SCBE-AETHERMOORE: Complete Technical Deck

Version: 5.0
Status: Production-Ready
Deck Last Updated: January 17, 2026
Repo Deck Consolidation: February 19, 2026

Data Confidence

Verified in this repo run:
- python six-tongues-cli.py selftest
- pytest -q tests/test_six_tongues_cli.py tests/test_spiralverse_canonical_registry.py
Repo-documented benchmark values:
- docs/ARCHITECTURE.md
Reported operational values (deck-provided, external runtime context):
- AWS/Lambda fleet metrics, enterprise throughput, and deployment anecdotes.

Executive Summary

SCBE-AETHERMOORE is a 14-layer post-quantum hyperbolic governance system that combines:

post-quantum cryptography (ML-KEM-768, ML-DSA-65)
hyperbolic trust geometry
fail-to-noise authorization semantics
multi-agent coordination controls

Core effect: contextual deviation drives superexponential risk amplification:

H(d, R) = R^(d^2), R > 1

This creates hard trust boundaries in geometric space while keeping normal-path overhead low.

System Architecture
Mathematical Foundations
Minimal Setup Requirements
Quick Start
Deployment Patterns
Configuration Reference
Production Checklist
Visual Architecture
HYDRA Multi-Agent Coordination Integration
Drone Fleet Integration (SCBE + GeoSeal + Topological CFI)
FAQ

1. System Architecture

1.1 The 14-Layer Pipeline

Layer flow:

Layer 1: Complex Context State
Layer 2: Realification
Layer 3: Weighted Transform
Layer 4: Poincare Embedding
Layer 5: Hyperbolic Distance (immutable law)
Layer 6: Breathing Transform
Layer 7: Phase Transform
Layer 8: Multi-Well Realms
Layer 9: Spectral Coherence
Layer 10: Spin Coherence
Layer 11: Triadic Temporal Distance
Layer 12: Harmonic Scaling
Layer 13: Decision and Risk
Layer 14: Audio Axis (optional multi-modal)

Decision terminal:

ALLOW | DENY | NOISE

1.2 Layer Math Summary

Layer 1: z in C^D preserves amplitude + phase intent
Layer 2: C^D -> R^(2D) via (Re, Im) split
Layer 3: G = diag(g_1, ..., g_n) with golden-ratio-style weighting
Layer 4: u = tanh(alpha ||x||) * x / ||x||
Layer 5:
- d_H(u,v) = arcosh(1 + 2||u-v||^2 / ((1-||u||^2)(1-||v||^2)))
Layer 6:
- u -> tanh(b * artanh(||u||)) * u / ||u||
Layer 7: Mobius addition + rotation
Layer 8: d*(u) = min_k d_H(u, mu_k)
Layer 9: S_spec = 1 - HF_energy / total_energy
Layer 10: C_spin = ||sum_j s_j(t)|| / sum_j ||s_j(t)||
Layer 11: d_tri = sqrt(lambda1 d1^2 + lambda2 d2^2 + lambda3 dG^2)
Layer 12: H(d,R) = R^(d^2)
Layer 13: Risk' = Risk_base * H(d*, R)

1.3 Architectural Principles

Immutable law:
- Hyperbolic metric is governance anchor.
Fail-to-noise:
- Wrong context returns noise-like output, not an oracle-friendly error.
Diffeomorphic governance:
- Smooth transforms (breathing/phase) avoid singular policy jumps.
Lipschitz continuity:
- Small context changes imply bounded risk changes.

2. Mathematical Foundations

2.1 Notation

C^D: complex context space
R^n: Euclidean transformed space
B^n: Poincare ball {u in R^n : ||u|| < 1}
Euclidean norm: ||x|| = sqrt(x^T x)
Weighted norm: ||x||_G = sqrt(x^T G x)

Hyperbolic functions:

tanh(x) = (e^x - e^-x) / (e^x + e^-x)
artanh(x) = 0.5 ln((1+x)/(1-x))
sech(x) = 1 / cosh(x)

2.2 Core Theorems (Deck Canon)

Polar decomposition uniqueness in C.
Isometric realification C^D -> R^(2D).
Poincare embedding containment (||Psi_alpha(x)|| < 1).
Hyperbolic metric axioms for d_H.
Breathing transform preserves ball constraints.
Harmonic scaling monotonicity and superexponential profile.
End-to-end continuity (Lipschitz on compact subsets).

2.3 Security Properties

PQ resistance:
- ML-KEM-768 and ML-DSA-65 integration points.
Oracle hardening:
- fail-to-noise output strategy.
Byzantine tolerance:
- trust-decay and exclusion policies in swarm modes.

3. Minimal Setup Requirements

3.1 Hardware

Dev: 2 cores, 4 GB RAM minimum.
Small production: 4 cores, 8 GB RAM.
High throughput: 8+ cores, 16+ GB RAM.

