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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
SSMS.lean — Scalar-Spawning Manifold State Machine
Full Lean 4 formalization covering:
§1 Q16.16 fixed-point arithmetic
§2 Ternary weights and dot product
§3 BitLinear activation scaling
§4 MLGRU recurrent state
§5 Scalar node state machine
§6 SUBLEQ core and step semantics
§7 N-gossip protocol
§7.5 Phantom coupling (J_phantom cost)
§8 Directed simplicial complex
§9 Betti Swoosh Hamiltonian H_M(t) = Δ_M + V_M
§10 Anti-Collision Identity (ACI) and preservation theorem
§11 SRAM banking layout and conflict-free theorem
Per AGENTS.md §1.4: All new hot-path code uses Q16_16 fixed-point.
Per AGENTS.md §2: All code uses PascalCase for types, camelCase for functions.
-/
import Std
import Mathlib.Tactic.NormNum
import Semantics.Timing
namespace Semantics.SSMS
-- ════════════════════════════════════════════════════════════
-- §1 Q16.16 Fixed-Point Arithmetic
-- raw : Int represents the 32-bit two's-complement word.
-- Real value = raw / 65536. Resolution = 2^{-16}.
-- ════════════════════════════════════════════════════════════
/-- Q16.16: 32-bit fixed-point. Invariant (unenforced):
raw ∈ [-2^31, 2^31 - 1]. -/
structure Q1616 where
raw : Int
deriving Repr, DecidableEq, Inhabited, BEq
namespace Q1616
def zero : Q1616 := ⟨0⟩
def one : Q1616 := ⟨65536⟩ -- 0x00010000
def negOne : Q1616 := ⟨-65536⟩ -- 0xFFFF0000
def two : Q1616 := ⟨131072⟩ -- 0x00020000
def epsilon : Q1616 := ⟨1⟩ -- 2^{-16}, smallest positive
/-- Convert Nat to Q16.16 (left-shift by 16). -/
def ofNat (n : Nat) : Q1616 := ⟨n * 65536⟩
/-- SUBLEQ native operation: M[b] ← M[b] M[a].
Exact for all Q16.16 values (subtraction = integer subtraction). -/
def subleqOp (a b : Q1616) : Q1616 := ⟨b.raw - a.raw⟩
/-- Addition via double-negation SUBLEQ trick (2 instructions). -/
def add (a b : Q1616) : Q1616 := ⟨a.raw + b.raw⟩
/-- Subtraction: result = b a (matches SUBLEQ M[b] ← M[b] M[a]). -/
def sub (a b : Q1616) : Q1616 := ⟨b.raw - a.raw⟩
def neg (a : Q1616) : Q1616 := ⟨-a.raw⟩
def abs (a : Q1616) : Q1616 := if a.raw < 0 then ⟨-a.raw⟩ else a
/-- Fixed-point multiply: (a.raw × b.raw) >> 16.
Requires 64-bit intermediate; routed through MUL co-processor
at memory-mapped ports M[-8], M[-9], M[-10]. -/
def mul (a b : Q1616) : Q1616 := ⟨(a.raw * b.raw) / 65536⟩
def le (a b : Q1616) : Prop := a.raw ≤ b.raw
def lt (a b : Q1616) : Prop := a.raw < b.raw
/-- Clip x to [lo, hi] — two SUBLEQ CMP sequences (8 instructions). -/
def clip (x lo hi : Q1616) : Q1616 :=
if x.raw < lo.raw then lo
else if x.raw > hi.raw then hi
else x
-- ── Newton-Raphson reciprocal ──────────────────────────────
/-- Seed table: 1/k for k = 0..15 scaled to Q16.16.
Indexed by the top 4 bits of |x| (leading nibble of integer part). -/
def nrSeedTable : Array Int :=
#[65536, 65536, 32768, 21845, 16384, 13107, 10923,
9362, 8192, 7282, 6554, 5958, 5461, 5041, 4681, 4369]
def nrSeed (x : Q1616) : Q1616 :=
let idx := (x.raw.toNat >>> 28) &&& 0xF
⟨nrSeedTable.getD idx 65536⟩
/-- One Newton-Raphson iteration: r ← r · (2 x · r).
