/-! # Q0_64 Experimental — Ultra-Precision Dimensionless Scalars **Status:** TEST BRANCH — Experimental, do not commit to main. **Purpose:** Explore 64-bit pure fraction for dimensionless quantities where Q0_16 (≈ 0.00003 resolution) is insufficient. **Q0_16 resolution:** 1/32767 ≈ 3.05×10⁻⁵ **Q0_64 resolution:** 1/2⁶³ ≈ 1.08×10⁻¹⁹ **Trade-off:** Q0_64 is 4× larger than Q0_16 (8 bytes vs 2 bytes). Per AGENTS.md §1.4 default: Q0_16. Q0_64 is for contexts where confidence thresholds demand sub-ppm precision (e.g., 6.5σ tail events). This file is standalone: zero imports. -/ -- ═══════════════════════════════════════════════════════════════════════════ -- §0 Q0_64 Structure -- ═══════════════════════════════════════════════════════════════════════════ /-- Q0.64 pure fraction: 64-bit unsigned interpreted as signed fixed-point. Range: [-1.0, 1.0 - 2⁻⁶⁴] ≈ [-1.0, 0.99999999999999999989] Resolution: 2⁻⁶³ ≈ 1.08 × 10⁻¹⁹ 0x8000_0000_0000_0000 = 1.0 (max positive) 0x0000_0000_0000_0000 = 0.0 -/ structure Q0_64 where val : UInt64 deriving Repr, BEq, Inhabited -- ═══════════════════════════════════════════════════════════════════════════ -- §1 Constants -- ═══════════════════════════════════════════════════════════════════════════ def Q0_64.zero : Q0_64 := ⟨0x0000_0000_0000_0000⟩ def Q0_64.one : Q0_64 := ⟨0x8000_0000_0000_0000⟩ -- ~1.0 def Q0_64.half : Q0_64 := ⟨0x4000_0000_0000_0000⟩ -- 0.5 -- ═══════════════════════════════════════════════════════════════════════════ -- §2 Basic Arithmetic -- ═══════════════════════════════════════════════════════════════════════════ def Q0_64.neg (x : Q0_64) : Q0_64 := ⟨-x.val⟩ def Q0_64.add (a b : Q0_64) : Q0_64 := ⟨a.val + b.val⟩ def Q0_64.sub (a b : Q0_64) : Q0_64 := ⟨a.val - b.val⟩ /-- Multiplication: (a/2⁶³) × (b/2⁶³) × 2⁶³ = (a×b)/2⁶³. Uses unbounded Nat intermediate to avoid 64-bit overflow. -/ def Q0_64.mul (a b : Q0_64) : Q0_64 := let prod : Nat := a.val.toNat * b.val.toNat ⟨(prod >>> 63).toUInt64⟩ /-- Division: a/b = (a × 2⁶³) / b. Saturate on div-by-zero. -/ def Q0_64.div (a b : Q0_64) : Q0_64 := if b.val = 0 then ⟨0x8000_0000_0000_0000⟩ else let num : Nat := a.val.toNat <<< 63 ⟨(num / b.val.toNat).toUInt64⟩ -- ═══════════════════════════════════════════════════════════════════════════ -- §3 Precision Comparison (Q0_16 vs Q0_64) -- ═══════════════════════════════════════════════════════════════════════════ /-- Smallest representable positive value in Q0_16: 1/32767 ≈ 3.05×10⁻⁵ -/ def q0_16Epsilon : Nat := 1 -- Q0_16.val = 1 corresponds to ≈ 3.05×10⁻⁵ in float space /-- Smallest representable positive value in Q0_64: 1/2⁶³ ≈ 1.08×10⁻¹⁹ -/ def q0_64Epsilon : Nat := 1 -- Q0_64.val = 1 corresponds to ≈ 1.08×10⁻¹⁹ in float space /-- Ratio of precisions: Q0_64 is 2⁴⁸× finer than Q0_16. 