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Unary records determine every frozen cross entry

Lax342547.FrozenRecords · concepts/Lax342547/FrozenRecords.lean · lax-342547

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    Natural Language Statement

    Lemma

    Pairings of nominal columns with already fixed frozen image vectors require only nominal dimension times frozen-vector count bits. Separate unary records determine all cross entries with a frozen factor.

    Concept map
    80 concepts
    100%
    Exact-image bounds for independent affinecolumnsOrdered atom products in the actualgradient formPoint atoms and finite flavor distributionsSparse unselected primal vectors in barredspaces lie in the pinsBarred response spaces and the actualobstruction rank budgetThe exact space of binary base momentsRank control for the frozen baseline onprimal inputsFormal ordered product bits realizesymmetric correctionsBounded allowed derivatives preserving theactual linearized responseAllowed channel changes and the actual tableinjection testsConcrete cut-space testers and the orderedmixer formConcrete coordinates, quadratic testers, andthe self-Gram formNumerical recipes prescribe the concretegradients on witness atomsThe affine minus-column law at a fixed plusframeCut profiles and the constant kernelThe full linearized response on pairs ofactual cut profilesFull response obstructions are effectiveprofiles plus selected atomsExact image pins in nominal coefficientspacesFinite linear images and their uniform-lawdensity boundsAmbient symmetries and frame marginalsFresh key directions are independent modulotable spacesBaseline bilinear extensions retaining allfrozen rows and columnsExact agreement of zero quotient charactersUnary records determine every frozen crossentryBaseline contractions on the selected atomsThe symmetric binary gradient formGram-conditioned columns and theirrank-failure probabilityTwo-sided Gram normalization forindividually injective framesThe binary hole relationPaying the reference-image conditioning anddimension costsUniform injective frames and channeltranspose failureFresh point-ray spans are disjoint from thenominal table spacesLow-rank Boolean moments have boundedlabel supportTriangle relations separate into individuallabel blocksBoolean point moments with restricted basecoordinatesThe 3K+28 baseline bound in the actualnominal coordinatesPrimal blocks of the nominal spaces andtheir bounded table partEndpoint projections of paired pure-responseannihilatorsActual paired-witness key spaces satisfy thebaseline hypothesesBinary prescriptions at all endpoints of apaired scalar recipeFull paired witness lists and scalar recipeequationsSparse pin exclusions with arbitrary basecoefficientsSparse residual contractions belong to theactual primal pinsRetractions with bounded rank on theprimal inputsExact images mixing independent injectiveframesJoint minus images after exposing severalplus framesPrimal projections and preservation ofeffective spacesPure obstructions on the actual pair of cutprofilesExtracting fresh label coefficients throughpin quotientsRank of a tensor killed in two quotientspacesRank-controlled pure forms on the actualbarred quotientsBounded baselines for both actual crossorientationsActual frame observations realize thenominal channel contractionsRaw matrix frames and their tensorrealizationThe finite uniform raw-vertex lawGradient residuals vanish on effective profilesand selected atomsCoupled scalar recipes give consistent atomgradientsJoint reference image caps across both signsand all drawsThe full reference cap for exact pin eventsRemoving selected atoms leaves onlyunselected component labelsThe bounded pure remainder of an actualscalar recipeMatrix representations and the boundedresidual rank ingredientsUnrestricted linearized solutions for actualscalar recipesRank loss under restriction of a bilinear formSelected tensor blocks of actual pureobstructionsA selected affine ray determines its momentblockSubtracting selected atoms preserves pureannihilationSelected label coefficients agree across thecut profileInterpolation of finitely many binary selectorlabelsNumerical cross tables, injection flags, andunary admissibilityUnselected sparse vectors cannot concealfresh key coefficientsA uniform label budget for all sparse pinvectorsConsistent symmetric binary prescriptions ontwo witness listsTable contractions on effective profiles andtheir full extensionsTable coordinates and private channelcomplementsMajority intersections in the cyclic taggeometryPure bilinear responses detect quotienttensorsQuotient extractors isolate individual tensorlabel blocksWell-defined channel contractions onprojected tensor spacesWitness atoms and their numerical testerrecords
    Proven claimDefinitionThis conceptRelated conceptA → B: B builds on ADescendants are omitted for concepts with more than 10 descendants.
    Evidence

    This concept declares 4 statements. Each proof establishes one of them relative to its assumptions.

    1 record_count proven

    2 record_evaluation proven

    3 records_determine_frozen proven

    4 two_records_cross_agreement proven

    Lean source view on GitHub

    1import Lax342547.FrozenCharacters
    2import Lax342547.RawFrames
    3
    4/-!
    5---
    6title: Unary records determine every frozen cross entry
    7type: lemma
    8---
    9Pairings of nominal columns with already fixed frozen image vectors require only nominal dimension times frozen-vector count bits. Separate unary records determine all cross entries with a frozen factor.
    10-/
    11
    12namespace Lax342547.FrozenRecords
    13
    14open Lax342547.MomentSpace Lax342547.ConcreteGeometry
    15
    16noncomputable def record {I X N : Type} [Fintype N]
    17 (A : (I → Binary) →ₗ[Binary] (N → Binary)) (frozen : X → N → Binary) : Matrix I X Binary := by
    18 classical
    19 exact fun i x => dotProduct (A (Pi.single i 1)) (frozen x)
    20
    21axiom record_count {I X : Type} [Fintype I] [Fintype X] : by
    22 classical
    23 exact Fintype.card (Matrix I X Binary) = 2 ^ (Fintype.card I * Fintype.card X)
    24
    25axiom record_evaluation {I X N : Type} [Fintype I] [Fintype N]
    26 (A : (I → Binary) →ₗ[Binary] (N → Binary)) (frozen : X → N → Binary)
    27 (v : I → Binary) (x : X) :
    28 dotProduct (A v) (frozen x) = ∑ i, v i * record A frozen i x
    29
    30axiom records_determine_frozen {I X N : Type} [Fintype I] [Fintype N]
    31 (A A' : (I → Binary) →ₗ[Binary] (N → Binary)) (frozen : X → N → Binary)
    32 (hrec : record A frozen = record A' frozen) (v : I → Binary)
    33 (w : Submodule.span Binary (Set.range frozen)) :
    34 dotProduct (A v) w.val = dotProduct (A' v) w.val
    35
    36axiom two_records_cross_agreement {I J X Y N : Type}
    37 [Fintype I] [Fintype J] [Fintype N]
    38 (A A' : (I → Binary) →ₗ[Binary] (N → Binary))
    39 (B B' : (J → Binary) →ₗ[Binary] (N → Binary))
    40 (left : X → I → Binary) (right : Y → J → Binary)
    41 (leftImages : X → N → Binary) (rightImages : Y → N → Binary)
    42 (hleft : ∀ x, A (left x) = leftImages x ∧ A' (left x) = leftImages x)
    43 (hright : ∀ y, B (right y) = rightImages y ∧ B' (right y) = rightImages y)
    44 (hrecA : record A rightImages = record A' rightImages)
    45 (hrecB : record B leftImages = record B' leftImages) :
    46 (∀ v ∈ Submodule.span Binary (Set.range left), ∀ w,
    47 dotProduct (A v) (B w) = dotProduct (A' v) (B' w)) ∧
    48 (∀ v w, w ∈ Submodule.span Binary (Set.range right) →
    49 dotProduct (A v) (B w) = dotProduct (A' v) (B' w))
    50
    51end Lax342547.FrozenRecords
    52
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