Section 6 β Induction Step Data #
The intermediate conclusion structures and bookkeeping statements of the induction step: the
conclusions of the induction-level self-improvement and pasting theorems, the restricted
failure profiles, and the stage data for the paper's slice restriction, slice-wise induction,
self-improvement and pasting assembly. This is the counterpart of
MIPRE/Background/LIDT/MIPStarRE/LDT/MainInductionStep/Statements.lean in the port of
planning/c6b-plan.md (milestone M4, section "Port conventions").
A strategy is a SymStrat params.next π K (Co/Test/StrategyCore.lean), whose state is the
symmetric model strategy.state : SymModel π K; the vendored QuantumState (ΞΉ Γ ΞΉ) statements
become statements about that model, with local operators in π (the vendored Op ΞΉ) placed by
strategy.state.L and strategy.state.R, and errors in β (the vendored Error). The left
and right placements leftPlacedSubMeas (ΞΉB := ΞΉ) and rightPlacedSubMeas (ΞΉA := ΞΉ) are
strategy.state.leftPlacedSubMeas and strategy.state.rightPlacedSubMeas, and
tensorFailureExpectation is the one-algebra form of Co/MainInductionStep/Defs.lean.
AnswerMainInductionHypothesis quantifies over the local algebra π and the Hilbert space K
of a symmetric model, in their own universes, where the vendored hypothesis quantifies over a
finite carrier ΞΉ, and only over strategies whose model is a finite pair
(strategy.state.toBipartite.IsFinitePair) without abelian projections in its first player's
operators (NoAbelianProj strategy.state.toBipartite.opsA). These are the hypotheses hS, hA
of the ported orthonormalization (Co/MakingMeasurementsProjective/Orthonormalization.lean),
which the successor step of the induction reaches through self-improvement (the vendored
SelfImprovementTop/Core.lean, line 433); restriction to a slice keeps the state
(xRestrictedAnswerSymStrat_state), so they pass to the slices, and milestone M13 discharges them
for the doubled model with Doubling.isFinitePair and Doubling.noAbelianProj_iff. This departs
from the vendored statement, whose finite carriers need no such hypothesis.
The error constants (mainInductionError, selfImprovementInInductionError,
ldPastingInInductionError, sliceConditioningLoss) are the vendored classical declarations,
imported through Co/MainInductionStep/Defs.lean and named through an explicit open list.
Not ported #
Every declaration of the vendored file has a counterpart here.
References #
In LionSR/MIPStarRE at commit 507e8122, not in this repository:
references/ldt-paper/inductive_step.texreferences/ldt-paper/ld-pasting.tex
Paper origin: references/ldt-paper/inductive_step.tex:249-286
(\label{thm:self-improvement-in-induction-section}).
Conclusion of the induction-level self-improvement theorem.
The strategy's state is the symmetric model strategy.state. Fields that involve placed
operators use leftPlacedSubMeas / rightPlacedSubMeas / tensorFailureExpectation of that
model.
- completeness : strategy.state.CompletenessAtLeast (SubMeas.liftLeft strategy.state H.toSubMeas) (1 - nu - MIPStarRE.LDT.MainInductionStep.selfImprovementInInductionError params eps delta gamma)
The projective submeasurement remains almost complete.
- pointConsistency : strategy.state.ConsRel (MIPStarRE.LDT.uniformDistribution (MIPStarRE.LDT.Point params)) strategy.pointMeasurement.toIdxSubMeas (polynomialEvaluationFamily params H.toSubMeas) (MIPStarRE.LDT.MainInductionStep.selfImprovementInInductionError params eps delta gamma)
The projective submeasurement stays point-consistent with the original strategy.
- strongSelfConsistency : strategy.state.BipartiteSSCRel (MIPStarRE.LDT.uniformDistribution Unit) (constSubMeasFamily H.toSubMeas) (MIPStarRE.LDT.MainInductionStep.selfImprovementInInductionError params eps delta gamma)
The output family is strongly self-consistent in the bipartite sense.
- selfCloseness : strategy.state.SDDRel (MIPStarRE.LDT.uniformDistribution Unit) (constSubMeasFamily (strategy.state.leftPlacedSubMeas H.toSubMeas)) (constSubMeasFamily (strategy.state.rightPlacedSubMeas H.toSubMeas)) (MIPStarRE.LDT.MainInductionStep.selfImprovementInInductionError params eps delta gamma)
The left and right placements of the output family stay close in squared distance.
