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Marker overlap contracts the cross term: the detection law and the visibility bound of an overlap-normalized marked model

Physical scope

The declared overlap-normalized marked two-component model of the interferometer pair: the phase family of marked preparations has unit norm, its local position-bin detection law is the which-path law plus a cross term whose modulus is contracted by the marker overlap, and the fringe visibility of the family at a bin is bounded by the marker overlap and computed exactly. The statement is a conditional computation in the declared model; it asserts no measured pattern, no counts, no decoherence mechanism, no irreversibility, no which-path ontology and no empirical fact.

Statement

Adopt the declared marked two-component model of Declared marked two-component model: path components, marker states, phase family, detection weights and fringe visibility with unit path components ψ1,ψ2∈Hs, unit marker states e1,e2∈K, phase family ρ(φ), marker-carried which-path preparation ρmix, and a declared detection bin B. Assume the model is overlap-normalized, ⟨ψ1,ψ2⟩=0, and assume the Axiom of Countable Choice and the Axiom of Choice (The Axiom of Countable Choice (ACω), The Axiom of Choice), as required by the cited position and local-readout suppliers. Put γ(B):=⟨e1,e2⟩ ⟨G(B)ψ1,ψ2⟩,pj(B):=⟨G(B)ψj,ψj⟩(j=1,2),pmix(B)=12(p1(B)+p2(B)). Then:

(a) Unit-norm phase family. ∥Ψ(φ)∥=1 for every φ, so ρ(φ)=TΨ(φ),Ψ(φ).

(b) Detection law. For every φ, p(φ)(B)=pmix(B)+Re⁡(e−iφγ(B)).

(c) Contraction of the cross term. For every φ, ∣p(φ)(B)−pmix(B)∣≤∣γ(B)∣≤∣⟨e1,e2⟩∣p1(B)p2(B)≤∣⟨e1,e2⟩∣ pmix(B). In particular, if e1⊥e2, then p(φ)(B)=pmix(B) for every φ: the marked detection law is exactly the which-path law.

(d) Visibility. Writing γ(B)=∣γ(B)∣eiθ with θ∈[0,2π), one has sup⁡φp(φ)(B)=pmix(B)+∣γ(B)∣,inf⁡φp(φ)(B)=pmix(B)−∣γ(B)∣, so that, whenever pmix(B)>0, the fringe visibility of clause (e) of the definition is V(B)=∣γ(B)∣pmix(B)=∣⟨e1,e2⟩∣ ∣⟨G(B)ψ1,ψ2⟩∣pmix(B)≤∣⟨e1,e2⟩∣.

(e) Extremes. If the model is trivially marked, ∣⟨e1,e2⟩∣=1, then for every bin with pmix(B)>0 one has V(B)=∣⟨G(B)ψ1,ψ2⟩∣pmix(B)≤1; if e1⊥e2, then V(B)=0 for every bin with pmix(B)>0.

(f) Scope. Clauses (a)-(e) are conditional computations in the declared model. They assert no measured pattern, no trial counts, no statistical analysis, no decoherence mechanism, no irreversibility and no which-path ontology, and they contain no empirical claim.

Facts & Assumptions

Given: The declared overlap-normalized marked model with unit ψ1,ψ2,e1,e2, ⟨ψ1,ψ2⟩=0; a declared detection bin B; the phase family and preparations of the model definition; the Axiom of Countable Choice and the Axiom of Choice.

[F1]

Model data. Ψ(φ)=12(κ(ψ1⊗e1)+eiφκ(ψ2⊗e2)), ρ(φ)=ρ^(Ψ(φ)), ρmix=12Tκ(ψ1⊗e1),κ(ψ1⊗e1)+12Tκ(ψ2⊗e2),κ(ψ2⊗e2), p(φ)(B)=tr⁡(ρ(φ)(G(B)⊗IK)), pmix(B)=12(p1(B)+p2(B)), and G(B) is the position spectral projection with pj(B)=∥G(B)ψj∥2∈[0,1] (Declared marked two-component model: path components, marker states, phase family, detection weights and fringe visibility clauses (a)-(d), Position and momentum outcome laws of the massive spin-s model clause (b)).

[F2]

Partial trace on elementary rank-one operators. The partial trace is linear and satisfies Tr⁡KTx⊗e,y⊗f=⟨e,f⟩Tx,y for all x,y∈Hs and e,f∈K (Separable partial trace and its basic properties clauses (a), (c)).

[F3]

Partial-trace pairing and local weights. For every trace-class R on the composite and every bounded X on the particle factor, tr⁡(R(X⊗IK))=tr⁡((Tr⁡KR)X) by Separable partial trace and its basic properties clause (a). Taking X=G(B) is legitimate because G(B) is a bounded projection, even though its outcome set is a Borel subset of R3. The model definition [F1] reads this pairing as its position-bin detection weight. For a real-valued assigned sharp observable and a Borel subset of R, the corresponding physical local-readout law is separately Local readout laws and reduced preparations: the subsystem state determines, and is determined by, the local statistics clause (a); no extension of that theorem's outcome domain is needed here.

[F4]

Tensor and rank-one calculus. The tensor pairing is ⟨κ(x⊗e),κ(y⊗f)⟩=⟨x,y⟩⟨e,f⟩ (Hilbert tensor construction: inner product, completion and product bases). Rank-one operators Tx,yz=⟨z,y⟩x are linear in x, conjugate-linear in y, and for bounded S satisfy tr⁡(Tx,yS)=⟨Sx,y⟩ by the product and trace formulas of Rank-one operator calculus clauses (a), (b), (d).

