Research-Stack/0-Core-Formalism/lean/Semantics/Semantics/ResonanceGradient.lean

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