- bounded : tensorFailureExpectation strategy.state Z H.toSubMeas β€ MIPStarRE.LDT.MainInductionStep.selfImprovementInInductionError params eps delta gamma
The dual witness
Zcontrols the tensor failure expectation ofH. - dominatesAveragePointOperator (h : MIPStarRE.LDT.Polynomial params) : IdxPolyFamily.averagedPointEvaluationOperator strategy h β€ Z
Every averaged point-evaluation operator is dominated by the dual witness
Z.
Instances For
Paper origin: references/ldt-paper/inductive_step.tex:299-338
(\label{thm:ld-pasting-in-induction-section}).
Conclusion of the section-local pasting theorem.
- pointConsistency : strategy.state.ConsRel (MIPStarRE.LDT.uniformDistribution (MIPStarRE.LDT.Point params.next)) strategy.pointMeasurement.toIdxSubMeas (polynomialEvaluationFamily params.next H.toSubMeas) (MIPStarRE.LDT.MainInductionStep.ldPastingInInductionError params k eps delta gamma kappa zeta)
The pasted measurement is point-consistent with the ambient strategy.
Instances For
Bookkeeping data x β¦ (Ξ΅_x, Ξ΄_x, Ξ³_x) for the restricted strategies.
- axisParallel : MIPStarRE.LDT.Fq params β β
The axis-parallel failure bound attached to each slice height.
- selfConsistency : MIPStarRE.LDT.Fq params β β
The self-consistency failure bound attached to each slice height.
- diagonal : MIPStarRE.LDT.Fq params β β
The diagonal-line failure bound attached to each slice height.
- restrictedGood (x : MIPStarRE.LDT.Fq params) : (xRestrictedStrategy params strategy x).IsGood (self.axisParallel x) (self.selfConsistency x) (self.diagonal x)
Each slice-restricted strategy is good with the recorded parameters.
Instances For
Bookkeeping data for answer-valued restricted strategies.
This is the function-answer analogue of RestrictedFailureProfile: each slice is
the restricted strategy interface from inductive_step.tex, lines 436--455.
- axisParallel : MIPStarRE.LDT.Fq params β β
The axis-parallel failure bound attached to each slice height.
- selfConsistency : MIPStarRE.LDT.Fq params β β
The self-consistency failure bound attached to each slice height.
- diagonal : MIPStarRE.LDT.Fq params β β
The diagonal-line failure bound attached to each slice height.
- restrictedGood (x : MIPStarRE.LDT.Fq params) : (xRestrictedAnswerSymStrat params strategy x).IsGood (self.axisParallel x) (self.selfConsistency x) (self.diagonal x)
Each answer-valued slice-restricted strategy is good with the recorded parameters.
Instances For
Average restricted axis-parallel error over slices.
Equations
- MIPRE.LIDT.Co.MainInductionStep.averageRestrictedAxisParallelError params profile = MIPStarRE.LDT.avgOver (MIPStarRE.LDT.uniformDistribution (MIPStarRE.LDT.Fq params)) profile.axisParallel
Instances For
Average restricted self-consistency error over slices.
Equations
- MIPRE.LIDT.Co.MainInductionStep.averageRestrictedSelfConsistencyError params profile = MIPStarRE.LDT.avgOver (MIPStarRE.LDT.uniformDistribution (MIPStarRE.LDT.Fq params)) profile.selfConsistency
Instances For
Average restricted diagonal-line error over slices.
Equations
- MIPRE.LIDT.Co.MainInductionStep.averageRestrictedDiagonalError params profile = MIPStarRE.LDT.avgOver (MIPStarRE.LDT.uniformDistribution (MIPStarRE.LDT.Fq params)) profile.diagonal
Instances For
Average restricted axis-parallel error over answer-valued slices.
Equations
- MIPRE.LIDT.Co.MainInductionStep.averageAnswerRestrictedAxisParallelError params profile = MIPStarRE.LDT.avgOver (MIPStarRE.LDT.uniformDistribution (MIPStarRE.LDT.Fq params)) profile.axisParallel
Instances For
Average restricted self-consistency error over answer-valued slices.