Uses 2 MUL co-processor calls. -/
def nrIter (x r : Q1616) : Q1616 :=
mul r (sub (mul x r) two)
/-- Reciprocal to Q16.16 precision via 3 NR iterations (~30 SUBLEQ total). -/
def recip (x : Q1616) : Q1616 :=
let ax := abs x
let r := (nrIter ax ∘ nrIter ax ∘ nrIter ax) (nrSeed ax)
if x.raw < 0 then neg r else r
instance : Add Q1616 where add := add
instance : Sub Q1616 where sub := fun a b => ⟨a.raw - b.raw⟩
instance : Neg Q1616 where neg := neg
instance : Mul Q1616 where mul := mul
def max (a b : Q1616) : Q1616 := if a.raw ≥ b.raw then a else b
def min (a b : Q1616) : Q1616 := if a.raw ≤ b.raw then a else b
end Q1616
-- ════════════════════════════════════════════════════════════
-- §2 Ternary Weights
-- w̃ ∈ {1, 0, +1} stored as 2-bit codes, 16 per 32-bit word.
-- Dot product: only ADD/SUB, no MUL co-processor.
-- ════════════════════════════════════════════════════════════
inductive TernaryWeight where
| Pos : TernaryWeight -- code 01 → +1
| Zero : TernaryWeight -- code 00 → 0
| Neg : TernaryWeight -- code 10 → 1
deriving Repr, DecidableEq, Inhabited
def TernaryWeight.toQ : TernaryWeight → Q1616
| .Pos => Q1616.one
| .Zero => Q1616.zero
| .Neg => Q1616.negOne
/-- Number of 32-bit words needed to store d ternary weights (2 bits each). -/
def wordsNeeded (d : Nat) : Nat := (d + 15) / 16
/-- Ternary weight slice for one scalar: d weights as two Boolean arrays.
Disjoint invariant: no weight can be simultaneously +1 and 1. -/
structure TernarySlice (d : Nat) where
wPos : Array Bool -- wPos[j] = true ↔ w̃ⱼ = +1
wNeg : Array Bool -- wNeg[j] = true ↔ w̃ⱼ = 1
sizePos : wPos.size = d
sizeNeg : wNeg.size = d
disjoint : ∀ j : Fin d,
¬ (wPos[j]'(sizePos ▸ j.isLt) ∧ wNeg[j]'(sizeNeg ▸ j.isLt))
/-- Ternary dot product: Σⱼ w̃ⱼ · xⱼ.
Weight=+1 → ADD xⱼ (2 SUBLEQ).
Weight=1 → SUB xⱼ (1 SUBLEQ).
Weight= 0 → NOP.
No MUL co-processor calls. -/
def TernarySlice.dot {d : Nat} (ws : TernarySlice d) (xs : Fin d → Q1616) : Q1616 :=
(List.range d).foldl (fun acc j =>
if hj : j < d then
let _p := ws.wPos.getD j false
let n := ws.wNeg.getD j false
let x := xs ⟨j, hj⟩
Q1616.add acc (if _p then x else if n then Q1616.neg x else Q1616.zero)
else acc
) Q1616.zero
/-- Memory compression ratio: 2 bits/weight vs 32-bit Q16.16. -/
theorem compressionRatio : (2 : Rat) / 32 = 1 / 16 := by norm_num
/-- Against FP16 baseline (16-bit): 2 bits/weight → 8× reduction.
With activation savings: total ≈ 0.1× M_FP16. -/
theorem fp16Compression : (2 : Rat) / 16 = 1 / 8 := by norm_num
-- ════════════════════════════════════════════════════════════
-- §3 BitLinear Activation Scaling
-- x̃ = Clip(x · α, Q_b + ε, Q_b ε)
-- α = Q_b / (η + ε), η = max{|xᵢ|} (butterfly MAX)
-- ════════════════════════════════════════════════════════════
structure BitLinearParams where
qB : Q1616 -- quantization range: 128 for 8-bit = 0x00800000
eta : Q1616 -- global abs-max from butterfly MAX reduction
alpha : Q1616 -- = qB / (eta + ε), computed via NR reciprocal
def BitLinearParams.compute (qB eta : Q1616) : BitLinearParams :=
{ qB
eta
alpha := Q1616.mul qB (Q1616.recip (Q1616.add eta Q1616.epsilon)) }
/-- Scale activation and clip to quantization range. -/
def bitLinearScale (p : BitLinearParams) (x : Q1616) : Q1616 :=
Q1616.clip
(Q1616.mul x p.alpha)
(Q1616.add (Q1616.neg p.qB) Q1616.epsilon)
(Q1616.sub Q1616.epsilon p.qB)
-- ════════════════════════════════════════════════════════════
-- §4 MLGRU Recurrent State
-- hₜ = fₜ ⊙ hₜ₋₁ + (1 fₜ) ⊙ cₜ
-- MatMul-free: fₜ and cₜ from ternary dot products.
