AutoSamplingTheory.SALD.cycle176GeneralMovingTargetDiscreteEmGeneratorLaplacianEventFieldFrozenScalarBrownianItoVarianceOneLower1Obligation
Data definition / provenance and workflow record
Meaning and type
The result has data type AutoSamplingTheory.ProofObligation. A value of this type stores descriptions; it is not a proof of the statements in those descriptions.
Lean statement of this data definition
The part after the colon is the output data type. This declaration takes no mathematical proof inputs.
def cycle176GeneralMovingTargetDiscreteEmGeneratorLaplacianEventFieldFrozenScalarBrownianItoVarianceOneLower1Obligation :
ProofObligationConstruction and field-by-field explanation
Construct a data record from explicit fields and the audited defaults shown below.
This Lean definition constructs provenance or workflow data. It does not prove the mathematical statements stored as text. Status labels, named dependencies and citations are data, not compilation, proof or source certificates.
id:String(explicit)Stable obligation identifier.
sald.general_moving_target_discrete.cycle176_em_generator_laplacian_event_field_frozen_scalar_brownian_ito_variance_one_lower1statement:String(explicit)Desired mathematical or workflow content as String; it is not a proposition in Prop and the def does not prove it.
Cycle 176 lower_1 dynamic-leaf proof-scout packet. Classification: narrows-source-cited-boundary. Exact missing theorem boundary narrowed: the downstream hVarianceOne : testRegular -> forall phi x i, (variance phi x i : Real) = 1 should be discharged only from the smaller source-facing normalized Brownian variance definition hNormalizedVarianceDef : testRegular -> forall phi x i, variance phi x i = (1 : NNReal). Source route: appendix.tex:958-970 states xi_k iid N(0,I_d) in the EM step; appendix.tex:984-995 gives the frozen interpolation Brownian increment sigma_eta*(W_s-W_{s_k}); appendix.tex:1170-1176 rewrites the increment as sigma_eta(t(s))*sqrt(s-s_k)*xi with xi ~ N(0,I); appendix.tex:1379-1387 keeps sigma_eta^2/2 outside the Brownian event field. Thus the local variance field for the normalized scalar Brownian coordinate is the unit NNReal variance before the external diffusion coefficient is applied. Lower_2-ready theorem shape: selectedWeakTestVarianceOneOfNormalizedBrownianVarianceDef (variance : Test -> E -> Fin (Module.finrank Real E) -> NNReal) (testRegular : Prop) (hNormalizedVarianceDef : testRegular -> forall phi x i, variance phi x i = (1 : NNReal)) : testRegular -> forall phi x i, (variance phi x i : Real) = 1. Proof route: intro htests phi x i; rewrite by hNormalizedVarianceDef htests phi x i; close the coercion of (1 : NNReal) to Real by norm_num. This does not derive hNormalizedVarianceDef itself, move sigma_eta^2/2 into the event field, reintroduce selected weak-test Hessian wrappers, or use VP score-Hessian regularity.source:AutoSamplingTheory.SourceAnchor(explicit)SourceAnchor supporting the intended requirement.
AutoSamplingTheory.SALD.saldGeneralMovingTargetDiscreteWeakFpSource— audited data reference, not expanded and not a compiled dependency edgestatus:AutoSamplingTheory.ProofStatus(explicit)Stored ProofStatus, default obligation; even an explicitly stored formalized does not independently certify a Lean theorem.
AutoSamplingTheory.ProofStatus.obligation— stored label only; no proof certificationdependsOn:List String(explicit)List of declared dependency names as strings; may mix theorem names, obligations, source labels, or descriptions. Not the compiled dependency DAG.
Ordered data items
- SALD.cycle176GeneralMovingTargetDiscreteEmGeneratorLaplacianEventFieldFrozenScalarBrownianItoVarianceOneMiddleObligation
- SALD.selectedWeakTestVarianceOneOfNormalizedBrownianVarianceDef
- SALD.selectedWeakTestQuadraticVariationNormalizationOfCoeffDefAndVarianceOne
- hVarianceOne
- hNormalizedVarianceDef
- hSecondTaylorCoeffDef
- hSourceHasHessian
- hSourceHessianBound
- hSecondCoeff
- hFrozenScalarBrownianItoTaylorMomentDecomposition
- hFrozenScalarBrownianItoNormalizedTaylorRemainderVanishes
- hFrozenScalarBrownianItoEventFieldCoordinateSum
- eq:SALD_general_EM
- eq:general_moving_target_SALD_frozen_interp
- eq:increment_basic_bound_revised
- appendix.tex:958-970
- appendix.tex:984-995
- appendix.tex:1170-1176
- appendix.tex:1379-1387
- paper-wide original-source search excluding sald_version_2.tex
- sald.general_moving_target_discrete.em_interpolation_fp
note:String(explicit)Recorded evidence/caveats; may distinguish a compiled scalar helper from still-open source analysis.
