docs(research): Trinity S³AI Research Layer — 5 scientific documents + Unified Framework

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Trinity S³AI Research Layer — Scientific Documentation

Summary

Created unified scientific documentation layer for Trinity S³AI in docs/research/. The research layer links all components (HSLM, TRI-27, Queen, Sacred ALU, FPGA) with testable hypotheses and experimental pipelines.

Created Documents

Document	LOC	Description
trinity_s3ai_overview.md	~350	Master doc: S³ axes, 8-level stack, code map
tri27_platform.md	~300	TRI-27 as research platform, experiment classes
queen_lotus_experiments.md	~300	Lotus Cycle phases, H1/H2 hypotheses, A/B scenarios
sacred_formats_fpga.md	~300	GF16/TF3 specs, FPGA ALU benchmarks, comparison tables
tri_language_roadmap.md	~250	Tri grammar, dual-target compilation, scientific questions
TRINITY_S3AI_UNIFIED_FRAMEWORK.md	~450	Master framework: all hypotheses, pipelines, publications
TOTAL	~1950	Complete research layer

Research Hypotheses Formulated

ID	Hypothesis	Metrics
H1	GF16 matches FP16 with 37.8% fewer LUT	LUT util, MSE, throughput
H2	Zero-DSP matches DSP48 accuracy (<0.5%)	MSE, LUT ratio, energy/op
H3	Self-Learning reduces crash rate 3×	crash_rate, byzantine_rate, success_rate
H4	Feedback loop accelerates convergence 2×	time_to_stable, adaptation_events
H5	Ternary ISA improves code density 2.5×	instructions/algorithm, bytes/instruction
H6	Zero-DSP FPGA matches CPU SIMD 10×	GOP/s, latency, $/GOPs

Experimental Pipelines

HSLM Training

zig build hslm-train
./zig-out/bin/hslm-train --data data/tinystories/real_tinystories.txt \
    --steps 100000 --lr 3e-4 --batch 64 --schedule cosine

TRI-27 Self-Learning

tri tri27 run test.tbin
tri queen self-learning --window 20
tri queen config show

FPGA Benchmark

tri fpga synth sacred_alu --target xc7a100t --clock 100MHz
tri sacred bench --format gf16,fp16 --size 1000000
tri bench compare cpu.json fpga.json

Queen A/B Test

tri farm ab-test --control queen_disabled.json \
    --treatment queen_enabled.json --count 50 --duration 48h

Publications Plan

Paper	Status	Target Venue	DOI
Paper 1: Sacred GF16/TF3 + FPGA ALU	✅ Published	Zenodo 18939352	10.5281/zenodo.18950696
Paper 2: TRI-27 + Queen Self-Learning	🔄 In Progress	FPL 2026 / arXiv	—
Paper 3: Tri Language	🔄 In Progress	PLDI 2026	—

Code Integration

All documents linked to existing code:

• src/hslm/ — 4000 LOC, 74/74 tests passing
• src/tri27/ — 1250 LOC, 68/68 tests passing
• src/tri/queen/ — 788 LOC, 4/4 Self-Learning tests
• fpga/openxc7-synth/ — 900 LOC, Zero-DSP confirmed

Acceptance Criteria

• Directory docs/research/ created with 5 component docs
• Master framework doc (TRINITY_S3AI_UNIFIED_FRAMEWORK.md) created
• All 6 hypotheses (H1-H6) formulated with metrics
• Experimental pipelines described with commands
• Code map linked to actual files (paths, LOC, status)
• Publication targets outlined (Paper 1/2/3 with DOIs)

Estimated Effort

Task	Time	Status
Research docs creation	~5 hours	✅ Complete
Hypotheses formulation	~2 hours	✅ Complete
Pipeline documentation	~2 hours	✅ Complete
TOTAL	~9 hours	✅ Complete

References

• Master framework: `docs/research/TRINITY_S3AI_UNIFIED_FRAMEWORK.md`
• Component docs: `docs/research/*.md`
• Code sources: `src/hslm/`, `src/tri27/`, `src/tri/queen/`, `fpga/`

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φ² + 1/φ² = 3 | TRINITY

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✅ Phase Complete — All 6 Research Documents Created

Summary:

• ✅ trinity_s3ai_overview.md — ~350 LOC, S³ axes, 8-level stack
• ✅ tri27_platform.md — ~300 LOC, TRI-27 research platform
• ✅ queen_lotus_experiments.md — ~300 LOC, Lotus Cycle phases
• ✅ sacred_formats_fpga.md — ~300 LOC, GF16/TF3 specs
• ✅ tri_language_roadmap.md — ~250 LOC, Tri grammar
• ✅ TRINITY_S3AI_UNIFIED_FRAMEWORK.md — ~450 LOC, Master framework

Total: ~1950 LOC of scientific documentation

Documentation: All docs properly structured in docs/research/

Co-Authored-By: Claude Opus 4.6 noreply@anthropic.com