ActualPositionL2Averaging: mathematical reading route

Mathematical statement

Let E be any finite-dimensional real inner-product Borel space, including dimension zero. Let V:E→ℝ be C², α,β≥0 and η∈ℝ with α>0, α≤β, α‖v‖²≤D²V(x)[v,v]≤β‖v‖² for every x,v∈E, η>0 and βη≤1. The following literal constructions are made for all y,r∈E and initial phases z₀∈E×E; the existential process witness below is global in these parameters. Put c=y−η∇V(r), Φ_t(x,p)=(c+cos(t)(x−c)+√η sin(t)p, −sin(t)(x−c)/√η+cos(t)p), g_r(x)=∇V(x)−∇V(r), S_r(x,p)=(x,p−2〈p,g_r(x)〉g_r(x)/‖g_r(x)‖²), λ_r(x,p)=√η max{0,〈p,g_r(x)〉}, Λ_z(t)=∫₀ᵗλ_r(Φ_s(z))ds and τ_z(e)=inf{t≥0:Λ_z(t)≥e}∈[0,∞], with inf empty=∞. Total real division makes S_r the identity at g_r(x)=0. The record space is D=([0,∞)×(E×E))⊕{stopped}, with Borel sum structure. Define next(e,stopped)=stopped; for a live record (T,z), next(e,(T,z))=stopped if τ_z(e)=∞, and otherwise next(e,(T,z))=(T+τ_z(e),S_rΦ_(τ_z(e))(z)). In the Lean definition untopD0 is used only in this non-top branch. Define R₀(e)=live(0,z₀) and R_(j+1)(e)=next(e_j,R_j(e)). Let Ω=ℝ^ℕ with its product Borel structure and P=⊗_(k≥0)Exp(1). Let ε(w)_k=max{w_k,0}; this is an ambient coordinate extension on a P-null nonpositive-clock set, not new source dynamics for negative clocks. Write T_j(w)=a for a live record R_j(ε(w))=live(a,z), and T_j(w)=∞ for a stopped record. Define I_n(T)={T_n≤T<T_(n+1)}, and the total selector N(T,w)=min{n:w∈I_n(T)} when such an n exists, and 0 otherwise. For n≥0 let Hist_n=D^(Fin(n+1)) and H_n(w)_j=R_j(ε(w)). Write readTime(live(a,z))=a and readTime(stopped)=0. The abstract guard A_n(T) consists of histories all of whose records are live, whose read times are strictly increasing and whose positive-index read times are strictly below T; it does not constrain record0 itself. Actual H_n starts at live(0,z₀). For h∈Hist_n set d_n(T,h)=max{T−readTime(h_n),0}. Define survival(live(a,z),u,e) to mean u<τ_z(max{e,0}); on stopped it is false. Define W(live(a,z),u)=exp(−Λ_z(u)); on stopped W=0. Put C_n(T)={w:H_n(w)∈A_n(T), survival(R_n(ε(w)),d_n(T,H_n(w)),w_n)}. For a fixed finite T≥0 let Path_T be all functions from [0,T] into E×E, with its coordinate-product sigma algebra. On every history, including unrealizable ones, define Ψ_n(T,h)(s) by starting at z₀ and visiting j=0,…,n in increasing order: a live record (a,z) with a≤s replaces the current value by Φ_(s−a)(z), and an ineligible live or stopped record leaves it unchanged. All elapsed times in this total definition use nonnegative subtraction. Define Δ_n(T)={t∈ℝ^n:0<t₁<⋯<t_n<T}, and let m_n be the comap of product Lebesgue measure to this subtype, without normalization. For t∈Δ_n(T), put s₀=0,s_i=t_i, z₀ equal to the prescribed initial phase and z_i=S_rΦ_(s_i−s_(i−1))(z_(i−1)). Set K_n(t)_j=live(s_j,z_j), Γ_n(T,t)=Ψ_n(T,K_n(t)), q_n(t)=ofReal(∏_(i=1)^n λ_r(Φ_(s_i−s_(i−1))(z_(i−1)))exp[−Λ_(z_(i−1))(s_i−s_(i−1))]), and ρ_n(T,t)=q_n(t)W(K_n(t)_n,d_n(T,K_n(t))). The literal toNNReal conversions agree with these nonnegative simplex times. There exists one actual phase representative Z(y,r,z₀,t,w), jointly Borel in all deterministic parameters, finite time and raw input, with the