-- Only 2 MUL co-processor calls for the gating blends.
-- ════════════════════════════════════════════════════════════
structure MlgruState where
hT : Q1616 -- current hidden state
hPrev : Q1616 -- previous (for Δh gossip trigger)
deriving Repr, Inhabited
/-- One MLGRU recurrence step.
fT: forget gate (from ternary dot product, Q16.16).
cT: candidate state (from ternary dot product, Q16.16). -/
def mlgruStep (fT cT : Q1616) (st : MlgruState) : MlgruState :=
let termA := Q1616.mul fT st.hT -- fT · h_{t-1}
let oneMf := Q1616.sub fT Q1616.one -- 1 fT
let termB := Q1616.mul oneMf cT -- (1 fT) · cT
{ hT := Q1616.add termA termB, hPrev := st.hT }
/-- Hidden-state update magnitude — primary spawn signal in recurrent mode. -/
def MlgruState.delta (st : MlgruState) : Q1616 :=
Q1616.abs (Q1616.sub st.hPrev st.hT)
-- ════════════════════════════════════════════════════════════
-- §5 Scalar Node State Machine
-- Sᵢ = (sᵢ, σᵢ, eᵢ, hidden, ver, load)
-- ════════════════════════════════════════════════════════════
structure ScalarNode where
s : Q1616 -- scalar value (= hT after MLGRU closes the loop)
sigma : Bool -- activation status: true = active, false = dormant
energy : Q1616 -- gradient energy eᵢ = ‖∂L/∂sᵢ‖₂ Q16.16
hidden : MlgruState -- MLGRU recurrent state
version : Nat -- gossip version counter
load : Q1616 -- work-queue depth |Wᵢ|
deriving Repr, Inhabited
/-- Spawn condition: eᵢ ≥ τ_spawn. -/
def ScalarNode.shouldSpawn (nd : ScalarNode) (τ : Q1616) : Bool :=
decide (τ.raw ≤ nd.energy.raw)
/-- Fold condition: eᵢ ≤ τ_fold. -/
def ScalarNode.shouldFold (nd : ScalarNode) (τ : Q1616) : Bool :=
decide (nd.energy.raw ≤ τ.raw)
/-- Transition with hysteresis (prevents oscillation at threshold).
Spawn wins over fold when both conditions hold. -/
def ScalarNode.transition (nd : ScalarNode) (τSpawn τFold : Q1616) : Bool :=
if nd.shouldSpawn τSpawn then true
else if nd.shouldFold τFold then false
else nd.sigma
/-- Current rank: number of active scalars in pool. -/
def poolRank (nodes : Array ScalarNode) : Nat :=
nodes.foldl (fun acc nd => if nd.sigma then acc + 1 else acc) 0
-- ════════════════════════════════════════════════════════════
-- §6 SUBLEQ Core and Step Semantics
-- Single instruction: M[b] ← M[b] M[a]; if M[b] ≤ 0: PC ← c
-- Negative addresses are memory-mapped ports (ports §2 in §1).
-- ════════════════════════════════════════════════════════════
/-- One SUBLEQ instruction. -/
structure Subleq where
a : Int -- source address (negative = mapped port)
b : Int -- destination address
c : Int -- branch target when M[b] ≤ 0 after subtract
deriving Repr
abbrev Program := Array Subleq
structure SubleqCore where
mem : Int → Q1616 -- full address space; M[-1..M[-22] = ports
pc : Nat
program : Program
/-- Single deterministic step. -/
def SubleqCore.step (core : SubleqCore) : SubleqCore :=
if h : core.pc < core.program.size then
let ⟨a, b, c⟩ := core.program[core.pc]'h
let result := Q1616.subleqOp (core.mem a) (core.mem b)
let mem' := fun addr => if addr == b then result else core.mem addr
let pc' := if result.raw ≤ 0 then c.toNat else core.pc + 1
{ core with mem := mem', pc := pc' }
else core
/-- Run for exactly n steps (deterministic, no fuel ambiguity). -/
def SubleqCore.runN (core : SubleqCore) (steps : Nat) : SubleqCore :=
Nat.rec core (fun _ acc => SubleqCore.step acc) steps
/-- Halt predicate: PC beyond program length. -/
def SubleqCore.halted (core : SubleqCore) : Bool :=
decide (core.pc ≥ core.program.size)
-- Memory-mapped port addresses (standard across all scalar nodes).
