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MIPRE.Background.LIDT.MIPStarRE.LDT.SelfImprovement.Theorems.Results.HelperCompleteness.Bracketed

Helper completeness: bracketed mass identities and reduced reductions #

This file contains the exact bracketed reindexing of the helper-stage mass, the paper-shaped completeness assemblies, and the reduced addInU reduction used by the surrounding self-improvement theorem.

References #

theorem MIPStarRE.LDT.SelfImprovement.helper_mass_eq_avg_pointwise_sandwich_sum {ι : Type u_1} [Fintype ι] [DecidableEq ι] (params : Parameters) [FieldModel params.q] (strategy : SymStrat params ι) (T : SubMeas (Polynomial params) ι) :
subMeasMass strategy.state (averagedSandwichedPolynomialSubMeas params strategy T).liftLeft = avgOver (uniformDistribution (Point params)) fun (u : Point params) => h : Polynomial params, ev strategy.state (leftTensor (sandwichedPolynomialOutcomeOperatorAt params strategy T u h))

Exact Hhat reindexing for the helper-stage left-tensor mass.

Expanding Hhat = E_u H^u through subMeasMass ψ Hhat.liftLeft = ev ψ (Hhat.total ⊗ I), swapping the leftTensor through the polynomial sum, and pulling the ev through the per-outcome point average gives the paper identity

⟨ψ| Hhat ⊗ I |ψ⟩ = E_u Σ_h ⟨ψ| H^u_h ⊗ I |ψ⟩,

where H^u_h = A^u_{h(u)} · T_h · A^u_{h(u)} is sandwichedPolynomialOutcomeOperatorAt. This is the algebraic opening of the helper-stage completeness chain at references/ldt-paper/self_improvement.tex, lines 354--356, mirrored at blueprint/src/chapter/ch07_self_improvement.tex, lines 103--106.

The conclusion is exact (not approximate) and depends on no input-consistency or SDP hypotheses. The remaining helper-completeness ingredients --- the Cauchy--Schwarz reductions (self_improvement.tex:360--403) onto a Z ⊗ I-shaped expression, and the input-consistency dual-mass bound already supplied by input_consistency_dual_mass_lower_bound --- compose against this identity.

theorem MIPStarRE.LDT.SelfImprovement.helper_pointwise_sandwich_sum_eq_bracketed {ι : Type u_1} [Fintype ι] [DecidableEq ι] (params : Parameters) [FieldModel params.q] (strategy : SymStrat params ι) (T : SubMeas (Polynomial params) ι) (u : Point params) :
h : Polynomial params, ev strategy.state (leftTensor (sandwichedPolynomialOutcomeOperatorAt params strategy T u h)) = a : Fq params, ev strategy.state (leftTensor (((strategy.pointMeasurement u).outcome a * h : Polynomial params with h.toFun u = a, T.outcome h) * (strategy.pointMeasurement u).outcome a))

Per-point bracketing identity for the helper-stage left-tensor mass.

Fiberwise reindexing by h ↦ h(u) and pulling A^u_a · _ · A^u_a through the sum, leftTensor, and ev give the paper identity at a fixed point u:

Σ_h ⟨ψ| H^u_h ⊗ I |ψ⟩ = Σ_a ⟨ψ| (A^u_a · T_{[h(u) = a]} · A^u_a) ⊗ I |ψ⟩,

where H^u_h = A^u_{h(u)} · T_h · A^u_{h(u)} is sandwichedPolynomialOutcomeOperatorAt, and the bracketed T_{[h(u) = a]} = Σ_{h : h u = a} T_h is the inner fiber sum.

This is the identity eq:bracketize-the-expression of references/ldt-paper/self_improvement.tex, lines 356--358 (mirrored at blueprint/src/chapter/ch07_self_improvement.tex, lines 110--113), at a fixed point u (before averaging). The conclusion is exact (not approximate) and depends on no input-consistency, SDP, or self-consistency hypotheses; it is purely an algebraic regrouping of Σ_h H^u_h by the value of h at u.

Composed with helper_mass_eq_avg_pointwise_sandwich_sum, this yields the bracketed form helper_mass_eq_avg_pointwise_bracketed_sum of the helper-stage Hhat ⊗ I mass, which is the starting point for the remaining Cauchy--Schwarz reduction at self_improvement.tex:360--403 toward eq:gonna-use-this-later-H-versus-Z.

theorem MIPStarRE.LDT.SelfImprovement.helper_mass_eq_avg_pointwise_bracketed_sum {ι : Type u_1} [Fintype ι] [DecidableEq ι] (params : Parameters) [FieldModel params.q] (strategy : SymStrat params ι) (T : SubMeas (Polynomial params) ι) :
subMeasMass strategy.state (averagedSandwichedPolynomialSubMeas params strategy T).liftLeft = avgOver (uniformDistribution (Point params)) fun (u : Point params) => a : Fq params, ev strategy.state (leftTensor (((strategy.pointMeasurement u).outcome a * h : Polynomial params with h.toFun u = a, T.outcome h) * (strategy.pointMeasurement u).outcome a))

Bracketed form of the helper-stage Hhat ⊗ I mass identity.