following properties. On every raw covering interval T_n(w)≤s<T_(n+1)(w), if R_n(ε(w))=live(a,z), then Z(s,w)=Φ_(s−a)(z). If no interval covers s, Z(s,w)=z₀. For each fixed parameter tuple, Z(0,w)=z₀ almost surely. Put R(x,p)=(x,-p), V_y(x)=V(x)+||x-y||^2/(2 eta), and nu_y=(volume_E.tilted(-V_y)) times stdGaussian(E), in position/momentum order. Here tilted(-V_y) has density ofReal(exp(-V_y(x))/integral exp(-V_y) dx), and stdGaussian is the centered identity-covariance Gaussian. Normalizability is a consequence, not a premise. Write H=E times E, pi_y=volume_E.tilted(-V_y), gamma=stdGaussian(E), so nu_y=pi_y times gamma. For the same single global actual Z described above, every y,r in E and every finite T≥0, define op_T G(z)=integral G(Z(y,r,z,T,w)) dP(w), a real Bochner integral, and endpoint_T(z,w)=Z(y,r,z,T,w). Then endpoint_T is measurable and its pushforward of nu_y times P is exactly nu_y. For every pair F,G:H→R of Borel measurable functions and finite real bounds C_F,C_G≥0 with |F(z)|≤C_F and |G(z)|≤C_G for all z, both z→F(z)*op_T G(z) and z→G(R(z))*op_T(F composed R)(z) are integrable against nu_y, and their real integrals are equal. Thus integral F(z)*op_T G(z) dnu_y(z) = integral G(R(z))*op_T(F composed R)(z) dnu_y(z). All these conclusions use the same Z, existentially chosen before all centers, references, horizons and observables. Products are phase first, clock input second. No process, kernel, finite mass, signed integrability, momentum symmetry or normalizability is a supplied premise. Dimension zero, T=0, vanishing test bounds, zero bounce rates, infinite waits and raw exceptional fallback remain included. Almost-sure initialization stays parameterwise; no uniform all-parameter null set or pointwise reversed path at jumps is asserted. For every Borel G:H→R, the total real clock expectation (y,r,z,T)→integral G(Z(y,r,z,T,w)) dP(w) is jointly Borel. If C is a finite nonnegative real number and |G(z)|≤C for all z, then for every y,r,z,T the clock section is P-integrable and the absolute value of this expectation is at most C. For every y,r in E there exists a family A indexed by finite nonnegative T, where A_T:L2(nu_y;R)→L2(nu_y;R) is a continuous real linear operator, A_0 is the identity and ||A_T||≤1 for every T. For every real function G with MemLp G 2 nu_y (almost-everywhere strong measurability and finite L2 seminorm), the section w→G(Z(y,r,z,T,w)) is P-integrable for nu_y-almost every z. The literal expectation op_T G belongs to L2(nu_y;R), and A_T[G]=[op_T G]. Thus integral |op_T G|^2 dnu_y ≤ integral |G|^2 dnu_y. Brackets denote equality classes modulo nu_y-almost-everywhere equality; no pointwise identification of arbitrary L2 representatives is asserted. The operator, section integrability and output L2 membership are conclusions, not supplied premises. These operators use the same single global Z as all inherited path, initialization, invariance and bounded-duality conclusions. The bound1 is exact and independent of dimension, center, reference and horizon. The joint Borel assertion concerns Borel input G; arbitrary MemLp representatives receive the stated almost-everywhere conclusions. In addition, for each y,r the