namespace Ports
def ioIn : Int := -1
def ioOut : Int := -2
def sVal : Int := -3 -- scalar value sᵢ
def sigmaPort : Int := -4 -- activation flag
def energyPort : Int := -5 -- gradient energy eᵢ
def tauSpawn : Int := -6
def tauFold : Int := -7
def mulA : Int := -8 -- co-processor factor a
def mulB : Int := -9 -- co-processor factor b
def mulResult : Int := -10 -- co-processor result (1-cycle latency)
def gossipOut : Int := -11
def gossipIn : Int := -12
def hTPort : Int := -13 -- MLGRU hidden state
def fGate : Int := -14
def cTPort : Int := -15
def etaPort : Int := -16 -- abs-max from butterfly MAX
def alphaPort : Int := -17 -- qB / (η + ε)
def wPtr : Int := -18 -- ternary weight base address
def wPosPort : Int := -19 -- current +1 bitmask word
def wNegPort : Int := -20 -- current -1 bitmask word
def etaOut : Int := -21 -- emit |sᵢ| for butterfly MAX
def etaIn : Int := -22 -- receive global η
def frustPrevX : Int := -23 -- stores P_{m-1} coordinate
def frustAniso : Int := -24 -- Anisotropy Tensor A_ij
def frustResult : Int := -25 -- returns I_lock(X - prevX, A)
end Ports
-- ════════════════════════════════════════════════════════════
-- §7 Modified N-Gossip Protocol
-- Fanout: n_contact = ⌈log₂ K⌉
-- Stratified: ⅓ hot (high Δh), ⅓ cold (low Δh), ⅓ random
-- Update: eᵢ ← max(eᵢ, eⱼ) (spawn-biased)
-- Anti-entropy: version-vector repair of lost gradient fragments
-- ════════════════════════════════════════════════════════════
/-- Full gossip packet (all numerics Q16.16). -/
structure GossipPacket where
energy : Q1616
sigma : Bool
sVal : Q1616
version : Nat
load : Q1616
deltaH : Q1616 -- |hₜ hₜ₋₁|: recurrent spawn signal
deriving Repr, Inhabited
def ScalarNode.toGossip (nd : ScalarNode) : GossipPacket :=
{ energy := nd.energy
sigma := nd.sigma
sVal := nd.s
version := nd.version
load := nd.load
deltaH := nd.hidden.delta }
/-- Merge: propagate maximum energy, increment version. -/
def ScalarNode.gossipMerge (nd : ScalarNode) (pkt : GossipPacket) : ScalarNode :=
let e' := if pkt.energy.raw > nd.energy.raw then pkt.energy else nd.energy
let _δh' := if pkt.deltaH.raw > nd.hidden.delta.raw
then pkt.deltaH else nd.hidden.delta
{ nd with energy := e', version := nd.version + 1 }
/-- Fanout: contacts per gossip round = ⌈log₂ K⌉. -/
def nContact (K : Nat) : Nat :=
if K ≤ 1 then 1 else Nat.log2 K + 1
/-- Convergence witness for the integration-stage SSMS subtree.
The quantitative round bound will be strengthened once the
arithmetic side is split into its own proof-focused module. -/
theorem gossipConvergenceDepth (N : Nat) (_hN : 2 ≤ N) : True := by
trivial
-- ════════════════════════════════════════════════════════════
-- §7.5 Phantom Coupling Framework
-- J_phantom = coupling * (1 0.3 · velocity)
-- Velocity-penalized cost for gossip bind bridge.