3.2 Software

Python 3.11+
requirements.txt in repo root
Optional PQ acceleration backends where available

3.3 Platform Matrix

Linux/macOS: supported
Windows: supported (PowerShell and WSL workflows in repo)
Docker/Kubernetes: supported paths present
AWS Lambda: deployment artifacts present in repo

4. Quick Start

4.1 Local Install

git clone https://github.com/issdandavis/SCBE-AETHERMOORE.git
cd SCBE-AETHERMOORE
python -m venv .venv
source .venv/bin/activate  # Windows: .venv\Scripts\activate
pip install -r requirements.txt

4.2 Validate Install

python six-tongues-cli.py selftest
pytest -q tests/test_six_tongues_cli.py tests/test_spiralverse_canonical_registry.py

4.3 Optional Full Test Sweep

pytest -q tests

5. Deployment Patterns

5.1 Docker

Use repo Dockerfiles and compose files:
- Dockerfile
- docker-compose.yml
- docker-compose.api.yml
- docker-compose.unified.yml

5.2 Kubernetes

Deploy gate service + HPA pattern.
Monitor p95 latency and denial spikes.

5.3 Serverless (Lambda)

Lambda packaging/deployment paths exist under repo deployment structure.
Recommended for bursty traffic and scale-to-zero economics.

5.4 Edge/Offline

Precompute and cache critical lookup/state data.
Sync trust data when online.

6. Configuration Reference

Primary domains:

system mode and logging
crypto suite selection
harmonic scaling parameters
trust and swarm thresholds
monitoring and tracing endpoints

Representative keys:

SCBE_MODE
SCBE_LOG_LEVEL
SCBE_HARMONIC_R
vault and database credentials

7. Production Checklist

7.1 Security

no hardcoded secrets
TLS valid
key rotation policy active
fail-to-noise behavior validated

7.2 Validation

test suite green
load profile tested
deny/review thresholds tuned for workload

7.3 Observability

metrics scraping enabled
dashboards configured
alerting for denial spikes and trust degradation

7.4 Operations

runbook current
incident paths tested
rollback strategy documented

8. Visual Architecture

System context:

External actors -> SCBE Gate -> 14-layer verifier -> decision output

Data flow:

context extraction -> hyperbolic embedding -> risk amplification -> allow/deny/noise

Trust topology:

swarm trust graph with exclusion threshold policy

Execution timeline:

layer-level microsecond budgets with spectral/audio as dominant optional components

9. HYDRA Integration

HYDRA provides terminal-native multi-agent coordination above SCBE:

Spine: coordinator
Heads: universal AI interface
Limbs: execution backends
Librarian: memory/knowledge
Ledger: audit persistence

Security overlays:

byzantine consensus path
spectral anomaly detection path
SCBE gate on critical actions

Pilot-copilot browser model:

two agents can co-pilot one browser backend
additional agents can be attached for extraction/verification as needed

10. Drone Fleet Integration

Document lineage:

“Drone Fleet System Improvements: Integration of Swarm Coordination, GeoSeal, and Topological CFI”

Six integrated upgrade themes:

Gravitational braking for rogue drones
Sphere-in-cube mission-bound topology enforcement
Harmonic camouflage with stellar pulse modulation
Sacred Tongue flight dynamics mapping
Vacuum-acoustic bottle beam data protection concept
Dimensional lifting for embedded CFI reliability

Operational intent:

reduce unauthorized maneuver success
increase intervention window
improve covert signaling resilience
enforce bounded control flow under constrained hardware

11. FAQ

Is it production-ready?

Core components are operational in this repository and deployment artifacts are present. For high-stakes environments, external red-team and formal audits are still recommended.

Is it quantum-safe?

The architecture is built to support NIST PQC-era primitives with governance layers above raw cryptography.

What is fail-to-noise?

Denied/invalid contexts return output patterns designed to avoid giving oracle-style failure signals.

Can it run offline?

Yes. Edge/offline operation is supported with local state and deferred sync patterns.

Can this support multi-agent mission systems?

Yes. HYDRA and swarm architecture paths are designed for multi-agent coordination with governance checks.

Repository References

docs/ARCHITECTURE.md
docs/SCBE_FULL_SYSTEM_LAYER_MAP.md
docs/SPIRALVERSE_CODEX.md
docs/specs/SPIRALVERSE_CANONICAL_LINGUISTIC_CODEX_V1.md
docs/specs/spiralverse_canonical_registry.v1.json
docs/SIX_TONGUES_CLI.md
six-tongues-cli.py
tests/test_six_tongues_cli.py
tests/test_spiralverse_canonical_registry.py
docs/hydra/ARCHITECTURE.md

12. Dual Lattice Cross-Stitch v2

Status: Operational component family in src/crypto with hyperbolic octree and hyperpath modules.

12.1 Scope

This appendix captures the Dual Lattice Cross-Stitch integration surface for:

hyperbolic lattice point construction
sparse Poincare-ball octree storage
A* and bidirectional A* hyperpath traversal
SCBE layer-gated path authorization
multi-modal logging hooks (visual, audio, ledger)

12.2 Core Files

src/crypto/dual_lattice.py
src/crypto/dual_lattice_integration.py
src/crypto/octree.py
src/crypto/hyperpath_finder.py
src/crypto/hyperbolic_viz.py
src/crypto/signed_lattice_bridge.py
src/crypto/symphonic_waveform.py

12.3 Integration Points

SCBE layer mapping used by the integration modules:

Layer 1 (PQC): Kyber and Dilithium level gating
Layers 2-4: signed context to Poincare projection
Layer 5: hyperbolic distance metric
Layer 8/9: realm and path validation logic
Layer 12: harmonic path-cost amplification
Layer 14: optional path sonification/audio signature