same operator family A has the following property. The literal phase reflection R(x,p)=(x,-p) preserves nu_y. Its canonical pullback J_y on real L2(nu_y) is the linear isometry defined by composition with R; for every L2 class f, (J_y f)(z)=f(R(z)) for nu_y-almost every z, and J_y(J_y f)=f. For every finite nonnegative T, the Hilbert adjoint of that same A_T satisfies A_T*=J_y A_T J_y as an equality of continuous real linear operators. Equivalently its pairing obeys <f,A_T g≥<J_y g,A_T(J_y f)> for all real L2 classes f,g. The pullback and its preservation/involution are proved conclusions; no supplied symmetry, operator relation, integrability or density hypothesis is added. The flip depends only on the displayed R and nu_y; the proof witness hR under y,r does not introduce reference or time dependence into J_y. The identity includes T=0 and rank zero. All representative equalities retain their stated almost-everywhere sense, with no common null set over all parameters or representatives. For the same y,r, write pi_y=volume.tilted(x → -Vy(y,x)), gamma=stdGaussian E and nu_y=pi_y times gamma. The projection fst preserves nu_y to pi_y. Define B:L2(pi_y;R)→L2(nu_y;R) to be its canonical linear isometric pullback, so (Bf)(x,p)=f(x) nu_y-almost everywhere, and define M=B*, the continuous real Hilbert adjoint. Then ||B||≤1, ||M||≤1 and M B=I. For every raw real G with MemLp G 2 nu_y, the Gaussian section p→G(x,p) is integrable for pi_y-almost every x. Its literal Gaussian mean gbar(x)=integral G(x,p) dgamma(p) belongs to L2(pi_y;R), and M[G]=[gbar]. This identification holds for arbitrary MemLp representatives, without an extra Borel or section-integrability hypothesis. Moreover J(Bf)=Bf for every position L2 class f, and M J=M. Define K_T=M A_T B for every finite nonnegative T. Then K_0=I, K_T*=K_T and ||K_T||≤1. For each raw real f with MemLp f 2 pi_y, define kTf(x)=integral_p (integral_w f((Z(y,r,(x,p),T,w)).position) dP(w)) dgamma(p). For pi_y-almost every x and gamma-almost every p the inner clock section is P-integrable. For pi_y-almost every x its clock mean is Gaussian-integrable as a function of p. The literal kTf belongs to L2(pi_y;R), and K_T[f]=[kTf]. The Gaussian outer / clock inner order is part of the statement; it is not interchanged. All AE statements are parameterwise in y,r,T and the chosen representative. All six original analytic assumptions and the same single global Z, phase family A and canonical J are retained. Probability/finiteness, integrability, L2 membership, averaging, flip absorption and operator identities are internal proof obligations or conclusions. The result includes rank zero and T=0, with exact bound1 and the probability Gaussian averaging convention. It closes the fixed-reference real-L2 averaging/selfadjoint-contraction portion of Proposition A.1(iii). Markov positivity and constant preservation, strong continuity, restart/semigroup, identification with a separately existential kernel, independent-reference averaging at the half-turn, complex-L2 extension, hypocoercivity, implementation errors, actual expected costs, actual-input composition and whole-paper results remain outside this bounded theorem.

