scbe-gate-swap

name	scbe-gate-swap
description	Analyze and swap between 2-gate (binary/negabinary) and 3-gate (balanced ternary) encoding for stability optimization. Use when evaluating gate efficiency, comparing encoding strategies for governance decisions, or optimizing bit-level representation in SCBE subsystems.

SCBE Gate Swap Analysis

Determine where in the SCBE-AETHERMOORE system to use 2-gate (binary) vs 3-gate (ternary) encoding for maximum stability and efficiency.

Gate Types

3-Gate (Balanced Ternary)

• Digits: {-1, 0, +1} (T, 0, 1)
• No sign bit needed
• Maps directly to ALLOW/QUARANTINE/DENY
• Best for: governance decisions, small mixed-sign values, consensus voting

2-Gate (Binary / Negabinary)

• Standard binary: digits {0, 1}, needs sign bit for negatives
• Negabinary (base -2): digits {0, 1}, no sign bit, polarity from position
• Best for: large positive ranges, bit-level operations, hardware compatibility

When to Use Which

Subsystem	Recommended Gate	Why
Governance decisions	3-gate (ternary)	Natural ALLOW/QUARANTINE/DENY mapping
BFT voting	3-gate (ternary)	YES/ABSTAIN/NO maps to +1/0/-1
Trust scores	3-gate (ternary)	Trust/neutral/distrust is triadic
Entropy values	2-gate (binary)	Always positive, wide range
Bit lengths	2-gate (binary)	Always positive integers
Polarity analysis	2-gate (negabinary)	Natural positive/negative encoding
Sacred Tongue mapping	2-gate (negabinary)	KO/AV polarity from bit position
Hamiltonian routing	3-gate (ternary)	Direction: forward/stay/backward
Safety scores	3-gate (ternary)	Safe/uncertain/unsafe
Cryptographic keys	2-gate (binary)	Hardware/algorithm compatibility
Spectral coefficients	3-gate (ternary)	Positive/zero/negative frequency

Analysis Workflow

1. Profile the Value Range

from src.symphonic_cipher.scbe_aethermoore.negabinary import analyze_gate_stability

# Collect values from the subsystem
values = [...]  # the data to encode

report = analyze_gate_stability(values)
print(report.stability_recommendation)
print(f"Binary:     {report.binary_total_bits} bits")
print(f"Ternary:    {report.ternary_total_trits} trits")
print(f"Negabinary: {report.negabinary_total_bits} bits")

2. Interpret the Recommendation

The analyzer uses these heuristics:

• Small mixed-sign (|max| <= 40, has negatives): TERNARY
• Mixed polarity, negabinary more compact: NEGABINARY
• Ternary fewer trits than negabinary bits: TERNARY
• Large positive range: BINARY

3. Cross-Convert if Needed

from src.symphonic_cipher.scbe_aethermoore.negabinary import (
    negabinary_to_balanced_ternary,
    balanced_ternary_to_negabinary,
)
from src.symphonic_cipher.scbe_aethermoore.trinary import BalancedTernary
from src.symphonic_cipher.scbe_aethermoore.negabinary import NegaBinary

# Ternary -> Negabinary
bt = BalancedTernary.from_int(42)
nb = balanced_ternary_to_negabinary(bt)

# Negabinary -> Ternary
nb = NegaBinary.from_int(-7)
bt = negabinary_to_balanced_ternary(nb)

4. Governance Decision Packing

from src.symphonic_cipher.scbe_aethermoore.trinary import BalancedTernary

decisions = ["ALLOW", "DENY", "QUARANTINE", "ALLOW", "ALLOW"]
packed = BalancedTernary.pack_decisions(decisions)
summary = packed.governance_summary()
# {consensus: "ALLOW", net_score: 2, allow: 3, deny: 1, quarantine: 1}

5. Tongue Polarity from Negabinary

from src.symphonic_cipher.scbe_aethermoore.negabinary import NegaBinary

nb = NegaBinary.from_int(42)
print(nb.tongue_polarity())   # "KO" or "AV" or "RU"
print(nb.tongue_encoding())   # ["KO", "UM", "AV", "KO", ...]

# Even bit positions = positive weight = KO (assertive)
# Odd bit positions  = negative weight = AV (receptive)
# Zero bits          = UM (silence)

Integration with Existing Systems

Dual Ternary (ai_brain/dual_ternary.py)

The existing 9-state dual ternary system uses {-1,0,+1} x {-1,0,+1} for spectral analysis. The new balanced ternary module provides arithmetic operations that complement it.

CPSE z-vector

The CPSE deviation channels (chaosdev, fractaldev, energydev) produce values in [-1, +1]. These map naturally to ternary encoding when discretized.

Layer 11 Triadic Distance

The triadic temporal distance already uses a 3-valued system. Balanced ternary provides the formal arithmetic foundation.

Key Files

File	Purpose
src/symphonic_cipher/scbe_aethermoore/trinary.py	Balanced ternary encoding + governance
src/symphonic_cipher/scbe_aethermoore/negabinary.py	Negabinary + gate stability analysis
src/symphonic_cipher/scbe_aethermoore/ai_brain/dual_ternary.py	9-state dual ternary spectral
tests/test_trinary_negabinary.py	45 tests covering both systems

Entropy Comparison

# Ternary: max entropy = log2(3) = 1.585 bits per trit
# Binary:  max entropy = log2(2) = 1.000 bits per bit
# Ternary packs more information per digit

bt = BalancedTernary.from_int(n)
density = bt.information_density()  # 0.0 to 1.0

nb = NegaBinary.from_int(n)
entropy = nb.bit_entropy()  # Shannon entropy of bit distribution