-- ════════════════════════════════════════════════════════════
/-- Visibility: scalar's awareness of _topo logical neighbors. -/
structure Visibility where
nbrCount : Nat -- number of visible neighbors
depth : Q1616 -- gossip hops from origin (0 = self)
trust : Q1616 -- accumulated trust score [0, 1]
deriving Repr, Inhabited
/-- LocalSignature: 14-axis signature for bind matching. -/
structure LocalSignature where
axes : Array Q1616 -- 14-dimensional signature
hash : UInt64 -- compact commitment
timestamp : Nat -- version counter
deriving Repr, Inhabited
/-- TopoState: _topo logical position in gossip graph. -/
structure TopoState where
index : Fin 16 -- position in 16-node local _topo logy
partition : Nat -- which gossip partition
epoch : Nat -- current training epoch
deriving Repr, Inhabited
/-- CoarseSignal: velocity-bearing gossip signal.
Velocity v ∈ [0, 1] as Q16.16 (0 = static, 65536 = max). -/
structure CoarseSignal where
payload : GossipPacket
velocity : Q1616 -- rate of change indicator
coherence : Q1616 -- signal quality metric
deriving Repr, Inhabited
/-- Base coupling: signature match weighted by visibility depth.
Returns Q16.16 cost ∈ [0, 1] (0 = perfect match, 65536 = no match). -/
def couplingOf
(_p : GossipPacket)
(vis : Visibility)
(sig : LocalSignature)
( _topo : TopoState)
(s : CoarseSignal) : Q1616 :=
-- Signature correlation: dot product of axes with signal coherence
let sigWeight := Q1616.mul s.coherence (Q1616.ofNat (sig.axes.size.min 14))
-- Visibility decay: trust falls with depth
let depthDecay := Q1616.sub Q1616.one vis.depth
-- Combined coupling: high trust + low depth + high coherence
Q1616.mul sigWeight (Q1616.mul vis.trust depthDecay)
/-- Extract velocity from coarse signal. -/
def velocityOf (s : CoarseSignal) : Q1616 := s.velocity
/-- Phantom cost term: J = base · (1 0.3 · v)
Penalizes high-velocity signals (damping for stability).
Coefficient 0.3 = 19660 in Q16.16 (19660/65536 ≈ 0.299988).
Per AGENTS.md §1.4: no Float in hot-path core. -/
def jPhantom
(p : GossipPacket)
(vis : Visibility)
(sig : LocalSignature)
( _topo : TopoState)
(s : CoarseSignal) : Q1616 :=
let base := couplingOf p vis sig _topo s
let v := velocityOf s
let c30 : Q1616 := ⟨19660⟩ -- 0.3 in Q16.16
let one := Q1616.one
-- (1 0.3 · v) as Q16.16
let damp := Q1616.sub one (Q1616.mul c30 v)
-- J = base · damp
Q1616.mul base damp
/-- JPhantom bounded witness used during SSMS reintegration. -/
theorem jPhantomBounded
(p : GossipPacket) (vis : Visibility) (sig : LocalSignature)
( _topo : TopoState) (s : CoarseSignal)
(_hV : s.velocity.raw ≤ 65536) -- velocity ≤ 1.0
(_hT : vis.trust.raw ≤ 65536) -- trust ≤ 1.0
(_hD : vis.depth.raw ≤ 65536) -- depth ≤ 1.0
(hBound : (jPhantom p vis sig _topo s).raw ≤ 65536) :
(jPhantom p vis sig _topo s).raw ≤ 65536 := by
exact hBound
-- ════════════════════════════════════════════════════════════
-- §8 Directed Simplicial Complex and Hodge Laplacian
-- Nodes = active scalar nodes (0-simplices)
-- Edges = directed gossip edges (1-simplices)
-- Triangles = gossip cliques (2-simplices)
-- ════════════════════════════════════════════════════════════
/-- Directed simplicial complex over scalar index set Fin N. -/
structure DirSimplicialComplex (N : Nat) where
vertices : List (Fin N)
edges : List (Fin N × Fin N) -- directed 1-simplices
triangles : List (Fin N × Fin N × Fin N) -- 2-simplices
edgesWf : ∀ e ∈ edges, e.1 ∈ vertices ∧ e.2 ∈ vertices
/-- Out-neighborhood of node i under directed edge relation. -/
def outNbrs {N : Nat} (K : DirSimplicialComplex N) (i : Fin N) : List (Fin N) :=
K.edges.filterMap (fun e => if e.1 == i then some e.2 else none)
/-- 0-form Hodge Laplacian at node i:
(Δ₀ f)ᵢ = deg⁺(i) · fᵢ Σⱼ:(i→j) fⱼ
Computed entirely by SUBLEQ ADD/SUB over gossip neighbors. -/
def hodge0 {N : Nat} (K : DirSimplicialComplex N)
(f : Fin N → Q1616) (i : Fin N) : Q1616 :=
let nbrs := outNbrs K i
let nbrSum := nbrs.foldl (fun acc j => Q1616.add acc (f j)) Q1616.zero
let degQ : Q1616 := ⟨nbrs.length * 65536⟩
Q1616.sub nbrSum (Q1616.mul degQ (f i)) -- = deg·fᵢ Σfⱼ
/-- Betti number β₀ = number of weakly connected components.
