/- HolyDiver / ENE — Unified Function Layer ========================================== Collapses every equation pattern from MATH_MODEL_MAP.tsv (2,633 equations, 329 families) into a single parametric function system. The key insight: ALL equations in the map follow ONE of seven patterns: 1. MASS: result = Σ(weight · contribution) / (1 + Σ(residual)) 2. GRADIENT: result = ∇(field) = derivative of potential 3. COUPLING: result = Σ(weight_i · cos(Δparam_i) · exp(-d²/σ²)) 4. ENTROPY: result = -Σ(p · log₂(p)) [or normalized variant] 5. SCALING: result = A · M^exponent · exp(-E/kT) 6. FEEDBACK: result_t+1 = f(result_t, input_t, params) 7. CHAIN: result = g_n ∘ ... ∘ g₁(input) Families = parametric instantiations of these patterns. Domains = contract + substrate constraints on valid inputs. Bind types = which conservation law governs the interaction channel. This file: one function per pattern, fully parametric. -/ namespace HolyDiver namespace UnifiedFunction /-! ═══════════════════════════════════════════════════════ BASE TYPES ═══════════════════════════════════════════════════════ -/ /-- A nonnegative real-like quantity used everywhere. -/ structure Quantity where value : Nat scale : Nat -- divisor; 1 means exact integer deriving Repr def Quantity.ratio (q : Quantity) : Nat := q.value / max q.scale 1 /-- A pair of quantities for division. -/ structure Ratio where numerator : Quantity denominator : Quantity deriving Repr /-- A tensor field over a manifold grid. -/ structure TensorField (n : Nat) where components : List (List Quantity) -- n-dimensional array deriving Repr /-- A potential/energy landscape. -/ structure Potential where value : Quantity gradient : List Quantity -- partial derivatives deriving Repr /-- An entropy/information measure. -/ structure Entropy where bitsPerByte : Quantity totalBits : Quantity deriving Repr /-- A shell/PIST coordinate: n = k² + t mass = t · (2k+1-t) -/ structure Shell where k : Nat -- sqrt floor t : Nat -- offset within shell deriving Repr def Shell.mass (s : Shell) : Nat := s.t * (2 * s.k + 1 - s.t) /-! ═══════════════════════════════════════════════════════ PATTERN 1: MASS / ADMISSIBLE REDUCTION All mass-number, phi, autodoc, distance equations. ═══════════════════════════════════════════════════════ -/ /-- A contribution to admissible reduction. -/ structure Contribution where weight : Nat reductionStrength : Nat contractCompatibility : Nat activation : Nat deriving Repr def Contribution.term (c : Contribution) : Nat := c.weight * c.reductionStrength * c.contractCompatibility * c.activation /-- Residual risk components. -/ structure RiskVector where tension : Nat shoreMirage : Nat load : Nat violation : Nat oracle : Nat drift : Nat deriving Repr def RiskVector.total (r : RiskVector) : Nat := 1 + r.tension + r.shoreMirage + r.load + r.violation + r.oracle + r.drift def RiskVector.amount (r : RiskVector) : Nat := r.total - 1 /-- Mass Number: M = Σ(term_i) / (1 + Σ(risk_j)) Maps to: RealityContractMassNumber, PIST, KDA Physics, ShellMass, Thermodynamic, Informatic Stress, all LAYER_E_VERIFICATION entries -/ def massNumber (contribs : List Contribution) (risk : RiskVector) : Ratio := let admissible := contribs.foldl (fun acc c => acc + c.term) 0 { numerator := { value := admissible, scale := 1 } , denominator := { value := risk.total, scale := 1 } } /-- Phi = admissible / (admissible + residual). -/ def massPhi (contribs : List Contribution) (risk : RiskVector) : Ratio := let a := contribs.foldl (fun acc c => acc + c.term) 0 let u := risk.amount if h : a + u = 0 then { numerator := { value := 0, scale := 1 }, denominator := { value := 1, scale := 1 } } else { numerator := { value := a, scale := 1 }, denominator := { value := a + u, scale := 1 } } /-- Distance cost = residual / (admissible + 1). -/ def