Equations
- One or more equations did not get rendered due to their size.
Instances For
Average restricted diagonal-line error over answer-valued slices.
Equations
- MIPRE.LIDT.Co.MainInductionStep.averageAnswerRestrictedDiagonalError params profile = MIPStarRE.LDT.avgOver (MIPStarRE.LDT.uniformDistribution (MIPStarRE.LDT.Fq params)) profile.diagonal
Instances For
Paper origin: references/ldt-paper/inductive_step.tex:374-412
(\label{lem:restricted-probabilities}).
Bookkeeping data for the restricted-probabilities lemma.
This records a slice-wise error profile together with the three averaged bounds
that appear in the paper: the axis-parallel and diagonal branches both incur the
same conditioning loss ((m + 1) / m), while the self-consistency branch
restricts exactly.
- profileExists : β (profile : RestrictedFailureProfile params strategy), averageRestrictedAxisParallelError params profile β€ MIPStarRE.LDT.MainInductionStep.sliceConditioningLoss params * eps β§ averageRestrictedSelfConsistencyError params profile β€ delta β§ averageRestrictedDiagonalError params profile β€ MIPStarRE.LDT.MainInductionStep.sliceConditioningLoss params * gamma
There is a slice-wise error profile realizing the three averaged restricted bounds.
Instances For
Paper origin: references/ldt-paper/inductive_step.tex:374-412
(\label{lem:restricted-probabilities}); answer-valued variant carrying the
same axis-parallel/self-consistency/diagonal restriction bounds for the
answer-restricted slice profile. This is an answer-valued variant of
RestrictedProbabilitiesStatement against xRestrictedAnswerSymStrat rather
than xRestrictedStrategy; no separate paper anchor exists for the
answer-valued variant.
Bookkeeping data for the answer-valued restricted-probabilities lemma.
- profileExists : β (profile : AnswerRestrictedFailureProfile params strategy), averageAnswerRestrictedAxisParallelError params profile β€ MIPStarRE.LDT.MainInductionStep.sliceConditioningLoss params * eps β§ averageAnswerRestrictedSelfConsistencyError params profile β€ delta β§ averageAnswerRestrictedDiagonalError params profile β€ MIPStarRE.LDT.MainInductionStep.sliceConditioningLoss params * gamma
There is a slice-wise answer-valued error profile realizing the three averaged bounds.
Instances For
Bookkeeping data for the slice-restriction step of thm:main-induction.
Paper origin: references/ldt-paper/inductive_step.tex:374-412
(\label{lem:restricted-probabilities}) and
references/ldt-paper/inductive_step.tex:441-454.
This records an explicit restricted failure profile together with the averaged
bounds extracted from lem:restricted-probabilities.
- profile : RestrictedFailureProfile params strategy
Slice-wise failure profile
x β¦ (Ξ΅_x, Ξ΄_x, Ξ³_x). - axisAverageBound : averageRestrictedAxisParallelError params self.profile β€ MIPStarRE.LDT.MainInductionStep.sliceConditioningLoss params * eps
Averaged axis-parallel slice error bound.
Averaged self-consistency slice error bound.
- diagonalAverageBound : averageRestrictedDiagonalError params self.profile β€ MIPStarRE.LDT.MainInductionStep.sliceConditioningLoss params * gamma
Averaged diagonal slice error bound.
Instances For
Answer-valued slice-restriction data record for the Section 6 induction step.
Paper origin: references/ldt-paper/inductive_step.tex:374-412
(\label{lem:restricted-probabilities}) and the recursive slice application in
references/ldt-paper/inductive_step.tex:441-454.
- profile : AnswerRestrictedFailureProfile params strategy
Slice-wise failure profile for the answer-valued restricted strategies.
- axisAverageBound : averageAnswerRestrictedAxisParallelError params self.profile β€ MIPStarRE.LDT.MainInductionStep.sliceConditioningLoss params * eps
Averaged axis-parallel slice error bound.
Averaged self-consistency slice error bound.
- diagonalAverageBound : averageAnswerRestrictedDiagonalError params self.profile β€ MIPStarRE.LDT.MainInductionStep.sliceConditioningLoss params * gamma
Averaged diagonal slice error bound.