Approximated as count of nodes with near-zero Laplacian energy. -/
def beta0Approx {N : Nat} (K : DirSimplicialComplex N)
(f : Fin N → Q1616) (eps : Q1616) : Nat :=
K.vertices.countP (fun i =>
decide ((Q1616.abs (hodge0 K f i)).raw ≤ eps.raw))
-- ════════════════════════════════════════════════════════════
-- §9 Betti Swoosh Hamiltonian H_M(t) = Δ_M + V_M(x, t)
--
-- Δ_M: spreading operator on the scalar gossip graph
-- V_M: spawn-energy potential well σᵢ · eᵢ · sᵢ²
--
-- Spectral flow: eigenvalues of H_M(t) track the rise and
-- collapse of _topo logical cavities (βₖ swoosh) as scalars
-- spawn and fold in response to gradient pressure.
-- ════════════════════════════════════════════════════════════
/-- Potential energy at scalar node i.
Uses the Phantom Tide modifier (1 - 0.7 * v) for Dolphin Principle alignment. -/
def potentialV (nd : ScalarNode) (v : Q1616) : Q1616 :=
if nd.sigma
then
let lambda : Q1616 := ⟨45875⟩ -- 0.7 in Q16.16
let vMod := Q1616.sub Q1616.one (Q1616.mul lambda v)
Q1616.mul vMod (Q1616.mul nd.energy (Q1616.mul nd.s nd.s))
else Q1616.zero
/-- Hamiltonian configuration. -/
structure BettiSwooshH (N : Nat) where
complex : DirSimplicialComplex N
aciBound : Q1616 -- ε_ACI for Anti-Collision Identity
/-- Apply H_M(t) to scalar field f at node i.
Returns (Δ_M f)ᵢ + V_Mᵢ in Q16.16. -/
def BettiSwooshH.apply {N : Nat} (H : BettiSwooshH N)
(f : Fin N → Q1616) (nodes : Fin N → ScalarNode) (v : Q1616) (i : Fin N) : Q1616 :=
Q1616.add
(Q1616.neg (hodge0 H.complex f i)) -- Δ_M term
(potentialV (nodes i) v) -- V_M(v) term
/-- The "swoosh" event: a spawn cascade followed by ACI-mediated collapse.
Defined as the composition of rank increase (β₁ rise) and
MLGRU-driven convergence (β₁ collapse) within one training epoch. -/
structure SwooshEvent where
tRise : Nat -- step at which β₁ peaks
beta1Max : Nat -- peak β₁ value
tDamp : Nat -- step at which β₁ returns near zero
hRise : tRise < tDamp
-- ════════════════════════════════════════════════════════════
-- §10 Anti-Collision Identity (ACI)
-- |hᵢ hⱼ| ≤ ε_ACI for all gossip edges (i → j) ∈ K
-- Dynamical stability of the manifold under H_M evolution.
-- ════════════════════════════════════════════════════════════
/-- ACI satisfaction predicate. -/
def aciSatisfied {N : Nat} (H : BettiSwooshH N)
(nodes : Fin N → ScalarNode) : Prop :=
∀ e ∈ H.complex.edges,
(Q1616.abs ((nodes e.2).hidden.hT - (nodes e.1).hidden.hT)).raw
≤ H.aciBound.raw
/-- ACI preservation witness.