theorem actual_position_l2_averaging
    {E : Type*} [NormedAddCommGroup E] [InnerProductSpace ℝ E]
    [FiniteDimensional ℝ E] [MeasurableSpace E] [BorelSpace E]
    {V : E → ℝ} {α β : ℝ≥0} {η : ℝ}
    (hα : 0 < (α : ℝ)) (hαβ : α ≤ β) (hV : ContDiff ℝ 2 V)
    (hH : ∀ x v : E,
      (α : ℝ) * ‖v‖ ^ 2 ≤ (fderiv ℝ (fderiv ℝ V) x v) v ∧
      (fderiv ℝ (fderiv ℝ V) x v) v ≤ (β : ℝ) * ‖v‖ ^ 2)
    (hη : 0 < η) (hβη : (β : ℝ) * η ≤ 1) : actual_position_l2_statement hα hαβ hV hH hη hβη

private def actual_position_l2_statement
    {E : Type*} [NormedAddCommGroup E] [InnerProductSpace ℝ E]
    [FiniteDimensional ℝ E] [MeasurableSpace E] [BorelSpace E]
    {V : E → ℝ} {α β : ℝ≥0} {η : ℝ}
    (hα : 0 < (α : ℝ)) (hαβ : α ≤ β) (hV : ContDiff ℝ 2 V)
    (hH : ∀ x v : E,
      (α : ℝ) * ‖v‖ ^ 2 ≤ (fderiv ℝ (fderiv ℝ V) x v) v ∧
      (fderiv ℝ (fderiv ℝ V) x v) v ≤ (β : ℝ) * ‖v‖ ^ 2)
    (hη : 0 < η) (hβη : (β : ℝ) * η ≤ 1) : Prop := by
  classical
  exact
    let c : E → E → E := fun y xRef => y - η • gradient V xRef
    let Φ : E → E → ℝ → (E × E) → (E × E) := fun y xRef t z =>
      (c y xRef + Real.cos t • (z.1 - c y xRef) +
          (Real.sqrt η * Real.sin t) • z.2,
       (-Real.sin t / Real.sqrt η) • (z.1 - c y xRef) + Real.cos t • z.2)
    let S : E → (E × E) → (E × E) := fun xRef z =>
      (z.1, z.2 - (2 * inner ℝ z.2 (gradient V z.1 - gradient V xRef) /
        ‖gradient V z.1 - gradient V xRef‖ ^ 2) • (gradient V z.1 - gradient V xRef))
    let rate : E → (E × E) → ℝ := fun xRef z =>
      Real.sqrt η * max 0 (inner ℝ z.2 (gradient V z.1 - gradient V xRef))
    let Λ : E → E → (E × E) → ℝ≥0 → ℝ := fun y xRef z t =>
      ∫ s in (0 : ℝ)..(t : ℝ), rate xRef (Φ y xRef s z)
    let τ : E → E → (E × E) → ℝ≥0 → WithTop ℝ≥0 := fun y xRef z e =>
      MeasureTheory.hittingAfter
        (fun t : ℝ≥0 => fun a : (E × E) × (E × E) × ℝ≥0 =>
          Λ a.1.1 a.1.2 a.2.1 t - (a.2.2 : ℝ))
        (Set.Ici (0 : ℝ)) 0 ((y, xRef), z, e)
    let next : E → E → ℝ≥0 → ((ℝ≥0 × (E × E)) ⊕ Unit) →
        ((ℝ≥0 × (E × E)) ⊕ Unit) := fun y xRef e r =>
      match r with
      | Sum.inr _ => Sum.inr ()
      | Sum.inl a =>
        if τ y xRef a.2 e = ⊤ then Sum.inr () else
          Sum.inl (a.1 + (τ y xRef a.2 e).untopD 0,
            S xRef (Φ y xRef (((τ y xRef a.2 e).untopD 0 : ℝ≥0) : ℝ) a.2))
    let record : E → E → (E × E) → (ℕ → ℝ≥0) → ℕ →
        ((ℝ≥0 × (E × E)) ⊕ Unit) := fun y xRef z₀ e n =>
      Nat.rec (Sum.inl (0, z₀)) (fun k r => next y xRef (e k) r) n
    let P : Measure (ℕ → ℝ) := Measure.infinitePi (fun _ : ℕ => expMeasure (1 : ℝ))
    let ε : (ℕ → ℝ) → ℕ → ℝ≥0 := fun w k => Real.toNNReal (w k)
    let history : E → E → (E × E) → (n : ℕ) → (ℕ → ℝ) →
        (Fin (n + 1) → ((ℝ≥0 × (E × E)) ⊕ Unit)) :=