[F5]

Cauchy-Schwarz. For vectors in a complex inner product space ∣⟨x,y⟩∣≤∥x∥ ∥y∥ (Cauchy–Schwarz: ∣⟨u,v⟩∣≤∥u∥∥v∥, with equality exactly for linearly dependent vectors).

[F6]

Choice hypothesis. The Axiom of Choice is assumed by the cited position and local-readout suppliers for their general spectral PVM constructions (The Axiom of Choice).

Proof

technique · direct; expand the tensor norm and the rank-one operator, then apply the partial trace to obtain the unit norm and the reduced weight, convert the weight into the composite detection law by the local readout law, bound the cross term by Cauchy-Schwarz, and evaluate the supremum and infimum of the resulting cosine modulation

Given: The data of the statement and [F1]-[F5].

1.1givenF1F2F4algebra

[Unit norm and reduced weight] Put qj=κ(ψj⊗ej), α=1/2 and β=eiφ/2. By [F4], ∥qj∥=1 and ⟨q1,q2⟩=⟨ψ1,ψ2⟩⟨e1,e2⟩=0, so ∥Ψ(φ)∥2=∣α∣2+∣β∣2=1. Thus I=R and ρ(φ)=TΨ(φ),Ψ(φ) by [F1]. Expanding by the sesquilinearity in [F4] gives TΨ,Ψ=∣α∣2Tq1,q1+∣β∣2Tq2,q2+αβ‾Tq1,q2+α‾βTq2,q1. Applying [F2] termwise gives ρ(φ)A=12Tψ1,ψ1+12Tψ2,ψ2+12e−iφ⟨e1,e2⟩Tψ1,ψ2+12eiφ⟨e2,e1⟩Tψ2,ψ1. This proves (a) and the reduction identity for every spin label, without applying a scalar-L2 supplier to vector-valued paths.

2.1givenF1F3F4F6step 1.1algebra

[Detection law] By [F3], p(φ)(B)=tr⁡(ρ(φ)(G(B)⊗IK))=tr⁡(ρ(φ)AG(B)); since G(B) is a bounded self-adjoint operator with G(B)=M1B and Tx,y pairs as tr⁡(Tx,yG(B))=⟨G(B)x,y⟩ by [F4], the weight of step 1.1 gives p(φ)(B)=12p1(B)+12p2(B)+Re⁡(e−iφ⟨e1,e2⟩⟨G(B)ψ1,ψ2⟩)=pmix(B)+Re⁡(e−iφγ(B)), which is (b).

3.1givenF1F5step 2.1algebra

[Cross-term contraction] Since G(B)=G(B)∗=G(B)2, ⟨G(B)ψ1,ψ2⟩=⟨G(B)ψ1,G(B)ψ2⟩. By [F5] its modulus is at most p1(B)p2(B). Hence step 2.1 gives ∣p(φ)(B)−pmix(B)∣≤∣γ(B)∣≤∣⟨e1,e2⟩∣p1(B)p2(B)≤∣⟨e1,e2⟩∣pmix(B), where the last inequality follows from (p1−p2)2≥0. The marker overlap is at most one by [F5] and unit normalization. If it is zero, γ(B)=0 and the detection law is pmix(B) for every phase. This proves (c), including zero-weight bins.

4.1givenF1step 2.1step 3.1algebra

[Visibility] Write γ(B)=∣γ(B)∣eiθ when γ(B)≠0; then Re⁡(e−iφγ(B))=∣γ(B)∣cos⁡(θ−φ), whose supremum over φ∈R is ∣γ(B)∣ (attained at φ=θ) and whose infimum is −∣γ(B)∣ (attained at φ=θ+π); when γ(B)=0 the function is identically zero and the same formulae hold. Hence sup⁡φp(φ)(B)=pmix(B)+∣γ(B)∣ and inf⁡φp(φ)(B)=pmix(B)−∣γ(B)∣, and if pmix(B)>0 the definition of the visibility gives V(B)=∣γ(B)∣/pmix(B); the bound V(B)≤∣⟨e1,e2⟩∣ is step 3.1. This is (d), and (e) is the special case ∣⟨e1,e2⟩∣=1 using the ratio bound of step 3.1 and the case e1⊥e2.

5.1step 1.1step 2.1step 3.1step 4.1∎

[Assembly and scope] Step 1.1 is (a), step 2.1 is (b), step 3.1 is (c), step 4.1 is (d), (e); only the declared model, its overlap-normalized hypothesis and the cited mathematics were used, with no measured pattern, count or mechanism asserted, which is (f).

Remarks

  • What the bound does and does not say. The factor ∣⟨e1,e2⟩∣ is an upper bound on the visibility of the declared phase family; the actual visibility also contains the overlap factor ∣⟨G(B)ψ1,ψ2⟩∣/pmix(B) of the path components at the bin, so a large marker overlap alone does not guarantee a visible fringe and a small marker overlap alone does not by itself describe a measured pattern.
  • No mechanism claim. The marker is part of the declared preparation; the computation exhibits the correlation between the marker state and the path component as the origin of the reduced contrast in the model. It asserts no dynamical decoherence process, no irreversibility and no preference among interpretations of the alternatives.

Depends on

Dependency tree · 2 levels

Sources