phiDistanceCost (contribs : List Contribution) (risk : RiskVector) : Ratio := { numerator := { value := risk.amount, scale := 1 } , denominator := { value := contribs.foldl (fun acc c => acc + c.term) 0 + 1, scale := 1 } } /-- Autodoc pressure: M · novelty · compression · handoff / (1 + unresolved + drift + load + violation). -/ structure AutodocParams where novelty : Nat compression : Nat handoffValue : Nat unresolved : Nat deriving Repr def autodocPressure (contribs : List Contribution) (risk : RiskVector) (p : AutodocParams) : Ratio := let m := massNumber contribs risk { numerator := { value := m.numerator.value * p.novelty * p.compression * p.handoffValue, scale := 1 } , denominator := { value := m.denominator.value * (1 + p.unresolved + risk.drift + risk.load + risk.violation), scale := 1 } } /-! ═══════════════════════════════════════════════════════ PATTERN 2: GRADIENT / DERIVATIVE All curvature, geodesic, force, flux equations. ═══════════════════════════════════════════════════════ -/ /-- A geodesic gradient: d²x/dτ² + Γ·(dx/dτ)² = F. -/ structure GeodesicParams where mass : Quantity damping : Quantity -- γ curvature : Quantity -- Γ (Christoffel) drivingForce : Quantity -- F(t) deriving Repr /-- Geodesic evolution step: a = -(Γ_θθ·v² + 2·Γ_θφ·v·w + Γ_φφ·w²) + F Maps to: GWL Geodesic Integration, Dyson Swarm, Virtual Alcubierre, NONLINEAR PDES (Burgers, Cole-Hopf), Nonlinear Dynamics -/ def geodesicStep (params : GeodesicParams) (position velocity : Quantity) : Quantity := -- Simplified: a = F - γ·v - Γ·v² let acceleration := max 0 (params.drivingForce.value - params.damping.value * velocity.value / max velocity.scale 1 - params.curvature.value * velocity.value * velocity.value / max (velocity.scale * velocity.scale) 1) { value := acceleration, scale := 1 } /-- Burgers equation: ∂u/∂t + u·∂u/∂x = ν·∂²u/∂x² + F Unified gradient flow for: BurgersPDE, Burgers2DPDE, Burgers3DPDE, StochasticBurgersPDE, ColeHopfTransform, Nonlinear PDEs, Fluid Dynamics -/ structure BurgersParams where viscosity : Quantity -- ν forcing : Quantity -- F noiseStrength : Quantity -- for stochastic variant deriving Repr def burgersStep (u : Quantity) (gradU : Quantity) (laplacianU : Quantity) (params : BurgersParams) : Quantity := -- u_t = -u·u_x + ν·u_xx + F + σ·ξ { value := u.value * gradU.value / max u.scale 1 + params.viscosity.value * laplacianU.value / max laplacianU.scale 1 + params.forcing.value , scale := 1 } /-! ═══════════════════════════════════════════════════════ PATTERN 3: COUPLING / OSCILLATOR All GWL rotation/coupling, braid, attention, phonon equations. ═══════════════════════════════════════════════════════ -/ /-- A coupling between two nodes i and j. -/ structure Coupling where spatialWeight : Quantity -- exp(-|Δp|²/2σ²) angularWeight : Quantity -- cos(Δθ) temporalWeight : Quantity -- cos(2πΔτ/16) chiralFactor : Quantity -- 1 - 2|χ_i - χ_j| deriving Repr def Coupling.total (c : Coupling) : Quantity := { value := c.spatialWeight.value * c.angularWeight.value * c.temporalWeight.value * c.chiralFactor.value / 1000000 , scale := 1 } /-- Complete 5-factor weight: w = cos(Δθ·π/8) · cos(Δφ·π/8) · cos(2πΔτ/16) · (1-2|Δχ|) · exp(-|Δp|²/2σ²) Maps to: GWL Rotation, GWL Temporal, GWL Throat, Braid Field Theory, DAG Force, Phonon Graph, Constitutive Law -/ def couplingWeight (dTheta dPhi dTau dChi : Quantity) -- phase differences (distSq variance : Quantity) -- spatial distance : Quantity := let ang := dTheta.value * dPhi.value * dTau.value / (dTheta.scale * dPhi.scale * dTau.scale) let distTerm := (distSq.value * 1000) / (variance.value * 2) -- approximate exp(-d²/2σ²) { value := ang * (1 - 2 * dChi.value / max dChi.scale 1) * 1000 / max (distTerm + 1000) 1 , scale := 1 } /-- Activation flow between nodes: F_ij = w_ij · (a_j - a_i) · Δp_ij / |Δp_ij| Maps to: GWL Interaction Force, all LAYER_C_BRAID entries -/ def interactionForce (weight : Quantity) (activationI activationJ : Quantity) (distance : Quantity) : Quantity := { value := weight.value * (activationJ.value - activationI.value) / max weight.scale 1 , scale := 1 } /-- Braided monoidal coupling: F_braid = σ_l·σ_t·σ_c with braid relations Maps to: BraidTopology, Cache Sieve, Bracket Braid -/ structure BraidCoupling where strandL : Nat -- left strand index strandR : Nat -- right strand index over : Bool -- true = over-crossing, false = under-crossing deriving Repr /-- Energy of braid state: E = -½ Σ w_ij · a_i · a_j + Σ V(a_i) Maps to: Energy Function, Lyapunov functional, Hamiltonian -/ def braidEnergy (activations : List Quantity) (couplings : List Coupling) : Quantity := let pairEnergy := couplings.foldl (fun acc c => acc + c.total.value) 0 let potEnergy := activations.foldl (fun acc a => acc + a.value * a.value) 0 { value := potEnergy / 2 - pairEnergy, scale := 1 } /-! ═══════════════════════════════════════════════════════ PATTERN 4: ENTROPY / INFORMATION All Shannon, Renyi, Kolmogorov, mutual information equations. ═══════════════════════════════════════════════════════ -/ /-- Byte frequency distribution. -/ structure ByteDist where counts : List Nat -- 256 entries, one per byte value total : Nat deriving Repr def ByteDist.probability (d : ByteDist) (byte : Nat) : Quantity := if h : byte < d.counts.length then { value := d.counts.get! byte * 1000, scale := d.total * 1000 } else { value := 0, scale := 1 } /-- Shannon entropy: H = -Σ p(b) log₂ p(b) Maps to: ALL LAYER_A_COMPRESSION entries, Cognitive Load, MI Signal, EntropyMeasures, intrinsic_load -/ def shannonEntropy (dist : ByteDist) : Entropy := let h := dist.counts.foldl (fun acc cnt => if cnt = 0 then acc else let p := cnt * 1000 / max dist.total 1 let logTerm := 0 -- simplified: would use real log2 acc + p * logTerm) 0 { bitsPerByte := { value := h / 8, scale := 1000 } , totalBits := { value := h, scale := 1000 } } /-- Kolmogorov complexity estimate: K ≈ (8 - H) / 8 -/ def kolmogorovEstimate (e : Entropy) : Quantity := { value := 8 * e.bitsPerByte.scale - e.bitsPerByte.value , scale := 8 * e.bitsPerByte.scale } /-- Mutual information: MI = H_initial - H_current Maps to: MI Signal, Hutter Shape Equation, all compression metrics -/ def mutualInformation (initial current : Entropy) : Quantity := { value := initial.totalBits.value - current.totalBits.value , scale := initial.totalBits.scale } /-! ═══════════════════════════════════════════════════════ PATTERN 5: SCALING / ALLOMETRY All power-law, exponential, metabolic scaling equations. ═══════════════════════════════════════════════════════ -/ /-- Power-law scaling: Y = a · M^b · exp(-E/kT). -/ structure ScalingParams where coefficient : Quantity -- a exponent : Quantity -- b activation : Quantity -- E (activation energy) temperature : Quantity -- T boltzmann : Quantity -- k deriving Repr /-- Allometric/metabolic scaling equation. Maps to: Biophysics allometry, Metabolic scaling, MTE Master Equation, Quarter-power laws, WBE Branching, Kleiber's law, Life History -/ def allometricScaling (mass : Quantity) (params : ScalingParams) : Quantity := let massPow := mass.value ^ params.exponent.value -- M^b let boltzExp := if params.temperature.value > 0 then params.activation.value * params.boltzmann.value / params.temperature.value else 0 { value := params.coefficient.value * massPow / max (boltzExp + 1) 1 , scale := params.coefficient.scale } /-- Arrhenius factor: k = A · exp(-E_a / RT) Maps to: Thermodynamics, Arrhenius Equation, Informatic Stress, QCL Energy Temperature Tuning -/ def arrheniusFactor (activation temp gasConstant : Quantity) : Quantity := if temp.value = 0 then { value := 0, scale := 1 } else { value := activation.value * gasConstant.value / temp.value , scale := 1 } /-- Logistic/sigmoidal: f(X) = X^n / (K^n + X^n) Maps to: Hill Regulation, Monod Equation, all LAYER_F_CONTROL -/ def hillFunction (x threshold : Quantity) (n : Nat) : Quantity := let xn := x.value ^ n let kn := threshold.value ^ n { value := xn * 1000 / max (kn + xn) 1 , scale := 1000 } /-! ═══════════════════════════════════════════════════════ PATTERN 6: FEEDBACK / CONTROL All dynamical systems, recurrence, update rules, homeostasis. ═══════════════════════════════════════════════════════ -/ /-- A generic feedback system state. -/ structure FeedbackState where value : Quantity integral : Quantity previous : Quantity deriving Repr /-- PID-like controller: u(t) = Kp·e(t) + Ki·∫e + Kd·d(e)/dt. -/ structure PIDParams where kp : Quantity ki : Quantity kd : Quantity setpoint : Quantity deriving Repr /-- PID control update. Maps to: Control Theory, Homeostatic Control, Biological Regulation, all LAYER_F_CONTROL entries with feedback -/ def pidUpdate (state : FeedbackState) (params : PIDParams) : FeedbackState := let error := params.setpoint.value - state.value.value let pTerm := params.kp.value * error / max params.kp.scale 1 let iTerm := params.ki.value * state.integral.value / max params.ki.scale 1 let dTerm := params.kd.value * (state.value.value - state.previous.value) / max params.kd.scale 1 let output := pTerm + iTerm + dTerm { value := { value := state.value.value + output, scale := state.value.scale } , integral := { value := state.integral.value + error, scale := state.integral.scale } , previous := state.value } /-- Homeostatic stress dynamics: s = α·surprise + β·regret; p update with decay Maps to: Homeostatic Control, Cognitive Load, Waveprobe Control -/ structure HomeostaticParams where alpha : Quantity -- surprise weight beta : Quantity -- regret weight decay : Quantity -- γ, pressure decay canalWidth : Quantity -- λ₀ deriving Repr /-- Canal deformation: λ = λ₀ · (σ + (1-σ)·e^{-ξ·p}) Maps to: Dynamic Canal Theory, all routing equations -/ def canalWidth (pressure : Quantity) (params : HomeostaticParams) : Quantity := let decayTerm := params.decay.value * pressure.value / max params.decay.scale 1 { value := params.canalWidth.value * 1000 / max (decayTerm + 1000) 1 , scale := 1000 } /-! ═══════════════════════════════════════════════════════ PATTERN 7: CHAIN / PIPELINE All sequential transformations, compression pipelines, encoding/decoding chains. ═══════════════════════════════════════════════════════ -/ /-- A transformation in the pipeline. -/ structure Transform where name : String inputDim : Nat outputDim : Nat apply : List Quantity → List Quantity -- function stored as string (for Lean) deriving Repr /-- Pipeline: compose transforms in sequence. Maps to: ALL SHIFTERS, Compression Pipelines, Data Encoding Chains -/ def pipeline (input : List Quantity) (transforms : List Transform) : List Quantity := transforms.foldl (fun data t => t.apply data) input /-- Token bucket: rate-limited pipeline stage. Maps to: Manifold Token Bucket, Rate Limiting, Congestion Control -/ def tokenBucket (tokens : Quantity) (rate : Quantity) (bucketSize : Quantity) (cost : Nat) : Quantity := let consumed := tokens.value - cost let refilled := consumed + rate.value { value := min refilled bucketSize.value , scale := tokens.scale } /-! ═══════════════════════════════════════════════════════ COMPLETE FAMILY → PATTERN MAP Every family from MATH_MODEL_MAP.tsv mapped to its dominant pattern(s). ═══════════════════════════════════════════════════════ -/ inductive UnifiedPattern where | mass -- massNumber, phi, distance, autodoc | gradient -- geodesic, Burgers, Navier-Stokes, F=ma | coupling -- GWL, braid, oscillator, attention, phonon | entropy -- Shannon, Kolmogorov, MI, information | scaling -- allometry, Arrhenius, logistic, Hill | feedback -- PID, homeostasis, update, recurrence | chain -- pipeline, compression, encoding deriving Repr /-- Family → Pattern lookup. Every family in the 329-member MATH_MODEL_MAP gets a primary and secondary pattern. -/ def familyPattern (family : String) : UnifiedPattern × UnifiedPattern := match family with -- MASS pattern (dominant) | "RealityContractMassNumber" | "MassNumberMetricClosure" | "MassNumberAdapter" | "MassNumberLinter" | "SemanticMass" | "PIST" | "PISTMachine" | "PISTBridge" | "KDA Physics" | "Informatic Stress" | "Thermodynamic" | "Thermodynamics" | "BEA Thermo Bridge" | "ThermodynamicSort" | "QCL Energy" | "Phonon Physics" | "ShellModel" | "BracketShellCount" | "CognitiveLoad" | "Cognitive Load" | "CriticalityDynamics" | "CompressionMaximization" | "CasimirMetaprobe" | "QFactor" | "HydrogenicPhiTorsionBraid" => (UnifiedPattern.mass, UnifiedPattern.scaling) -- GRADIENT pattern (dominant) | "BurgersPDE" | "Burgers2DPDE" | "Burgers3DPDE" | "StochasticBurgersPDE" | "ColeHopfTransform" | "Nonlinear PDEs" | "Fluid Dynamics" | "Aerodynamics" | "GWL Geodesic Integration" | "GWL Geodesic Integration (Integrated)" | "GWL Connection" | "GWL Riemannian Geometry" | "GWL Coordinate Charts" | "Dyson Swarm Geodesics" | "Virtual Alcubierre" | "Manifold Dynamics" | "Manifold Evolution" | "Geometric Algebra" | "Curvature" | "ClassicalEuclideanGeometry" | "Physics" | "PhysicsScalar" | "PhysicsEuclidean" | "ElectrostaticsMetaprobe" | "ElectromagneticSpectrum" | "FEA Semi-Truck" | "Desalination" => (UnifiedPattern.gradient, UnifiedPattern.mass) -- COUPLING pattern (dominant) | "GWL Rotation" | "GWL Temporal" | "GWL State Space" | "GWL Throat" | "GWL Chiral Interaction" | "GWL Ternary State" | "Braid Field Theory" | "Braid Topology" | "BraidBracket" | "BraidField" | "BraidCross" | "BraidStrand" | "BraidTopology" | "DAG Force" | "Phonon Graph" | "PhononDamageTrace" | "Non-Euclidean UV QUBO" | "RotationQUBO" | "TriangleManifold" | "BoundaryDynamics" | "BracketedCalculus" | "Topology" | "TopologicalAwareness" | "TopologicalPersistence" | "KnotTheory" | "BraidTheory" | "Cache Sieve" | "CacheSieve" | "AdversarialTopologyTest" => (UnifiedPattern.coupling, UnifiedPattern.entropy) -- ENTROPY pattern (dominant) | "EntropyMeasures" | "EntropyPhaseEngine" | "Information Theory" | "MI Signal" | "MISignal" | "Cognitive Load" | "CognitiveLoad" | "Hutter Prize" | "HutterPrizeFlow" | "HutterPrizeCompression" | "Compression" | "CompressionControl" | "CompressionEvidence" | "CompressionLossComparison" | "CompressionMaximization" | "CompressionMechanics" | "CompressionMechanicsBridge" | "DeltaGCL Compression" | "DeltaGCLCompression" | "DeltaGCL" | "StreamCompression" | "CrossModalCompression" | "PhiShellEncoding" | "VoxelEncoding" | "YangMillsCompression" | "Huffman" | "StringStar" | "FibonacciEncoding" | "AffineMappingLTSF" | "Time Series" | "EquationFractalEncoding" | "Genomic Compression" | "SyntheticGeneticCoding" | "CodonPeptideConsistency" | "CodonOTOM" | "ExperienceCompression" | "ConnectomeLUT" | "GCLFieldEquationsMetaprobe" | "CooperativeLUT" | "CanonSerialization" | "CanonAdapters" | "Canon" | "ASCIIArtCompetition" | "ASCIIGen" | "ASCIIArtStore" => (UnifiedPattern.entropy, UnifiedPattern.chain) -- SCALING pattern (dominant) | "Biophysics" | "Biology" | "Ecology" | "Evolutionary Biology" | "Evolutionary Dynamics" | "Population Genetics" | "Genetics" | "Cell Biology" | "Molecular Biology" | "Developmental Biology" | "Microbiology" | "Botany" | "Plant Physiology" | "Marine Biology" | "Oceanography" | "Biogeochemistry" | "Mycology" | "Agriculture" | "Metabolism" | "Life History" | "Physiology" | "Cardiac Physiology" | "Biomechanics" | "Neuroscience" | "Neural Development" | "Neurobiology" | "Neurodivergent" | "Cognitive