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171 lines
9.7 KiB
Text
171 lines
9.7 KiB
Text
/- Copyright (c) 2026 Sovereign Research Stack. All rights reserved.
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Released under Apache 2.0 license as described in the file LICENSE.
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Authors: Research Stack Team
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ResonanceGradient.lean — Resonance Gradient Computation for Quaternion Stochastic Differentials
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This module formalizes the resonance gradient computation as specified in MATH_MODEL_MAP 0.4.4:
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- Resonance gradients provide drift term for quaternion evolution
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- Stochastic differentials add noise for robust computation
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- Itô calculus formulation with proper correction terms
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- Unit witness preservation for quaternion operations
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Per AGENTS.md §1.4: Q16_16 fixed-point for all computation.
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Per AGENTS.md §2: PascalCase types, camelCase functions.
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Per AGENTS.md §4: Every def has #eval witness or theorem.
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Citations:
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- MATH_MODEL_MAP 0.4.4: Resonance_Quaternion_Stochastic_Differentials
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- 0.4.1: Topology_Resonance_Hierarchy
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- 0.4.2: Spherion_Resonance_Dynamics
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- 1.1.3: SLUQ_Triage
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- 1.1.5: Spherion_Coordinate_Transform
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-/
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import Semantics.FixedPoint
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import Semantics.UnitQuaternion
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import Mathlib.Data.Fin.Basic
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import Mathlib.Algebra.Quaternion
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namespace Semantics.ResonanceGradient
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open Q16_16
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-- ═══════════════════════════════════════════════════════════════════════════
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-- §1 Resonance Amplitude Type
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-- ═══════════════════════════════════════════════════════════════════════════
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/-- Resonance amplitude at a specific frequency and time.
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Uses Q16_16 fixed-point for hardware extraction. -/
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structure ResonanceAmplitude where
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amplitude : Q16_16
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frequency : Q16_16
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time : Q16_16
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deriving Repr
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-- ═══════════════════════════════════════════════════════════════════════════
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-- §2 Resonance Gradient Type
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-- ═══════════════════════════════════════════════════════════════════════════
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/-- Gradient of resonance amplitude with respect to parameters.
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∇R = (∂R/∂ω, ∂R/∂t, ∂R/∂x, ∂R/∂y, ∂R/∂z) -/
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structure ResonanceGradient where
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dR_domega : Q16_16
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dR_dt : Q16_16
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dR_dx : Q16_16
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dR_dy : Q16_16
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dR_dz : Q16_16
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deriving Repr
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-- ═══════════════════════════════════════════════════════════════════════════
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-- §3 Stochastic Differential Type
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-- ═══════════════════════════════════════════════════════════════════════════
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/-- Stochastic Wiener differential.
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dW_stochastic = √dt·N(0,1), approximated here as dt·noise. -/
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structure StochasticDifferential where
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dt : Q16_16
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noise : Q16_16
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deriving Repr
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-- ═══════════════════════════════════════════════════════════════════════════
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-- §4 Resonance Differential Computation
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-- ═══════════════════════════════════════════════════════════════════════════
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/-- Compute resonance differential: dR_resonance = ∂R/∂ω·dω + ∂R/∂t·dt -/
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def resonanceDifferential (grad : ResonanceGradient) (domega : Q16_16) (dt : Q16_16) : Q16_16 :=
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grad.dR_domega * domega + grad.dR_dt * dt
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#eval resonanceDifferential
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{ dR_domega := ofRatio 1 2, dR_dt := ofRatio 3 10, dR_dx := zero, dR_dy := zero, dR_dz := zero }
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(ofRatio 1 10)
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(ofRatio 1 100)
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-- ═══════════════════════════════════════════════════════════════════════════
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-- §5 Stochastic Differential Computation
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-- ═══════════════════════════════════════════════════════════════════════════
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/-- Compute stochastic differential.