No local SLT theorem was consulted or imported. Mathlib/local input needed by lower_2 is only the existing NNReal-to-Real coercion simplification by norm_num after rewriting by hNormalizedVarianceDef. The remaining source-facing stochastic work is hNormalizedVarianceDef from xi ~ N(0,I).
Exact Lean data construction
Each field assignment stores the corresponding value shown above. Omitted fields use the explicitly identified schema defaults. Strings that name theorems remain strings; they do not call those theorems.
def cycle176GeneralMovingTargetDiscreteEmGeneratorLaplacianEventFieldFrozenScalarBrownianItoVarianceOneLower1Obligation :
ProofObligation where
id := "sald.general_moving_target_discrete.cycle176_em_generator_laplacian_event_field_frozen_scalar_brownian_ito_variance_one_lower1"
statement := "Cycle 176 lower_1 dynamic-leaf proof-scout packet. Classification: narrows-source-cited-boundary. Exact missing theorem boundary narrowed: the downstream hVarianceOne : testRegular -> forall phi x i, (variance phi x i : Real) = 1 should be discharged only from the smaller source-facing normalized Brownian variance definition hNormalizedVarianceDef : testRegular -> forall phi x i, variance phi x i = (1 : NNReal). Source route: appendix.tex:958-970 states xi_k iid N(0,I_d) in the EM step; appendix.tex:984-995 gives the frozen interpolation Brownian increment sigma_eta*(W_s-W_{s_k}); appendix.tex:1170-1176 rewrites the increment as sigma_eta(t(s))*sqrt(s-s_k)*xi with xi ~ N(0,I); appendix.tex:1379-1387 keeps sigma_eta^2/2 outside the Brownian event field. Thus the local variance field for the normalized scalar Brownian coordinate is the unit NNReal variance before the external diffusion coefficient is applied. Lower_2-ready theorem shape: selectedWeakTestVarianceOneOfNormalizedBrownianVarianceDef (variance : Test -> E -> Fin (Module.finrank Real E) -> NNReal) (testRegular : Prop) (hNormalizedVarianceDef : testRegular -> forall phi x i, variance phi x i = (1 : NNReal)) : testRegular -> forall phi x i, (variance phi x i : Real) = 1. Proof route: intro htests phi x i; rewrite by hNormalizedVarianceDef htests phi x i; close the coercion of (1 : NNReal) to Real by norm_num. This does not derive hNormalizedVarianceDef itself, move sigma_eta^2/2 into the event field, reintroduce selected weak-test Hessian wrappers, or use VP score-Hessian regularity."
source := saldGeneralMovingTargetDiscreteWeakFpSource
status := ProofStatus.obligation
dependsOn := [
"SALD.cycle176GeneralMovingTargetDiscreteEmGeneratorLaplacianEventFieldFrozenScalarBrownianItoVarianceOneMiddleObligation",
"SALD.selectedWeakTestVarianceOneOfNormalizedBrownianVarianceDef",
"SALD.selectedWeakTestQuadraticVariationNormalizationOfCoeffDefAndVarianceOne",
"hVarianceOne",
"hNormalizedVarianceDef",
"hSecondTaylorCoeffDef",
"hSourceHasHessian",
"hSourceHessianBound",
"hSecondCoeff",
"hFrozenScalarBrownianItoTaylorMomentDecomposition",
"hFrozenScalarBrownianItoNormalizedTaylorRemainderVanishes",
"hFrozenScalarBrownianItoEventFieldCoordinateSum",
"eq:SALD_general_EM",
"eq:general_moving_target_SALD_frozen_interp",
"eq:increment_basic_bound_revised",
"appendix.tex:958-970",
"appendix.tex:984-995",
"appendix.tex:1170-1176",
"appendix.tex:1379-1387",
"paper-wide original-source search excluding sald_version_2.tex",
"sald.general_moving_target_discrete.em_interpolation_fp"
]
note := "No local SLT theorem was consulted or imported. Mathlib/local input needed by lower_2 is only the existing NNReal-to-Real coercion simplification by norm_num after rewriting by hNormalizedVarianceDef. The remaining source-facing stochastic work is hNormalizedVarianceDef from xi ~ N(0,I)."
/-- Cycle-176 lower_2 compiled bridge through the normalized variance field.
The direct variance-one theorem was already available when lower_2 arrived, so
this packet composes it with the cycle-175 second-Taylor coefficient bridge.
The older `hQuadraticCoeffDef`/`hVarianceOne` pair is replaced by the smaller
source-facing `hSecondTaylorCoeffDef`/`hNormalizedVarianceDef` pair for the
quadratic-variation normalization step.
-/Existing module entry · Audited data-reader index · All teaching coverage