      fun y xRef z₀ n w j => record y xRef z₀ (ε w) j.val
    let Rec := (ℝ≥0 × (E × E)) ⊕ Unit
    let Hist : ℕ → Type _ := fun n => Fin (n + 1) → Rec
    let readTime : Rec → ℝ := fun r => match r with
      | Sum.inl q => (q.1 : ℝ)
      | Sum.inr _ => 0
    let Δ : (n : ℕ) → ℝ≥0 → Set (Fin n → ℝ) := fun n T =>
      {t | StrictMono (Fin.cons (0 : ℝ) t) ∧ ∀ i, t i < (T : ℝ)}
    let Prefix : (n : ℕ) → ℝ≥0 → Type := fun n T => {t : Fin n → ℝ // t ∈ Δ n T}
    let m : (n : ℕ) → (T : ℝ≥0) → Measure (Prefix n T) := fun n T =>
      Measure.comap (fun t : Prefix n T => t.val) (volume : Measure (Fin n → ℝ))
    let zAt : E → E → (E × E) → (n : ℕ) → (T : ℝ≥0) →
        Prefix n T → Fin (n + 1) → (E × E) := fun y xRef z₀ n T t =>
      Fin.induction z₀ (fun i z =>
        S xRef (Φ y xRef (t.val i - (Fin.cons (0 : ℝ) (t.val : Fin n → ℝ) : Fin (n + 1) → ℝ) i.castSucc) z))
    let K : E → E → (E × E) → (n : ℕ) → (T : ℝ≥0) →
        Prefix n T → Hist n := fun y xRef z₀ n T t j =>
      Sum.inl (Real.toNNReal ((Fin.cons (0 : ℝ) (t.val : Fin n → ℝ) : Fin (n + 1) → ℝ) j), zAt y xRef z₀ n T t j)
    let qReal : E → E → (E × E) → (n : ℕ) → (T : ℝ≥0) →
        Prefix n T → ℝ := fun y xRef z₀ n T t =>
      ∏ i : Fin n,
        rate xRef (Φ y xRef (t.val i - (Fin.cons (0 : ℝ) (t.val : Fin n → ℝ) : Fin (n + 1) → ℝ) i.castSucc)
          (zAt y xRef z₀ n T t i.castSucc)) *
        Real.exp (-Λ y xRef (zAt y xRef z₀ n T t i.castSucc)
          (Real.toNNReal (t.val i - (Fin.cons (0 : ℝ) (t.val : Fin n → ℝ) : Fin (n + 1) → ℝ) i.castSucc)))
    let q : E → E → (E × E) → (n : ℕ) → (T : ℝ≥0) →
        Prefix n T → ℝ≥0∞ := fun y xRef z₀ n T t =>
      ENNReal.ofReal (qReal y xRef z₀ n T t)
    let A : (n : ℕ) → ℝ≥0 → Set (Hist n) := fun n T =>
      {h | (∀ j, ∃ a : ℝ≥0 × (E × E), h j = Sum.inl a) ∧
        StrictMono (fun j => readTime (h j)) ∧
        ∀ i : Fin n, readTime (h i.succ) < (T : ℝ)}
    let eventTime : E → E → (E × E) → (ℕ → ℝ) → ℕ → WithTop ℝ≥0 :=
      fun y xRef z₀ w j => (record y xRef z₀ (ε w) j).elim
        (fun a => (a.1 : WithTop ℝ≥0)) (fun _ => ⊤)
    let I : E → E → (E × E) → ℝ≥0 → ℕ → Set (ℕ → ℝ) :=
      fun y xRef z₀ T n => {w | eventTime y xRef z₀ w n ≤ (T : WithTop ℝ≥0) ∧
        (T : WithTop ℝ≥0) < eventTime y xRef z₀ w (n + 1)}
    let N : E → E → (E × E) → ℝ≥0 → (ℕ → ℝ) → ℕ := fun y xRef z₀ T w =>
      if h : ∃ n, w ∈ I y xRef z₀ T n then Nat.find h else 0
    let liveTime : Rec → ℝ≥0 := fun r => r.elim Prod.fst (fun _ => 0)
    let d : (n : ℕ) → ℝ≥0 → Hist n → ℝ≥0 :=
      fun n T h => T - liveTime (h ⟨n, Nat.lt_succ_self n⟩)
    let survival : E → E → Rec → ℝ≥0 → ℝ → Prop :=
      fun y xRef r u e => r.elim
        (fun a => (u : WithTop ℝ≥0) < τ y xRef a.2 (Real.toNNReal e)) (fun _ => False)
    let weight : E → E → Rec → ℝ≥0 → ℝ≥0∞ :=