2⁶³ / 2¹⁵ = 2⁴⁸ ≈ 2.8 × 10¹⁴ -/ def precisionRatio : Nat := let q16Max : Nat := 0x8000 -- 32768 let q64Max : Nat := 0x8000_0000_0000_0000 -- 2^63 q64Max / q16Max -- ═══════════════════════════════════════════════════════════════════════════ -- §4 6.5σ Tail Probability in Q0_64 -- ═══════════════════════════════════════════════════════════════════════════ /-- Standard normal CDF at 6.5σ: Φ(6.5) ≈ 4.02 × 10⁻¹¹. In Q0_16: this rounds to 0 (below epsilon). In Q0_64: representable as val ≈ 346 (6.5σ in Q0_64 units, approximate). -/ def sigma65TailProbabilityQ0_16Representable : Bool := false -- 4.02×10⁻¹¹ << Q0_16 epsilon (3.05×10⁻⁵). Rounds to zero. def sigma65TailProbabilityQ0_64Representable : Bool := true -- 4.02×10⁻¹¹ >> Q0_64 epsilon (1.08×10⁻¹⁹). Easily representable. -- ═══════════════════════════════════════════════════════════════════════════ -- §5 Witness Values -- ═══════════════════════════════════════════════════════════════════════════ #eval Q0_64.zero -- { val := 0 } #eval Q0_64.one -- { val := 9223372036854775808 } #eval Q0_64.half -- { val := 4611686018427387904 } #eval Q0_64.add Q0_64.half Q0_64.half -- { val := 9223372036854775808 } = one #eval Q0_64.sub Q0_64.one Q0_64.half -- { val := 4611686018427387904 } = half #eval Q0_64.mul Q0_64.half Q0_64.half -- 0.25: { val := 2305843009213693952 } #eval Q0_64.div Q0_64.one Q0_64.half -- 2.0: { val := 0 } -- wraps (2.0 exceeds [-1,1) range) #eval precisionRatio -- 281474976710656 (2^48) -- ═══════════════════════════════════════════════════════════════════════════ -- §6 Size Impact on Neural Compression (Back-of-Envelope) -- ═══════════════════════════════════════════════════════════════════════════ /-- Q0_16 neural state: 1 PB = 10¹⁵ bytes. Q0_64 neural state: 4 PB = 4×10¹⁵ bytes (4× larger). -/ def q0_16StateBytes : Nat := 1000000000000000 def q0_64StateBytes : Nat := q0_16StateBytes * 4 /-- At 1,250× compression: Q0_16 compressed: 800 GB Q0_64 compressed: 3,200 GB (exceeds 800 GB target) -/ def q0_16CompressedGb : Nat := q0_16StateBytes / 1250 / 1000000000 def q0_64CompressedGb : Nat := q0_64StateBytes / 1250 / 1000000000 /-- To hit 800 GB with Q0_64 raw state, compression ratio must be: C = 4×10¹⁵ / 8×10¹¹ = 5,000× -/ def requiredRatioForQ0_64 : Nat := q0_64StateBytes / 800000000000 #eval q0_16CompressedGb -- 800 #eval q0_64CompressedGb -- 3200 (fails 800 GB target) #eval requiredRatioForQ0_64 -- 5000 (need 4× higher compression) -- ═══════════════════════════════════════════════════════════════════════════ -- §7 Verdict -- ═══════════════════════════════════════════════════════════════════════════ /-- Q0_64 buys 2^48× precision at a 4× size cost. For 6.5σ tail probabilities (4×10⁻¹¹), Q0_16 rounds to zero. Q0_64 captures it with ~37 bits of headroom. Trade-off: if the neural state is stored as Q0_64, the compression pipeline must achieve 5,000× instead of 1,250× to hit the same storage target. This is feasible with deeper quantization-aware training but must be proven in the pipeline. -/ def testBranchVerdict : String := "Q0_64: 2^48 precision gain, 4x size cost. " ++ "6.5σ tails representable. " ++ "Compression target increases 1,250x -> 5,000x. " ++ "Test branch only — do not merge without pipeline proof." #eval testBranchVerdict