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MIPRE.Background.LIDT.MIPStarRE.LDT.MakingMeasurementsProjective.Defs

Section 5 — Making measurements projective: definitions #

Definitions for Naimark dilation and orthonormalization, matching Section 5 of references/ldt-paper/orthonormalization.tex and Chapter 4 of the blueprint (blueprint/src/chapter/ch04_projective.tex).

Naimark dilation structure #

The key mathematical content is the Naimark dilation theorem: given submeasurements on a bipartite space, there exist auxiliary registers and projective measurements on the enlarged space that preserve all correlations exactly.

One-measurement Naimark (Lemma 5.2) #

The building block is the one-measurement Naimark lemma. Given a submeasurement {M_a}_{a ∈ α} on Op d, it produces a projective submeasurement on the enlarged space Op (d × Option α). The auxiliary register has dimension |α| + 1, with the extra dimension absorbing the "missing mass" I − ∑ M_a. The construction uses the isometry V|ψ⟩ = ∑_a √M_a |ψ⟩ ⊗ |a⟩ + √(I−M)|ψ⟩ ⊗ |⊥⟩ and defines P̂_a = V† (I ⊗ |a⟩⟨a|) V.

Questionwise Naimark data #

For a prospective full bipartite assembly, one-measurement Naimark is applied independently to each question on each side. The current formal interface records these questionwise local data and their marginal preservation identities, not the full tensor-product correlation theorem.

Matrix-level witnesses #

Concrete Matrix d d ℂ witnesses are provided alongside the abstract operator-algebra formulation, giving honest probability and overlap formulas.

Finite Hilbert space infrastructure #

A finite-dimensional Hilbert space represented by a finite index type.

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    @[reducible, inline]

    Concrete operators on a finite Hilbert space.

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      The SDP separation argument uses the elementwise finite-matrix norm. These instances record that choice once for the project's concrete operator type, rather than reintroducing it in each analytic argument.

      A positive operator used as a possibly unnormalized state witness.

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        Concrete submeasurements on a finite Hilbert space.

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          @[reducible, inline]

          Concrete measurements on a finite Hilbert space.

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            View a concrete matrix submeasurement as the paper-local submeasurement structure.

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              View a concrete matrix measurement as the paper-local measurement structure.

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                One-measurement Naimark dilation (Lemma 5.2) #

                The one-measurement Naimark dilation is the building block for the full theorem. Given a submeasurement M on space d, it produces a projective submeasurement on the enlarged space d × Option α, where Option α models the auxiliary register with one extra dimension none = ⊥ for the missing mass I − ∑ M_a.

                The auxiliary pure-state projector |⊥⟩⟨⊥| on Option α, where ⊥ = none. This is the initial state of the auxiliary register before the Naimark isometry is applied.

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                  The lifted density matrix for one-measurement Naimark dilation: ρ_lifted = |Option α| · (ρ ⊗ |⊥⟩⟨⊥|). The scaling by |Option α| ensures the normalized trace is preserved: τ'(ρ_lifted) = τ(ρ), where τ' is the normalized trace on the enlarged space.

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                    One-measurement Naimark dilation data at the matrix level.

                    Given a submeasurement M : Submeasurement α d, this witnesses the existence of a projective submeasurement on the enlarged space d × Option α that preserves all expectation values. This is Lemma 5.2 of the paper.

                    The construction: let V : H → H ⊗ ℂ^{|α|+1} be the isometry V|ψ⟩ = ∑_a √M_a |ψ⟩ ⊗ |a⟩ + √(I−M)|ψ⟩ ⊗ |⊥⟩. Then P̂_a = V† (I ⊗ |a⟩⟨a|) V is a projection, and ⟨ψ|M_a|ψ⟩ = ⟨ψ⊗⊥|P̂_a|ψ⊗⊥⟩.

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                      Positivity of a lifted Naimark effect, derived from its projectivity.

                      Lean-only consequence of the one-measurement Naimark data: the paper records the lifted effects as projections, and positivity is supplied here by the Mathlib star-projection order theorem through IsStarProjection.nonneg.

                      Questionwise Naimark data #

                      The current Lean data applies one-measurement Naimark independently to each question on each side.

                      structure MIPStarRE.LDT.MakingMeasurementsProjective.NaimarkData (QuestionA : Type u_1) (OutcomeA : Type u_2) (QuestionB : Type u_3) (OutcomeB : Type u_4) (ι : Type u_5) [Fintype QuestionA] [DecidableEq QuestionA] [Fintype OutcomeA] [DecidableEq OutcomeA] [Fintype QuestionB] [DecidableEq QuestionB] [Fintype OutcomeB] [DecidableEq OutcomeB] [Fintype ι] [DecidableEq ι] :
                      Type (max (max (max (max u_1 u_2) u_3) u_4) u_5)

                      Questionwise Naimark data for the prospective full assembly.

                      Given submeasurements on space ι, this carries the questionwise one-measurement Naimark dilations used as the local building blocks for the full tensor-product assembly.

                      • left (x : QuestionA) : OneMeasNaimarkData OutcomeA ι

                        Alice's questionwise one-measurement Naimark dilations.

                      • right (y : QuestionB) : OneMeasNaimarkData OutcomeB ι

                        Bob's questionwise one-measurement Naimark dilations.

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                        Error functions for orthonormalization #

                        The explicit error in thm:orthonormalization.

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                          Error bound of the direct completion-route orthonormalization theorem.

                          The paper proves the sharper orthonormalizationError ζ. The direct completion route first converts the completed measurement's self-consistency estimate into a source-almost-projective estimate, and therefore uses this weaker named envelope.

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                            The explicit error in the measurement version of the lemma.

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                              The spectral-truncation error when rounding one almost-projective effect to a projection via eigenvalue truncation. Dominated by √ζ.

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                                The rounding error when converting an almost-projective POVM to a projective submeasurement.

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