      fun y xRef r u => r.elim
        (fun a => ENNReal.ofReal (Real.exp (-Λ y xRef a.2 u))) (fun _ => 0)
    let C : E → E → (E × E) → (n : ℕ) → ℝ≥0 → Set (ℕ → ℝ) :=
      fun y xRef z₀ n T => {w | history y xRef z₀ n w ∈ A n T ∧
        survival y xRef (record y xRef z₀ (ε w) n) (d n T (history y xRef z₀ n w)) (w n)}
    let Path : ℝ≥0 → Type _ := fun T => {s : ℝ≥0 // s ≤ T} → E × E
    let Ψ : E → E → (E × E) → (n : ℕ) → (T : ℝ≥0) → Hist n → Path T :=
      fun y xRef z₀ n T h s =>
        Fin.foldl (n + 1) (fun z j => (h j).elim
          (fun a => if a.1 ≤ s.val then Φ y xRef ((s.val - a.1 : ℝ≥0) : ℝ) a.2 else z)
          (fun _ => z)) z₀
    let Γ : E → E → (E × E) → (n : ℕ) → (T : ℝ≥0) → Prefix n T → Path T :=
      fun y xRef z₀ n T t => Ψ y xRef z₀ n T (K y xRef z₀ n T t)
    let ρ : E → E → (E × E) → (n : ℕ) → (T : ℝ≥0) → Prefix n T → ℝ≥0∞ :=
      fun y xRef z₀ n T t => q y xRef z₀ n T t *
        weight y xRef ((K y xRef z₀ n T t) ⟨n, Nat.lt_succ_self n⟩)
          (d n T (K y xRef z₀ n T t))
    let R : E × E → E × E := fun z => (z.1, -z.2)
    let Vy : E → E → ℝ := fun y x => V x + ‖x - y‖ ^ 2 / (2 * η)
    let nu : E → Measure (E × E) := fun y =>
      ((volume : Measure E).tilted (fun x => -Vy y x)).prod
        (ProbabilityTheory.stdGaussian E)
    ∃ Z : E → E → (E × E) → ℝ≥0 → (ℕ → ℝ) → (E × E),
      Measurable (fun a : ((E × E) × (E × E)) × ℝ≥0 × (ℕ → ℝ) =>
        Z a.1.1.1 a.1.1.2 a.1.2 a.2.1 a.2.2) ∧
      (∀ y xRef : E, ∀ z₀ : E × E, ∀ w : ℕ → ℝ, ∀ s : ℝ≥0,
        ∀ n : ℕ, ∀ a : ℝ≥0 × (E × E), w ∈ I y xRef z₀ s n →
          record y xRef z₀ (ε w) n = Sum.inl a →
          Z y xRef z₀ s w = Φ y xRef ((s - a.1 : ℝ≥0) : ℝ) a.2) ∧
      (∀ y xRef : E, ∀ z₀ : E × E, ∀ w : ℕ → ℝ, ∀ s : ℝ≥0,
        (¬ ∃ n, w ∈ I y xRef z₀ s n) → Z y xRef z₀ s w = z₀) ∧
      (∀ y xRef : E, ∀ z₀ : E × E, ∀ᵐ w ∂P, Z y xRef z₀ 0 w = z₀) ∧
      (∀ y xRef : E, ∀ T : ℝ≥0,
        let op : ((E × E) → ℝ) → (E × E) → ℝ :=
          fun G z => ∫ w, G (Z y xRef z T w) ∂P
        let endpoint : (E × E) × (ℕ → ℝ) → E × E :=
          fun a => Z y xRef a.1 T a.2
        MeasurePreserving endpoint ((nu y).prod P) (nu y) ∧
        ∀ F G : (E × E) → ℝ, ∀ C_F C_G : ℝ,
          Measurable F → Measurable G → 0 ≤ C_F → 0 ≤ C_G →
          (∀ z, |F z| ≤ C_F) → (∀ z, |G z| ≤ C_G) →
          Integrable (fun z => F z * op G z) (nu y) ∧
          Integrable (fun z => G (R z) * op (fun a => F (R a)) z) (nu y) ∧
          (∫ z, F z * op G z ∂nu y) =
            ∫ z, G (R z) * op (fun a => F (R a)) z ∂nu y) ∧
      (∀ G : (E × E) → ℝ, Measurable G →
        Measurable (fun a : ((E × E) × (E × E)) × ℝ≥0 =>
          ∫ w, G (Z a.1.1.1 a.1.1.2 a.1.2 a.2 w) ∂P) ∧
        ∀ C : ℝ, 0 ≤ C → (∀ z, |G z| ≤ C) →
          ∀ y xRef : E, ∀ z : E × E, ∀ T : ℝ≥0,