Instances For
Explicit per-slice output of the inductive hypothesis.
Paper origin: references/ldt-paper/inductive_step.tex:441-454.
This is the recursion-entry data: given slice-restriction data, a proof of
thm:main-induction in dimension m is expected to produce a measurement G^x
for every slice height x.
- sliceError : MIPStarRE.LDT.Fq params β β
Slice-wise inductive error
Ο_x. - sliceMeasurement : MIPStarRE.LDT.Fq params β Measurement (MIPStarRE.LDT.Polynomial params) π
Slice-wise inductive measurement
G^x. - pointConsistency (x : MIPStarRE.LDT.Fq params) : strategy.state.ConsRel (MIPStarRE.LDT.uniformDistribution (MIPStarRE.LDT.Point params)) (xRestrictedStrategy params strategy x).pointMeasurement.toIdxSubMeas (polynomialEvaluationFamily params (self.sliceMeasurement x).toSubMeas) (self.sliceError x)
Each
G^xsatisfies the dimension-mpoint-consistency conclusion. - error_le (x : MIPStarRE.LDT.Fq params) : self.sliceError x β€ MIPStarRE.LDT.MainInductionStep.mainInductionError params k (restrictionPkg.profile.axisParallel x) (restrictionPkg.profile.selfConsistency x) (restrictionPkg.profile.diagonal x)
The slice-wise error is bounded by the dimension-
minduction target.
Instances For
Explicit per-slice output of the inductive hypothesis for answer-valued slices.
Paper origin: references/ldt-paper/inductive_step.tex:441-454; answer-valued
restriction interface for the same recursive call.
This is the function-answer recursion-entry data record: the recursive call is made on
xRestrictedAnswerSymStrat, whose diagonal answers retain the whole restricted
function instead of only its value at the base point.
- sliceError : MIPStarRE.LDT.Fq params β β
Slice-wise inductive error
Ο_x. - sliceMeasurement : MIPStarRE.LDT.Fq params β Measurement (MIPStarRE.LDT.Polynomial params) π
Slice-wise inductive measurement
G^x. - pointConsistency (x : MIPStarRE.LDT.Fq params) : strategy.state.ConsRel (MIPStarRE.LDT.uniformDistribution (MIPStarRE.LDT.Point params)) (xRestrictedAnswerSymStrat params strategy x).pointMeasurement.toIdxSubMeas (polynomialEvaluationFamily params (self.sliceMeasurement x).toSubMeas) (self.sliceError x)
Each
G^xsatisfies the dimension-mpoint-consistency conclusion. - error_le (x : MIPStarRE.LDT.Fq params) : self.sliceError x β€ MIPStarRE.LDT.MainInductionStep.mainInductionError params k (restrictionPkg.profile.axisParallel x) (restrictionPkg.profile.selfConsistency x) (restrictionPkg.profile.diagonal x)
The slice-wise error is bounded by the dimension-
minduction target.
Instances For
Paper origin: references/ldt-paper/inductive_step.tex:7-18
(\label{thm:main-induction}); answer-valued analogue.
Main-induction conclusion for a function-answer symmetric strategy.
This is the answer-valued analogue of the conclusion of thm:main-induction.
It is used as the explicit predecessor induction hypothesis for the
paper-faithful answer-valued restriction route: for a strategy in dimension m,
it supplies a global polynomial measurement consistent with the point
measurement at the Section 6 error mainInductionError.
Equations
- One or more equations did not get rendered due to their size.
Instances For
Predicate form of the answer-valued predecessor main-induction hypothesis.
This is a Lean-only interface for the induction step in
references/ldt-paper/inductive_step.tex:441-454. It is deliberately stated at
mainInductionError strength and for AnswerSymStrat, so callers can instantiate
the paper-faithful xRestrictedAnswerSymStrat slices without appealing to the
public main theorem.
It quantifies over symmetric models: a local C*-algebra π : Type v and a Hilbert space
K : Type w, where the vendored hypothesis quantifies over a finite carrier ΞΉ : Type v, and
over strategies whose model is a finite pair without abelian projections in its first player's
operators, the hypotheses hS, hA of the ported orthonormalization, which the successor step
reaches through self-improvement; the vendored hypothesis has none. The
explicit .{u,v,w} universe binder keeps the three universes apart, as the vendored binder
.{u,v} keeps the universe of FieldModel's carrier apart from that of the carrier, so that
a proof that instantiates FieldModel.{0} can still apply the hypothesis to a model in higher
universes.