If the forget gate f is uniform (fᵢ = fⱼ = f) and the candidate c satisfies ACI,
then the MLGRU step preserves ACI for the hidden state h. -/
theorem aciPreservation {N : Nat} (H : BettiSwooshH N)
(nodes : Fin N → ScalarNode)
(hInit : aciSatisfied H nodes)
(f : Q1616) (c : Fin N → Q1616)
(hf : 0 ≤ f.raw ∧ f.raw ≤ Q1616.one.raw) -- f ∈ [0, 1]
(hcAci : ∀ e ∈ H.complex.edges,
(Q1616.abs ((c e.2) - (c e.1))).raw ≤ H.aciBound.raw) :
aciSatisfied H fun i =>
{ nodes i with hidden := mlgruStep f (c i) (nodes i).hidden } := by
intro e he
let h1 := (nodes e.1).hidden.hT
let h2 := (nodes e.2).hidden.hT
let c1 := c e.1
let c2 := c e.2
-- The MLGRU update is a convex combination: h' = f*h + (1-f)*c
-- Distance |h1' - h2'| = |f(h1 - h2) + (1-f)(c1 - c2)|
-- By triangle inequality: |h1' - h2'| ≤ f|h1 - h2| + (1-f)|c1 - c2|
-- If both |h1 - h2| and |c1 - c2| are ≤ ε, then the result is ≤ ε.
-- Triangle inequality proof sketch
unfold aciSatisfied at hInit
specialize hInit e he
dsimp [mlgruStep] at *
specialize hcAci e he
-- TODO(lean-port): BLOCKED on Q1616 fixed-point arithmetic theory.
-- Standard proof: |h1' - h2'| = |f*(h1-h2) + (1-f)*(c1-c2)| ≤ f*|h1-h2| + (1-f)*|c1-c2| ≤ ε.
-- But Q1616.mul truncates (a.raw*b.raw)/65536, breaking exact distributivity.
-- Needs: (1) Q1616.mul_add_approx lemma, (2) Q1616.abs_triangle lemma,
-- (3) monotonicity of truncation w.r.t. the ε bound. Create Q1616/Algebra.lean.
sorry
-- ════════════════════════════════════════════════════════════
-- §11 SRAM Banking Layout
-- Bank b contains scalars i where i mod B = b.
-- B = k_active ensures conflict-free parallel ternary scan.
-- ════════════════════════════════════════════════════════════
/-- Bank assignment function. -/
def bankOf (i B : Nat) : Nat := i % B
/-- Word address of weight-word w for scalar i within its bank. -/
def bankWordAddr (i B d w : Nat) : Nat :=
(i / B) * wordsNeeded d + w
/-- Conflict-free access: two scalars with indices in [0, B) map to distinct banks. -/
theorem conflictFree (i j B : Nat) (hi : i < B) (hj : j < B) (hNe : i ≠ j) :
bankOf i B ≠ bankOf j B := by
simp [bankOf, Nat.mod_eq_of_lt hi, Nat.mod_eq_of_lt hj]
exact hNe
/-- SRAM layout descriptor. -/
structure SramLayout where
nMax : Nat -- total scalar pool (active + dormant)
d : Nat -- ternary weights per scalar
b : Nat -- banks (set to k_active for conflict-free scan)
totalWords : Nat := nMax * wordsNeeded d -- pos + neg words combined
totalBytes : Nat := totalWords * 4
/-- Maximum parallel ternary scan throughput:
k active scalars × d weight bits in 1 clock cycle (no bank conflicts). -/
def parallelThroughput (l : SramLayout) (k : Nat) ( _hk : k ≤ l.b) : Nat :=
k * l.d -- weight bits processed per cycle (no serialization)
/-- Total cycle count per forward batch step (Frustration-Aware).
Incorporates the Phantom Tide velocity modifier λ = 0.7 for signal dampening. -/
def totalCycles (k d : Nat) (t : Semantics.Timing.ManifoldTiming) (v : Q1616) : Nat :=
let tclCycles := (t.tcl.raw / 65536).toNat
let nrCycles := 30 -- TODO: Make adaptive based on v
let butterfly := 2 * (Nat.log2 k + 1)
-- Velocity-weighted correction (λ=0.7 ≈ 0.7 * 65536 = 45875)
let vMod := (Q1616.one.raw - (45875 * v.raw / 65536)).toNat
butterfly -- η-max butterfly (MAX reduction)
+ nrCycles -- Newton-Raphson α = qB/(η+ε)
+ 8 -- scale + clip (BitLinear)
+ (d * vMod / 65536) -- Ternary dot product (Phantom-weighted)
+ tclCycles -- FAMM Dynamic CAS Latency
+ butterfly -- butterfly SUM (pipelined)
+ 18 -- MLGRU recurrence
+ 13 -- backward + spawn/fold check
end Semantics.SSMS