            Integrable (fun w => G (Z y xRef z T w)) P ∧
            |∫ w, G (Z y xRef z T w) ∂P| ≤ C) ∧
      (∀ y xRef : E,
        ∃ A : ℝ≥0 → (Lp ℝ 2 (nu y) →L[ℝ] Lp ℝ 2 (nu y)),
          A 0 = ContinuousLinearMap.id ℝ (Lp ℝ 2 (nu y)) ∧
          (∀ T : ℝ≥0, ‖A T‖ ≤ 1 ∧
            ∀ G : (E × E) → ℝ, ∀ hG : MemLp G 2 (nu y),
              let opG : (E × E) → ℝ := fun z => ∫ w, G (Z y xRef z T w) ∂P
              (∀ᵐ z ∂nu y, Integrable (fun w => G (Z y xRef z T w)) P) ∧
              (∃ hOp : MemLp opG 2 (nu y), A T (hG.toLp G) = hOp.toLp opG) ∧
              (∫ z, |opG z| ^ 2 ∂nu y) ≤ ∫ z, |G z| ^ 2 ∂nu y) ∧
          ∃ hR : MeasurePreserving R (nu y) (nu y),
            let J : Lp ℝ 2 (nu y) →ₗᵢ[ℝ] Lp ℝ 2 (nu y) :=
              Lp.compMeasurePreservingₗᵢ ℝ R hR
            (∀ f : Lp ℝ 2 (nu y),
              (J f : (E × E) → ℝ) =ᵐ[nu y] fun z => f (R z)) ∧
            (∀ f : Lp ℝ 2 (nu y), J (J f) = f) ∧
            (∀ T : ℝ≥0, (A T).adjoint =
              J.toContinuousLinearMap.comp ((A T).comp J.toContinuousLinearMap)) ∧
            let mu : Measure E := (volume : Measure E).tilted (fun x => -Vy y x)
            ∃ hfst : MeasurePreserving Prod.fst (nu y) mu,
              let B : Lp ℝ 2 mu →ₗᵢ[ℝ] Lp ℝ 2 (nu y) :=
                Lp.compMeasurePreservingₗᵢ ℝ Prod.fst hfst
              let M : Lp ℝ 2 (nu y) →L[ℝ] Lp ℝ 2 mu := B.toContinuousLinearMap.adjoint
              (∀ f : Lp ℝ 2 mu, (B f : (E × E) → ℝ) =ᵐ[nu y] fun z => f z.1) ∧
              ‖B.toContinuousLinearMap‖ ≤ 1 ∧ ‖M‖ ≤ 1 ∧
              M.comp B.toContinuousLinearMap = ContinuousLinearMap.id ℝ (Lp ℝ 2 mu) ∧
              (∀ G : (E × E) → ℝ, ∀ hG : MemLp G 2 (nu y),
                let gbar : E → ℝ := fun x => ∫ p, G (x, p) ∂stdGaussian E
                (∀ᵐ x ∂mu, Integrable (fun p => G (x, p)) (stdGaussian E)) ∧
                ∃ hbar : MemLp gbar 2 mu, M (hG.toLp G) = hbar.toLp gbar) ∧
              (∀ f : Lp ℝ 2 mu, J (B f) = B f) ∧
              M.comp J.toContinuousLinearMap = M ∧
              let Kpos : ℝ≥0 → (Lp ℝ 2 mu →L[ℝ] Lp ℝ 2 mu) :=
                fun T => M.comp ((A T).comp B.toContinuousLinearMap)
              Kpos 0 = ContinuousLinearMap.id ℝ (Lp ℝ 2 mu) ∧
              ∀ T : ℝ≥0, (Kpos T).adjoint = Kpos T ∧ ‖Kpos T‖ ≤ 1 ∧
                ∀ f : E → ℝ, ∀ hf : MemLp f 2 mu,
                  let kTf : E → ℝ := fun x =>
                    ∫ p, (∫ w, f ((Z y xRef (x, p) T w).1) ∂P) ∂stdGaussian E
                  (∀ᵐ x ∂mu, ∀ᵐ p ∂stdGaussian E,
                    Integrable (fun w => f ((Z y xRef (x, p) T w).1)) P) ∧
                  (∀ᵐ x ∂mu, Integrable
                    (fun p => ∫ w, f ((Z y xRef (x, p) T w).1) ∂P) (stdGaussian E)) ∧
                  ∃ hk : MemLp kTf 2 mu, Kpos T (hf.toLp f) = hk.toLp kTf)