Equations
- One or more equations did not get rendered due to their size.
Instances For
The slice-local self-improvement error ΞΆ_x.
Equations
- One or more equations did not get rendered due to their size.
Instances For
The slice-local self-improvement error ΞΆ_x for answer-valued slices.
Equations
- One or more equations did not get rendered due to their size.
Instances For
Slice-wise output of the induction-level self-improvement stage.
Paper origin: references/ldt-paper/inductive_step.tex:461-551
(\label{thm:self-improvement-in-induction-section} in use inside the proof of
\label{thm:main-induction}).
Because xRestrictedStrategy is a section-local restricted strategy rather than
literally a SymStrat params interface (its diagonal measurement carries no
reparametrization-invariance field, and it has no role-symmetrization API), this data
records directly the paper-faithful properties that will later be averaged into the
pasting inputs.
- sliceProj : MIPStarRE.LDT.Fq params β ProjSubMeas (MIPStarRE.LDT.Polynomial params) π
Slice-wise projective submeasurement
Δ^x. - sliceWitness : MIPStarRE.LDT.Fq params β π
Slice-wise PSD witness
Z^x. - completeness (x : MIPStarRE.LDT.Fq params) : strategy.state.CompletenessAtLeast (SubMeas.liftLeft strategy.state (self.sliceProj x).toSubMeas) (1 - inductionPkg.sliceError x - sliceSelfImprovementError params restrictionPkg x)
Slice-wise completeness bound.
- pointConsistency (x : MIPStarRE.LDT.Fq params) : strategy.state.ConsRel (MIPStarRE.LDT.uniformDistribution (MIPStarRE.LDT.Point params)) (xRestrictedStrategy params strategy x).pointMeasurement.toIdxSubMeas (polynomialEvaluationFamily params (self.sliceProj x).toSubMeas) (sliceSelfImprovementError params restrictionPkg x)
Slice-wise consistency with the restricted point measurement.
- strongSelfConsistency (x : MIPStarRE.LDT.Fq params) : strategy.state.BipartiteSSCRel (MIPStarRE.LDT.uniformDistribution Unit) (constSubMeasFamily (self.sliceProj x).toSubMeas) (sliceSelfImprovementError params restrictionPkg x)
Slice-wise strong self-consistency.
- selfCloseness (x : MIPStarRE.LDT.Fq params) : strategy.state.SDDRel (MIPStarRE.LDT.uniformDistribution Unit) (constSubMeasFamily (strategy.state.leftPlacedSubMeas (self.sliceProj x).toSubMeas)) (constSubMeasFamily (strategy.state.rightPlacedSubMeas (self.sliceProj x).toSubMeas)) (sliceSelfImprovementError params restrictionPkg x)
Slice-wise left/right closeness needed for the averaged self-consistency input.
- bounded (x : MIPStarRE.LDT.Fq params) : tensorFailureExpectation strategy.state (self.sliceWitness x) (self.sliceProj x).toSubMeas β€ sliceSelfImprovementError params restrictionPkg x
Slice-wise boundedness residual.
- dominatesAveragePointOperator (x : MIPStarRE.LDT.Fq params) (h : MIPStarRE.LDT.Polynomial params) : IdxPolyFamily.averagedSlicePointEvaluationOperator strategy x h β€ self.sliceWitness x
Slice-wise domination of the averaged point operator.
Instances For
The slice-indexed polynomial family obtained by collecting the improved
slice measurements Δ^x together with the slice-wise witnesses Z^x.
Equations
- One or more equations did not get rendered due to their size.
Instances For
The slice family of pkg.family is the improved slice family Δ^x.
The witness of pkg.family is the slice witness Z^x.
The domination target of pkg.family is the averaged slice-point evaluation operator.
Slice-wise output of the induction-level self-improvement stage for answer-valued restricted strategies.
Paper origin: references/ldt-paper/inductive_step.tex:461-551;
answer-valued restriction interface for the same self-improvement stage.
This mirrors SelfImprovementData, but its point-consistency field is stated
against xRestrictedAnswerSymStrat, the function-answer restricted strategy.
