refactor: move all remaining files to orig/ directory

Completed clean root directory structure:
- Root now contains only: .git, .env, docs/, orig/
- Moved all remaining files and directories to orig/:
  - Config files (.claude, .dockerignore, .drone.yml, etc.)
  - All .env variants (except active .env)
  - Git config (.gitconfig, .github, .gitignore, etc.)
  - Tool configs (.golangci.yml, .revive.toml, etc.)
  - Documentation (*.md files, @prompts)
  - Build files (Dockerfiles, Makefile, go.mod, go.sum)
  - Docker compose files
  - All source directories (scripts, tests, tools, etc.)
  - Runtime directories (logs, monitoring, reports)
  - Dependency files (node_modules, lib, cache)
  - Special files (--delete)

- Removed empty runtime directories (bin/, data/)

V2 structure is now clean:
- docs/planning/ - V2 planning documents
- orig/ - Complete V1 codebase preserved
- .env - Active environment config (not in git)

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

orig/.qwen/PROJECT_SUMMARY.md

@@ -0,0 +1,41 @@
+# Mathematical Optimization Summary
+
+## Work Completed
+
+1. **Performance Analysis**: Conducted comprehensive benchmarks and profiling of Uniswap V3 pricing functions
+2. **Optimization Implementation**: Created optimized versions of key mathematical functions using constant caching
+3. **Testing & Validation**: Implemented comprehensive test suites to verify accuracy of optimizations
+4. **Documentation**: Created detailed documentation of optimizations and performance analysis
+5. **Integration**: Updated project documentation to reference the optimizations
+
+## Key Results
+
+### Performance Improvements
+- **SqrtPriceX96ToPriceCached**: 24% faster than original (1406 ns/op → 1060 ns/op)
+- **PriceToSqrtPriceX96Cached**: 19% faster than original (1324 ns/op → 1072 ns/op)
+- **Memory Allocations**: Reduced by 20-33% across all optimized functions
+
+### Technical Insights
+- **Caching Strategy**: Precomputing expensive constants (`2^96`, `2^192`) was the most effective optimization
+- **Memory Bottleneck**: Profiling revealed memory allocation as the primary performance bottleneck
+- **Uint256 Overhead**: Attempts to optimize with uint256 operations were unsuccessful due to conversion overhead
+
+## Files Created
+- `pkg/uniswap/cached.go` - Cached versions of mathematical functions
+- `pkg/uniswap/optimized.go` - Alternative optimization approaches
+- `pkg/uniswap/pricing_bench_test.go` - Benchmarks for original functions
+- `pkg/uniswap/cached_bench_test.go` - Benchmarks for cached functions
+- `pkg/uniswap/optimized_bench_test.go` - Benchmarks for optimized functions
+- `pkg/uniswap/roundtrip_test.go` - Round-trip conversion accuracy tests
+- `pkg/uniswap/cached_test.go` - Accuracy tests for cached functions
+- `pkg/uniswap/optimized_test.go` - Accuracy tests for optimized functions
+- `docs/MATH_OPTIMIZATIONS.md` - Documentation of mathematical optimizations
+- `docs/MATH_PERFORMANCE_ANALYSIS.md` - Detailed performance analysis report
+
+## Integration
+- Updated `README.md` to reference mathematical optimizations
+- Updated `.qwen/QWEN.md` to include caching as an optimization target
+- Committed all changes with proper conventional commit formatting
+
+## Impact
+These optimizations will significantly improve the performance of the MEV bot, especially during high-frequency arbitrage detection where these mathematical functions are called repeatedly. The 19-24% performance improvements, combined with reduced memory allocations, will allow the bot to process more opportunities with lower latency and resource usage.