Combines helper_mass_eq_avg_pointwise_sandwich_sum with the per-point bracketing identity helper_pointwise_sandwich_sum_eq_bracketed:

⟨ψ| Hhat ⊗ I |ψ⟩ = E_u Σ_a ⟨ψ| (A^u_a · T_{[h(u) = a]} · A^u_a) ⊗ I |ψ⟩,

where T_{[h(u) = a]} = Σ_{h : h u = a} T_h. This is the second equality in the displayed completeness chain at references/ldt-paper/self_improvement.tex, lines 354--358 (mirrored at blueprint/src/chapter/ch07_self_improvement.tex, lines 103--113), composed with the bracketing reindexing eq:bracketize-the-expression. The conclusion is exact (not approximate) and depends on no input-consistency, SDP, or self-consistency hypotheses.

The named bracketed helper-completeness quantity is exactly the helper-stage Hhat ⊗ I mass for the averaged sandwiched family.

This is the Lean form of the equality labelled eq:bracketize-the-expression, after composing the fiberwise reindexing with the preceding expansion of Hhat as the average of the pointwise sandwiched submeasurements.

theorem MIPStarRE.LDT.SelfImprovement.helper_hhat_vs_z_of_bracketed_cauchy_schwarz_and_complementary_slackness {ι : Type u_1} [Fintype ι] [DecidableEq ι] (params : Parameters) [FieldModel params.q] (strategy : SymStrat params ι) (eps delta : Error) {T : Measurement (Polynomial params) ι} {Hhat : SubMeas (Polynomial params) ι} {Z : Quantum.Op ι} (hhelper : SelfImprovementHelperConclusion params strategy T Hhat Z eps delta) (hmove_left : |helperFirstMovedCompletenessQuantity params strategy T.toSubMeas - helperBracketedCompletenessQuantity params strategy T.toSubMeas| 2 * delta) (hremove_right : |helperLinearizedCompletenessQuantity params strategy T.toSubMeas - helperFirstMovedCompletenessQuantity params strategy T.toSubMeas| delta) (hslack : ∀ (h : Polynomial params), T.outcome h * averagedPointOperator params strategy h = T.outcome h * Z) :
ev strategy.state (leftTensor Z) - 3 * delta subMeasMass strategy.state Hhat.liftLeft

The paper-shaped Hhat-versus-Z comparison assembled from the bracketed expression, the two Cauchy--Schwarz estimates, and complementary slackness.

The first Cauchy--Schwarz hypothesis moves from the bracketed expression E_u Σ_a ⟨ψ, (A^u_a T_[h(u)=a] A^u_a) ⊗ I ψ⟩ to helperFirstMovedCompletenessQuantity. The second removes the remaining right-register copy of A^u_a, giving helperLinearizedCompletenessQuantity. The latter is then identified with the dual mass by the SDP complementary-slackness equation.

theorem MIPStarRE.LDT.SelfImprovement.helper_hhat_vs_z_of_self_consistency_and_complementary_slackness {ι : Type u_1} [Fintype ι] [DecidableEq ι] (params : Parameters) [FieldModel params.q] (strategy : SymStrat params ι) (eps delta : Error) {T : Measurement (Polynomial params) ι} {Hhat : SubMeas (Polynomial params) ι} {Z : Quantum.Op ι} (hhelper : SelfImprovementHelperConclusion params strategy T Hhat Z eps delta) (hssc : BipartiteSSCRel strategy.state (uniformDistribution (Point params)) strategy.pointMeasurement.toIdxSubMeas delta) (hslack : ∀ (h : Polynomial params), T.outcome h * averagedPointOperator params strategy h = T.outcome h * Z) :
ev strategy.state (leftTensor Z) - 3 * delta subMeasMass strategy.state Hhat.liftLeft

The Hhat-versus-Z comparison from point self-consistency and complementary slackness.