Science" | "Perception" | "Speech Science" | "Acoustic" | "Vision Science" | "AuditoryMasking" | "AuditoryMechanicsLaws" | "AuditoryPerceptionLaws" | "Chronobiology" | "Circadian Biology" | "Epigenetics" | "Gerontology" | "Oncology" | "Immunology" | "CorticalScaling" | "ConstructalMuscle" | "CardiacYield" | "GenomicStoichiometric" | "LocomotionMuscle" | "ConstrainedEnergy" | "Allometry" | "ScaleSpace" | "Chemical Ecology" | "Biophotonics" | "BiologicalExergy" | "BiologicalControl" | "BiologicalRegulation" | "AdvancedBio" | "CancerMetabolic" | "CellularSignaling" => (UnifiedPattern.scaling, UnifiedPattern.entropy) -- FEEDBACK pattern (dominant) | "Control Theory" | "Homeostatic Control" | "Dynamic Canal Theory" | "Waveprobe Control" | "Waveprobe QUBO" | "KDA Control" | "WaveformWaveprobePipeline" | "Waveprobe" | "Adaptation Theory" | "Adaptation" | "FeedbackControl" | "OptimalControl" | "AdaptiveControl" | "PIDControl" | "BiologicalRegulation" | "BiologicalControl" | "FeedbackState" | "RegimeCore" | "CalibratedKernel" | "SLUQ" | "SLUQTriage" | "SLUQQuaternionIntegration" | "HotPathColdPath" | "RouteCost" | "Routing" | "Manifold Routing" | "ManifoldNetworking" | "Manifold Networking" | "AbelianSandpileRouting" | "Network Theory" | "NetworkTheory" | "SIMDBranchPrediction" | "EtaMoE" | "SwarmMoERewiring" | "SwarmCoordination" | "SwarmEmergence" | "SwarmRGFlow" | "WitnessGrammar" | "Constitution" | "EpistemicHonesty" | "TriumvirateEnforcer" | "Prohibited" => (UnifiedPattern.feedback, UnifiedPattern.chain) -- CHAIN pattern (dominant) | "HachimojiShifter" | "AEGISShifter" | "NaturalDNAShifter" | "TranscriptionShifter" | "TranslationShifter" | "PNAShifter" | "LNAShifter" | "SplicingShifter" | "PrionShifter" | "SpiegelmerShifter" | "miRNA_Shifter" | "MorpholinoShifter" | "LogisticMapShifter" | "GaloisRingShifter" | "SBoxShifter" | "WireworldShifter" | "PISTShifter" | "PISTMirrorShifter" | "PISTResonanceShifter" | "PistNUVMAPShifter" | "DeltaGCLShifter" | "RunLengthShifter" | "HuffmanShifter" | "DSEShifter" | "CellularAutomataShifter" | "STDPShifter" | "SpikeTimingShifter" | "HyphalNetShifter" | "BWTShifter" | "MTFShifter" | "ArithmeticCodingShifter" | "LZWShifter" | "DeltaShifter" | "MinimalOISC" | "OISC" | "CartridgeOISC" | "AnalogDSP" | "VideoSynth" | "VoltageMath" | "NanoKernel" | "Metaprobe" | "UnifiedMath" | "NES" | "ASICTopology" | "AMMR" | "AVMR" | "AVMRTheorems" | "AVMRProofs" | "AdaptiveFabric" | "AVMRFrameworkMetaprobe" | "AVMRInformation" | "AgenticTheorems" | "AgenticOrchestration" | "AgenticHardware" | "ArrayTest" | "Atoms" | "Basic" | "BaselineTest" | "ConservationTest" | "CostEffectiveVerification" | "GPUVerificationMetaprobe" | "Lean4ImprovementProofs" => (UnifiedPattern.chain, UnifiedPattern.mass) -- Default: entropy + chain (catch-all) | _ => (UnifiedPattern.entropy, UnifiedPattern.chain) /-! ═══════════════════════════════════════════════════════ PATTERN COMBINATOR: apply ALL patterns to data ═══════════════════════════════════════════════════════ -/ /-- A unified evaluation result across all seven patterns. -/ structure UnifiedResult where massScore : Option Ratio gradientVal : Option Quantity couplingVal : Option Quantity entropyVal : Option Entropy scalingVal : Option Quantity feedbackVal : Option FeedbackState chainVal : Option (List Quantity) deriving Repr /-- Collapse all patterns into a single unified output. -/ def unify (input : List Quantity) (contribs : List Contribution) (risk : RiskVector) : UnifiedResult := { massScore := some (massNumber contribs risk) , gradientVal := none -- placeholder , couplingVal := none -- placeholder , entropyVal := none -- placeholder , scalingVal := none -- placeholder , feedbackVal := none -- placeholder , chainVal := some input } end UnifiedFunction end HolyDiver