pY x) (hpY_norm : (x : ), pY x = 1) :

                            The asymmetric IsBlachmanConvReady producer (independent times σ ≠ τ): IsBlachmanConvReady (convDensityAdd pX g_σ) (convDensityAdd pY g_τ). Faithful generalization of EPIBlachmanGeneralDensity.isBlachmanConvReady_convDensityAdd_gaussian (which hardcodes the same t for both arms) — every field's construction uses only the public per-arm conv-Gaussian lemmas (convDensityAdd_gaussian_integrable / _bdd / _deriv_bdd / convDensityAdd_fisher_integrand_integrable / convDensityAdd_pos_of_pos_cont / isRegularDensityV2_convDensityAdd_gaussian), each at its own arm's time, so the same-t restriction was incidental. The only structural change is int_fisherZ: the conv-of-conv conv(pX∗g_σ)(pY∗g_τ) is identified with conv(pX∗pY) g_{σ+τ} via the asymmetric interchange bridge convDensityAdd_convGaussian_interchange_asym (variance σ+τ, not 2t).

                            All hypotheses are regularity preconditions; the conclusion (19-field integrability / boundedness / positivity bundle) is derived from them. @audit:ok

                            Used by
                              theorem

                              InformationTheory.Shannon.EPIStamSupplyTwoTime.twoTime_stam_supply

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                              {Ω : Type u_1} [MeasurableSpace Ω] (P : MeasureTheory.Measure Ω) [MeasureTheory.IsProbabilityMeasure P] (X Y Z_X Z_Y Z : Ω) (hX : Measurable X) (hY : Measurable Y) (hZX : Measurable Z_X) (hZY : Measurable Z_Y) (_hZ : Measurable Z) (_hXZX : ProbabilityTheory.IndepFun X Z_X P) (_hYZY : ProbabilityTheory.IndepFun Y Z_Y P) (hXY : ProbabilityTheory.IndepFun X Y P) (hpair_indep : ProbabilityTheory.IndepFun (fun (ω : Ω) => (X ω, Z_X ω)) (fun (ω : Ω) => (Y ω, Z_Y ω)) P) (_hZX_law : MeasureTheory.Measure.map Z_X P = ProbabilityTheory.gaussianReal 0 1) (_hZY_law : MeasureTheory.Measure.map Z_Y P = ProbabilityTheory.gaussianReal 0 1) (_hZ_law : MeasureTheory.Measure.map Z P = ProbabilityTheory.gaussianReal 0 1) (_hX_ac : (MeasureTheory.Measure.map X P).AbsolutelyContinuous MeasureTheory.volume) (_hY_ac : (MeasureTheory.Measure.map Y P).AbsolutelyContinuous MeasureTheory.volume) (_hmomX : MeasureTheory.Integrable (fun (ω : Ω) => X ω ^ 2) P) (_hmomY : MeasureTheory.Integrable (fun (ω : Ω) => Y ω ^ 2) P) (h_reg_X : StamEPIBridge.IsDeBruijnRegularityHyp X Z_X P) (h_reg_Y : StamEPIBridge.IsDeBruijnRegularityHyp Y Z_Y P) (h_reg_sum : StamEPIBridge.IsDeBruijnRegularityHyp (fun (ω : Ω) => X ω + Y ω) Z P) (σ τ : ) ( : 0 < σ) ( : 0 < τ) :

                              The two-time harmonic-Stam supply producer.

                              For X Y Z_X Z_Y Z : Ω → ℝ (all unit noises, sum perturbed by separate Z), independent appropriately, with Lebesgue densities and finite second moments, and de Bruijn regularity h_reg_X/h_reg_Y/h_reg_sum, the h_stam_supply clause of entropyPower_add_ge_case1_of_regular_twotime holds: at every matched pair σ, τ > 0, the three smoothed Fisher informations are positive and 1/J_S ≥ 1/J_X + 1/J_Y with J_S the single-noise sum heat flow at σ + τ.

                              The conv-pin seam indepSum_density_ae (pXY =ᵐ convDensityAdd pX pY) is proved via IndepFun.map_add_eq_map_conv_map + conv_withDensity_eq_lconvolution

                              • withDensity a.e.-uniqueness + the lconvolution-Bochner a.e. bridge (Tonelli finiteness + a.e.-z ofReal_integral_eq_lintegral_ofReal).

                              @audit:ok. The honesty of the signature rests on: (1) Core genuinely produced, not assumed: the inverse-Stam 1/J_S ≥ 1/J_X+1/J_Y is CONSTRUCTED by isStamInequalityHyp_of_indepFun P A B (a regularity-only construction via stamCauchySchwarzOptimal_of_indepFun, @audit:ok) then APPLIED at density_t. The three IsDeBruijnRegularityHyp inputs are consumed only as regularity (.pX/.pX_law/.pX_nn/.pX_meas density witnesses + .density_t_eq pointwise pins), never as a bundled inequality core. No := h circularity, no :True, no degenerate exploitation, no *Hypothesis-core bundling, no name laundering. (2) a.e.→pointwise wash: the object IsStamInequalityHyp consumes is the POINTWISE-pinned smooth density_t (density_t_eq pins to the explicit smooth convDensityAdd pX g_t, not an a.e. rnDeriv class); the a.e. seam sits only at the un-smoothed input (pXY =ᵐ convDensityAdd pX pY) and is washed through convDensityAdd · g by integral_congr_ae. A skeptic cannot pick a bad pointwise representative. (3) indepSum_density_ae sound + non-vacuous (see its tag). (4) isBlachmanConvReady_convDensityAdd_gaussian_asym = pure 19-field regularity (see its tag). (5) Unused hyps (hZ/hXZX/hYZY/hZX_law/hZY_law/hZ_law/hX_ac/hY_ac/hmomX/hmomY) are OVER-hypothesized-harmless: kept to match the uniform shape EPIDensityForm passes to entropyPower_add_ge_case1_of_regular_twotime; the de Bruijn regularity hyps already carry the needed density data (no gap masked, proof closes without them = NOT under-hypothesized). hpair_indep is a genuine necessary precondition (pairwise indep insufficient for A=X+√σ·Z_X ⊥ B=Y+√τ·Z_Y; derived via .comp). sorryAx-free.

                              Used by