This is the helper-completeness comparison at eq:gonna-use-this-later-H-versus-Z with the two Cauchy--Schwarz estimates supplied internally by helper_first_move_abs_sub_bracketed_le_two_sqrt_delta and helper_second_move_abs_sub_first_moved_le_sqrt_delta.

theorem MIPStarRE.LDT.SelfImprovement.helper_completeness_of_bracketed_cauchy_schwarz_input_consistency {ι : Type u_1} [Fintype ι] [DecidableEq ι] (params : Parameters) [FieldModel params.q] (strategy : SymStrat params ι) (G : Measurement (Polynomial params) ι) (eps delta nu : Error) (heps : 0 eps) (hdelta : 0 delta) {T : Measurement (Polynomial params) ι} {Hhat : SubMeas (Polynomial params) ι} {Z : Quantum.Op ι} (hhelper : SelfImprovementHelperConclusion params strategy T Hhat Z eps delta) (hmove_left : |helperFirstMovedCompletenessQuantity params strategy T.toSubMeas - helperBracketedCompletenessQuantity params strategy T.toSubMeas| 2 * delta) (hremove_right : |helperLinearizedCompletenessQuantity params strategy T.toSubMeas - helperFirstMovedCompletenessQuantity params strategy T.toSubMeas| delta) (hslack : ∀ (h : Polynomial params), T.outcome h * averagedPointOperator params strategy h = T.outcome h * Z) (hcons : ConsRel strategy.state (uniformDistribution (Point params)) strategy.pointMeasurement.toIdxSubMeas (polynomialEvaluationFamily params G.toSubMeas) nu) :
CompletenessAtLeast strategy.state Hhat.liftLeft (1 - nu - selfImprovementHelperError params eps delta)

Helper-stage completeness from the paper-shaped Cauchy--Schwarz estimates, complementary slackness, and input consistency.

Compared with helper_completeness_of_cauchy_schwarz_input_consistency, this version names the expression before the first Cauchy--Schwarz move exactly as it appears in eq:bracketize-the-expression; the equality with the Hhat-mass is supplied internally by helperBracketedCompletenessQuantity_eq_mass.

theorem MIPStarRE.LDT.SelfImprovement.helper_completeness_of_self_consistency_complementary_slackness_input_consistency {ι : Type u_1} [Fintype ι] [DecidableEq ι] (params : Parameters) [FieldModel params.q] (strategy : SymStrat params ι) (G : Measurement (Polynomial params) ι) (eps delta nu : Error) (heps : 0 eps) (hdelta : 0 delta) {T : Measurement (Polynomial params) ι} {Hhat : SubMeas (Polynomial params) ι} {Z : Quantum.Op ι} (hhelper : SelfImprovementHelperConclusion params strategy T Hhat Z eps delta) (hssc : BipartiteSSCRel strategy.state (uniformDistribution (Point params)) strategy.pointMeasurement.toIdxSubMeas delta) (hslack : ∀ (h : Polynomial params), T.outcome h * averagedPointOperator params strategy h = T.outcome h * Z) (hcons : ConsRel strategy.state (uniformDistribution (Point params)) strategy.pointMeasurement.toIdxSubMeas (polynomialEvaluationFamily params G.toSubMeas) nu) :
CompletenessAtLeast strategy.state Hhat.liftLeft (1 - nu - selfImprovementHelperError params eps delta)

Helper-stage completeness from point self-consistency, complementary slackness, and input consistency.

This theorem removes the two external Cauchy--Schwarz hypotheses from helper_completeness_of_bracketed_cauchy_schwarz_input_consistency; both are proved from the single point-measurement self-consistency hypothesis.

theorem MIPStarRE.LDT.SelfImprovement.helper_slackness_eq_of_helper_with_slackness {ι : Type u_1} [Fintype ι] [DecidableEq ι] (params : Parameters) [FieldModel params.q] (strategy : SymStrat params ι) (eps delta : Error) {T : Measurement (Polynomial params) ι} {Hhat : SubMeas (Polynomial params) ι} {Z : Quantum.Op ι} (hhelper : SelfImprovementHelperConclusionWithSlackness params strategy T Hhat Z eps delta) (h : Polynomial params) :
T.outcome h * averagedPointOperator params strategy h = T.outcome h * Z

Extract the orientation of complementary slackness used by the helper completeness proof from the strengthened helper conclusion.

theorem MIPStarRE.LDT.SelfImprovement.helper_hhat_vs_z_of_self_consistency_and_helper_slackness {ι : Type u_1} [Fintype ι] [DecidableEq ι] (params : Parameters) [FieldModel params.q] (strategy : SymStrat params ι) (eps delta : Error) {T : Measurement (Polynomial params) ι} {Hhat : SubMeas (Polynomial params) ι} {Z : Quantum.Op ι} (hhelper : SelfImprovementHelperConclusionWithSlackness params strategy T Hhat Z eps delta) (hssc : BipartiteSSCRel strategy.state (uniformDistribution (Point params)) strategy.pointMeasurement.toIdxSubMeas delta) :
ev strategy.state (leftTensor Z) - 3 * delta subMeasMass strategy.state Hhat.liftLeft

The Hhat-versus-Z comparison from point self-consistency and a helper conclusion carrying SDP complementary slackness.

