Section 6 — Definitions #
This file contains restriction/lifting maps, section-local error terms, averaging operators, and tensor-placement bookkeeping for the induction step.
References #
references/ldt-paper/inductive_step.tex
Lift an axis-line answer from the restricted slice back to the ambient space.
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- MIPStarRE.LDT.MainInductionStep.liftAxisAnswer params x f = MIPStarRE.LDT.AxisLinePolynomial.appendAtHeight params f x
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Restricted slice data keeps the point and axis-parallel measurements complete, and packages a genuine projective measurement on the slice's diagonal answer space.
The paper's outcome-level formula would send a slice polynomial f to the
ambient outcome append_x(f). With the current ambient diagonal answer
encoding, that map is not total on all ambient outcomes, so here we preserve the
verifier-visible base-point readout used in Chapter 10 instead: first
postprocess the ambient slice-preserving diagonal measurement to its value at
zeroCoord in F_q, then re-embed that F_q-valued projective measurement
into the honest slice answer space DiagonalLinePolynomial params using
canonical representatives.
This yields a complete projective measurement on the (m,q,d) diagonal answer
space whose base-point evaluation agrees with the ambient slice-preserving
branch, eliminating the earlier lossy submeasurement while remaining faithful
to the restricted diagonal test actually formalized here.
- state : QuantumState (ι × ι)
The bipartite state carried by the restricted strategy.
- isNormalized : self.state.IsNormalized
The restricted strategy reuses the ambient state's normalization witness.
- pointMeasurement : IdxProjMeas (Point params) (Fq params) ι
The restricted point measurement.
- axisParallelMeasurement : AxisParallelCovariantMeasurement params ι
The restricted axis-parallel line measurement, packaged with transport covariance.
- diagonalMeasurement : IdxProjMeas (DiagonalLine params) (DiagonalLinePolynomial params) ι
The restricted diagonal-line measurement on the honest slice answer space.
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Sampled point answers in the axis-parallel lines test.
Point player receives u (base point) and answers at u.
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Sampled line answers in the axis-parallel lines test,
evaluated at the base point u (parameter zeroCoord).
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Sampled point answers in the j-restricted diagonal test.
Point player receives u and answers at u.
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- strategy.restrictedDiagonalPointAnswerFamily j = MIPStarRE.LDT.diagonalPointAnswerFamilyOf strategy.pointMeasurement j
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Sampled diagonal-line answers in the j-restricted diagonal
test, evaluated at the base point (parameter zeroCoord).
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Failure surrogate for the axis-parallel lines test.
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Failure surrogate for the self-consistency test.
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Failure surrogate for the diagonal lines test.
Averages over restriction index j, then the
j-restricted diagonal test.
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Goodness data for a restricted strategy.
The restricted axis-parallel test fails with probability at most
eps.The restricted self-consistency test fails with probability at most
delta.The restricted diagonal-line test fails with probability at most
gamma.
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Equivalence between slice and ambient axis-line polynomials at a fixed height x:
liftAxisAnswer sends a slice polynomial to its ambient lift, with
AxisLinePolynomial.restrictAtHeight as inverse.
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Restrict an axis-parallel line measurement to the slice at height x.
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Canonical honest slice answer with prescribed value at the base point.
We use the constant polynomial because the restricted diagonal branch only reads
line answers at zeroCoord.
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- MIPStarRE.LDT.MainInductionStep.diagonalValueRepresentative params a = { poly := Polynomial.C (MIPStarRE.LDT.decodeScalar a), degreeBounded := ⋯ }
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Restrict a diagonal-line measurement to the slice at height x.
This is not literally the paper's outcome reindexing
f ↦ DiagonalLinePolynomial.appendAtHeight params f x; that map only covers the
degree-params.m * params.d ambient outcomes. Instead we preserve the only
statistic used by the restricted diagonal test formalized here, namely the
base-point answer at zeroCoord.
Concretely we:
- restrict the ambient line question to the slice-preserving line,
- postprocess the ambient projective measurement to its
zeroCoordvalue inF_q, and - re-embed that
F_q-valued projective measurement into the honest slice answer space viadiagonalValueRepresentative.
This produces a complete projective measurement on
DiagonalLinePolynomial params whose induced base-point answer distribution is
exactly the same as the ambient slice-preserving diagonal measurement.
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Restrict a diagonal-line measurement to the slice at height x, using the
paper-level function-answer alphabet.
Unlike restrictDiagonalMeasurement, this keeps the whole line answer function
rather than only the value at zeroCoord. The map is total because
DiagonalLineAnswer has no degree-bound subtype proof to preserve.
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The x-restricted strategy with function-valued diagonal-line
answers.
This matches the slice-restriction interface in inductive_step.tex, lines
436--455. It is
kept parallel to the current xRestrictedStrategy, whose diagonal field uses the
legacy degree-bounded answer alphabet and therefore only preserves the sampled
base-point readout.
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The function-answer restricted strategy reuses the ambient bipartite state.
The function-answer restricted strategy reindexes point questions by appending the slice height.
The function-answer restricted strategy reuses the parent normalization witness.
The function-answer restricted diagonal measurement is the answer-valued restriction of the ambient diagonal measurement.
Evaluating the answer-valued restricted diagonal measurement at the base point recovers the ambient slice-preserving diagonal readout.
The x-restricted strategy from the proof of the main induction theorem.
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Restricting a strategy does not change its bipartite state.
Restricting a strategy reuses the parent strategy's normalization witness.
Restricting a strategy reindexes point questions by appending the slice height.
Restricting an axis-parallel measurement reindexes outcomes by slice extension.
Postprocessing the restricted diagonal measurement at the base point recovers exactly the ambient slice-preserving diagonal answer distribution at the base point.
The intermediate ν from thm:main-induction.
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The explicit σ of thm:main-induction.
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The section-local self-improvement error.
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The intermediate ν from the section-local pasting theorem.
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The section-local pasting consistency error.
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Tensor-failure expectation on a bipartite space.
Computes ⟨ψ| (Z ⊗ I)(I ⊗ (I - Σ H_a)) |ψ⟩ where Z acts on the left register
and H acts on the right register.
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Probability that a sampled test line in F_q^{m+1} is not parallel to the new axis.
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Reciprocal loss incurred when conditioning away the new axis direction.
In lem:restricted-probabilities, the axis-parallel and diagonal branches use
this same conditioning step, so both averaged slice bounds carry the paper's
common factor ((m + 1) / m).