feat: vendor midstream and sublinear-time-solver libraries

Add ruvnet/midstream (AIMDS real-time inference) and
ruvnet/sublinear-time-solver (sublinear optimization algorithms)
as vendored dependencies under vendor/.

Co-Authored-By: claude-flow <ruv@ruv.net>

vendor/sublinear-time-solver/validation/README.md

@@ -0,0 +1,150 @@
+# Psycho-Symbolic Reasoner Performance Validation Suite
+
+## Overview
+
+This validation suite provides **verifiable proof** of the Psycho-Symbolic Reasoner's performance claims through reproducible benchmarks and comparisons with traditional AI reasoning systems.
+
+## Key Performance Claims (Verified)
+
+- **Simple Query**: 0.3ms (500x faster than GPT-4)
+- **Complex Reasoning**: 2.1ms (380x faster than GPT-4)
+- **Graph Traversal**: 1.2ms
+- **GOAP Planning**: 1.8ms
+
+## Quick Start
+
+```bash
+# Install dependencies
+npm install
+
+# Run all benchmarks
+npm run benchmark:all
+
+# Generate performance report
+npm run report:generate
+```
+
+## Benchmark Scripts
+
+### Individual Benchmarks
+
+```bash
+# Psycho-Symbolic Reasoner benchmarks
+npm run benchmark:psycho
+
+# Traditional systems simulation
+npm run benchmark:traditional
+
+# Performance verification
+npm run benchmark:verify
+```
+
+### Docker Execution
+
+```bash
+# Build Docker image
+npm run docker:build
+
+# Run benchmarks in Docker
+npm run docker:run
+```
+
+## Verification Methodology
+
+### 1. Direct Measurement
+- Psycho-Symbolic operations measured with high-resolution timers
+- 10,000-100,000 iterations per test
+- Statistical analysis (mean, median, P95, P99)
+
+### 2. Traditional System Simulation
+- Based on published performance data
+- Simulates realistic latencies
+- Includes network overhead for cloud services
+
+### 3. Comparison Analysis
+- Side-by-side performance comparison
+- Speedup calculations
+- Statistical validation
+
+## Results Structure
+
+```
+validation/
+├── benchmarks/           # Benchmark scripts
+│   ├── psycho-symbolic-bench.js
+│   ├── traditional-bench.js
+│   ├── verify-claims.js
+│   └── run-all.js
+├── results/             # Generated results
+│   ├── psycho-symbolic-*.json
+│   ├── traditional-systems-*.json
+│   ├── verification-report-*.json
+│   ├── PERFORMANCE_VERIFICATION.md
+│   └── PERFORMANCE_VERIFICATION.html
+└── scripts/            # Utility scripts
+    └── generate-report.js
+```
+
+## Performance Comparison
+
+| System | Typical Latency | Psycho-Symbolic | Improvement |
+|--------|----------------|-----------------|-------------|
+| GPT-4 (Simple) | 150-300ms | 0.3ms | **500-1000x** |
+| GPT-4 (Complex) | 500-800ms | 2.1ms | **238-380x** |
+| Neural Theorem Prover | 200-2000ms | 2.1ms | **95-950x** |
+| Prolog | 5-50ms | 0.3ms | **17-167x** |
+| CLIPS/JESS | 8-45ms | 1.2ms | **7-38x** |
+
+## Reproducibility
+
+### Environment Requirements
+- Node.js 20+
+- 2GB RAM minimum
+- x64 or ARM64 architecture
+
+### Statistical Significance
+- Minimum 10,000 iterations per test
+- Warmup phase to eliminate JIT compilation effects
+- Multiple statistical measures for validation
+
+### High-Resolution Timing
+- Uses `process.hrtime.bigint()` for nanosecond precision
+- `performance.now()` for millisecond measurements
+- Cross-validation between timing methods
+
+## Understanding the Results
+
+### Metrics Explained
+- **Mean**: Average execution time
+- **Median**: Middle value (less affected by outliers)
+- **P95/P99**: 95th/99th percentile (worst-case scenarios)
+- **StdDev**: Standard deviation (consistency measure)
+
+### Why These Numbers Are Achievable
+
+1. **In-Memory Operations**: No network latency
+2. **Optimized Data Structures**: Efficient Maps and Sets
+3. **No LLM Overhead**: Direct algorithmic execution
+4. **Native JavaScript**: JIT-compiled performance
+5. **Caching**: Smart memoization strategies
+
+## Verification Reports
+
+After running benchmarks, find detailed reports in `results/`:
+
+- **JSON Files**: Raw benchmark data with timestamps
+- **Markdown Report**: Human-readable performance analysis
+- **HTML Report**: Visual presentation with charts
+
+## Contributing
+
+To add new benchmarks or improve verification:
+
+1. Add test cases to relevant benchmark files
+2. Ensure statistical significance (>10,000 iterations)
+3. Document methodology and data sources
+4. Submit PR with benchmark results
+
+## License
+
+MIT - See LICENSE file for details