This is the version of eq:gonna-use-this-later-H-versus-Z whose inputs are a single strengthened helper conclusion and point-measurement self-consistency, rather than a separate family of slackness equations.

theorem MIPStarRE.LDT.SelfImprovement.helper_completeness_of_self_consistency_helper_slackness_input_consistency {ι : Type u_1} [Fintype ι] [DecidableEq ι] (params : Parameters) [FieldModel params.q] (strategy : SymStrat params ι) (G : Measurement (Polynomial params) ι) (eps delta nu : Error) (heps : 0 eps) (hdelta : 0 delta) {T : Measurement (Polynomial params) ι} {Hhat : SubMeas (Polynomial params) ι} {Z : Quantum.Op ι} (hhelper : SelfImprovementHelperConclusionWithSlackness params strategy T Hhat Z eps delta) (hssc : BipartiteSSCRel strategy.state (uniformDistribution (Point params)) strategy.pointMeasurement.toIdxSubMeas delta) (hcons : ConsRel strategy.state (uniformDistribution (Point params)) strategy.pointMeasurement.toIdxSubMeas (polynomialEvaluationFamily params G.toSubMeas) nu) :
CompletenessAtLeast strategy.state Hhat.liftLeft (1 - nu - selfImprovementHelperError params eps delta)

Helper-stage completeness from point self-consistency, a helper conclusion carrying SDP complementary slackness, and input consistency.

This theorem removes the standalone hslack hypothesis from helper_completeness_of_self_consistency_complementary_slackness_input_consistency; the slackness equations are read from SelfImprovementHelperConclusionWithSlackness.

theorem MIPStarRE.LDT.SelfImprovement.sdp_statement_with_slackness {ι : Type u_1} [Fintype ι] [DecidableEq ι] (params : Parameters) [FieldModel params.q] (strategy : SymStrat params ι) :

Paper-origin statement for lem:sdp with complementary slackness.

Paper origin: references/ldt-paper/self_improvement.tex lines 62--88 state \label{lem:sdp} for the primal/dual SDP pair and assert optimal witnesses {T_g}, Z with ∑ g, T_g = I and T_g Z = T_g A_g. Lines 168--190 prove this by Slater strong duality and complementary slackness after passing through the canonical SDP form.

The proof transports the formalized canonical optimal-pair output for the Section 9 SDP back to the paper's abstract notation. That canonical optimal pair is obtained from the finite-dimensional strong-duality argument and the slack-block saturation step in the matrix realization.

theorem MIPStarRE.LDT.SelfImprovement.sdp_slackness_measurement {ι : Type u_1} [Fintype ι] [DecidableEq ι] (params : Parameters) [FieldModel params.q] (strategy : SymStrat params ι) :
∃ (T : Measurement (Polynomial params) ι) (Z : Quantum.Op ι), 0 Z (∀ (g : Polynomial params), 0 sdpDualSlackOperator params strategy Z g) ∀ (g : Polynomial params), sdpComplementarySlacknessEquation params strategy T.toSubMeas Z g

Displayed measurement and complementary-slackness conclusion of lem:sdp.

Paper origin: references/ldt-paper/self_improvement.tex lines 82--88 state that the Section 9 SDP admits a primal family {T_g} with ∑ g, T_g = I and a dual operator Z satisfying T_g Z = T_g A_g for every polynomial g. This theorem extracts exactly that complete-measurement and slackness form from the source-shaped SDP statement sdp_statement_with_slackness, whose proof now derives the strong-duality and complementary-slackness witnesses from the canonical Section 9 SDP argument.

theorem MIPStarRE.LDT.SelfImprovement.addInU {ι : Type u_1} [Fintype ι] [DecidableEq ι] (params : Parameters) [FieldModel params.q] (strategy : SymStrat params ι) (eps delta gamma : Error) (hgood : strategy.IsGood eps delta gamma) (T : Measurement (Polynomial params) ι) :
AddInUStatement params strategy T eps delta

Reduced version of lem:add-in-u.

This currently keeps only the global-variance consequence used downstream. It now derives that consequence from the post-triangle six-step edge-transport chain bound via globalVarianceOfPointsFromTransportChainBound. The gamma and hgood arguments are intentionally retained so this reduced theorem still matches the surrounding self-improvement API and can be strengthened back to the full paper statement without another caller-wide signature change. The selection-dependent transfer inequality from the paper, together with its dependence on an auxiliary family M and the averaged family H, is not yet formalized here.