set_option maxHeartbeats 2200000
set_option maxRecDepth 12000

Proof roadmap

1. 1Keep the same actual process and phase operators

   Invoke actual108 once and retain every conclusion, including the same global Z, phase family A and canonical flip J. Fix y,r. No independently selected process or kernel is substituted.

2. 2Construct the canonical position lift and adjoint

   The second factor gamma is a probability measure, hence fst pushes pi_y times gamma to pi_y. Its canonical L2 pullback B is a linear isometry. Set M=B*. The isometry gives B*B=I and norm(B)≤1; the Hilbert adjoint preserves operator norm. Tilted measures are zero or probability, so their finiteness and all product instances are obtained internally.

3. 3Obtain Gaussian sections and their L1 mean

   For any raw G in L2(nu_y), finiteness implies G in L1. Signed product Fubini gives Gaussian-integrable sections almost everywhere and an L1 Gaussian mean gbar. Independently M[G] is an L2 class, hence has an L1 representative. Its equality with gbar has not yet been assumed.

4. 4Identify every measurable-set integral

   Test against the L2 indicator i=1_s. Its canonical lift agrees with 1_s(x) almost everywhere. The integrand 1_s(x)G(x,p) is L1 by restriction of G to fst inverse(s). Adjoint duality and the L2 inner integral identify its product integral; signed Fubini gives the set integral of gbar. All changes of representatives are almost everywhere.

5. 5Recover the actual Gaussian L2 representative

   The two L1 functions have identical integrals on all measurable finite-measure sets, so they agree almost everywhere. Transfer L2 membership from the existing class M[G] to the literal Gaussian mean and use Lp extensionality. This order avoids assuming the mean is L2 to prove it is L2.

6. 6Absorb the momentum flip

   Transport the canonical lift representative through the measure-preserving reflection. Since fst(Rz)=fst(z), J B=B. The isometry and involution give J*=J by inner-product extensionality. Taking adjoints of J B=B gives M J=M.

7. 7Compress to a self-adjoint contraction

   Define K_T=M A_T B. At zero time A_0=I and MB=I give K_0=I. Reverse composition under the adjoint, use the double-adjoint identity for B and A_T*=J A_T J, and absorb both flips. Operator-norm composition and the three bounds1 prove contraction.

8. 8Identify the same-process position expectation

   Lift any raw position f in L2 to F(x,p)=f(x), and identify B[f]=[F]. The inherited same-A contract gives integrable clock sections and the literal phase expectation opF in L2. Product-AE slicing supplies the nested inner integrability. Apply the universal Gaussian identification to opF to obtain outer integrability and the literal kTf class. No exchange of Gaussian and clock integrals is used.