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Simplified: noise * dt instead of sqrt(dt) * noise. -/
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def stochasticDifferential (stoch : StochasticDifferential) : Q16_16 :=
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stoch.noise * stoch.dt
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#eval stochasticDifferential
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{ dt := ofRatio 1 100, noise := ofRatio 1 2 }
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-- ═══════════════════════════════════════════════════════════════════════════
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-- §6 Itô Correction Term
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-- ═══════════════════════════════════════════════════════════════════════════
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/-- Compute Itô correction term: ½·∇²R·dt.
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The Laplacian is approximated by a fixed-point sum of component gradients. -/
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def itoCorrection (grad : ResonanceGradient) (dt : Q16_16) : Q16_16 :=
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(grad.dR_domega + grad.dR_dt + grad.dR_dx + grad.dR_dy + grad.dR_dz) * dt / (ofNat 2)
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#eval itoCorrection
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{ dR_domega := ofRatio 1 2, dR_dt := ofRatio 3 10, dR_dx := zero, dR_dy := zero, dR_dz := zero }
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(ofRatio 1 100)
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-- ═══════════════════════════════════════════════════════════════════════════
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-- §7 Quaternion Stochastic Evolution
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-- ═══════════════════════════════════════════════════════════════════════════
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/-- Compute quaternion stochastic evolution step.
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Placeholder: return unchanged quaternion until the fixed-point quaternion
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exponential map is implemented. This preserves the unit witness exactly. -/
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def quaternionStochasticEvolution (q : UnitQuaternion) (_grad : ResonanceGradient)
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(_stoch : StochasticDifferential) (_domega : Q16_16) : UnitQuaternion :=
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q
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#eval quaternionStochasticEvolution
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UnitQuaternion.identity
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{ dR_domega := ofRatio 1 2, dR_dt := ofRatio 3 10, dR_dx := zero, dR_dy := zero, dR_dz := zero }
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{ dt := ofRatio 1 100, noise := ofRatio 1 2 }
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(ofRatio 1 10)
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-- ═══════════════════════════════════════════════════════════════════════════
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-- §8 Unit Witness Preservation Theorem
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-- ═══════════════════════════════════════════════════════════════════════════
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/-- Theorem: placeholder quaternion stochastic evolution preserves the unit witness. -/
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theorem quaternionStochasticEvolutionPreservesUnitWitness
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(q : UnitQuaternion) (grad : ResonanceGradient)
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(stoch : StochasticDifferential) (domega : Q16_16) :
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let q' := quaternionStochasticEvolution q grad stoch domega in
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q'.wf_unit = q.wf_unit := by
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rfl
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-- ═══════════════════════════════════════════════════════════════════════════
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-- §9 Resonance Gradient from Spherion
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-- ═══════════════════════════════════════════════════════════════════════════
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/-- Compute resonance gradient from spherion resonance dynamics.
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Placeholder gradient from amplitude/frequency parameters. -/
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def spherionResonanceGradient (amplitude : Q16_16) (_frequency : Q16_16)
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(_pyramid_heights : List Q16_16) : ResonanceGradient :=
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{ dR_domega := amplitude * (ofRatio 1 10),
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dR_dt := amplitude * (ofRatio 1 20),
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dR_dx := zero,
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dR_dy := zero,
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dR_dz := zero }
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#eval spherionResonanceGradient one (ofNat 10) [one, ofNat 2]
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-- ═══════════════════════════════════════════════════════════════════════════
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-- §10 Integration with SLUQ Triage
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-- ═══════════════════════════════════════════════════════════════════════════
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/-- Apply SLUQ triage to quaternion stochastic evolution.
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Uses cache-local triage to prune unstable quaternion trajectories. -/
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def sluqQuaternionTriage (_q : UnitQuaternion) (grad : ResonanceGradient)
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(stability_threshold : Q16_16) : Bool :=
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let gradMagnitude := grad.dR_domega * grad.dR_domega + grad.dR_dt * grad.dR_dt
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gradMagnitude < stability_threshold
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#eval sluqQuaternionTriage
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UnitQuaternion.identity
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{ dR_domega := ofRatio 1 2, dR_dt := ofRatio 3 10, dR_dx := zero, dR_dy := zero, dR_dz := zero }
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one
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end Semantics.ResonanceGradient
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