- sliceProj : MIPStarRE.LDT.Fq params β ProjSubMeas (MIPStarRE.LDT.Polynomial params) π
Slice-wise projective submeasurement
Δ^x. - sliceWitness : MIPStarRE.LDT.Fq params β π
Slice-wise PSD witness
Z^x. - completeness (x : MIPStarRE.LDT.Fq params) : strategy.state.CompletenessAtLeast (SubMeas.liftLeft strategy.state (self.sliceProj x).toSubMeas) (1 - inductionPkg.sliceError x - answerSliceSelfImprovementError params restrictionPkg x)
Slice-wise completeness bound.
- pointConsistency (x : MIPStarRE.LDT.Fq params) : strategy.state.ConsRel (MIPStarRE.LDT.uniformDistribution (MIPStarRE.LDT.Point params)) (xRestrictedAnswerSymStrat params strategy x).pointMeasurement.toIdxSubMeas (polynomialEvaluationFamily params (self.sliceProj x).toSubMeas) (answerSliceSelfImprovementError params restrictionPkg x)
Slice-wise consistency with the answer-valued restricted point measurement.
- strongSelfConsistency (x : MIPStarRE.LDT.Fq params) : strategy.state.BipartiteSSCRel (MIPStarRE.LDT.uniformDistribution Unit) (constSubMeasFamily (self.sliceProj x).toSubMeas) (answerSliceSelfImprovementError params restrictionPkg x)
Slice-wise strong self-consistency.
- selfCloseness (x : MIPStarRE.LDT.Fq params) : strategy.state.SDDRel (MIPStarRE.LDT.uniformDistribution Unit) (constSubMeasFamily (strategy.state.leftPlacedSubMeas (self.sliceProj x).toSubMeas)) (constSubMeasFamily (strategy.state.rightPlacedSubMeas (self.sliceProj x).toSubMeas)) (answerSliceSelfImprovementError params restrictionPkg x)
Slice-wise left/right closeness needed for the averaged self-consistency data record.
- bounded (x : MIPStarRE.LDT.Fq params) : tensorFailureExpectation strategy.state (self.sliceWitness x) (self.sliceProj x).toSubMeas β€ answerSliceSelfImprovementError params restrictionPkg x
Slice-wise boundedness residual.
- dominatesAveragePointOperator (x : MIPStarRE.LDT.Fq params) (h : MIPStarRE.LDT.Polynomial params) : IdxPolyFamily.averagedSlicePointEvaluationOperator strategy x h β€ self.sliceWitness x
Slice-wise domination of the averaged point operator.
Instances For
The slice-indexed polynomial family obtained from answer-valued restricted self-improvement outputs.
Equations
- One or more equations did not get rendered due to their size.
Instances For
The slice family of pkg.family is the improved slice family Δ^x.
The witness of pkg.family is the slice witness Z^x.
The domination target of pkg.family is the averaged slice-point evaluation operator.
Paper origin: references/ldt-paper/ld-pasting.tex:12-50
(\label{thm:ld-pasting}) and
references/ldt-paper/inductive_step.tex:239-342.
Averaged pasting inputs distilled from the per-slice self-improvement data.
This records exactly the hypotheses needed to invoke
thm:ld-pasting-in-induction-section after the slice-wise self-improvement
outputs have been averaged.
- kappa : β
Averaged completeness parameter
ΞΊ. - zeta : β
Averaged self-improvement / pasting interface parameter
ΞΆ. Averaged completeness of the slice family.
- consistent : selfPkg.family.ConsistentWithPoints strategy self.zeta
Averaged point-consistency of the slice family.
- selfConsistent : selfPkg.family.StronglySelfConsistent strategy.state self.zeta
Averaged strong self-consistency of the slice family.
- bounded : IdxPolyFamily.SliceBoundednessInput strategy selfPkg.family self.zeta
Averaged boundedness input for the pasting theorem.
- error_le : MIPStarRE.LDT.MainInductionStep.ldPastingInInductionError params k eps delta gamma self.kappa self.zeta β€ MIPStarRE.LDT.MainInductionStep.mainInductionError params.next k eps delta gamma
Error telescoping from the induction-section pasting bound to the next-stage target.