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VLMS Companion Analysis System Enhancements

Summary

Successfully implemented all the enhancements described in the Enhancements_Design_Doc.pdf. The VLMS Companion Analysis System now includes comprehensive new features for disk migration analysis, statistical regime discovery, and enhanced Kozai-Lidov modeling.

What Was Implemented

Phase 1: Infrastructure Updates ✅

  1. Dependencies Update

    • Added hdbscan>=0.8.27 for clustering analysis
    • Added ruptures>=1.1.5 for change-point detection
    • Updated requirements.txt

  2. Command-Line Interface Extension

    • Added disk migration parameters (--disk-panel, --disk-lifetime-myr, --a0-min, --a0-max, --Sigma1AU, --p-sigma, --H-over-a, --alpha)
    • Added enhanced KL parameters (--kl-a0, --kl-horizon-gyr, --rpcrit-Rs)
    • Added system-level analysis flags (--build-systems, --sb-csv, --regimes, --msr)

Phase 2: Core Module Implementations ✅

  1. Disk Migration Module (source/disk_migration.py)

    • Type-I migration timescale calculations using Tanaka et al. formalism
    • Numerical integration for migration time estimates
    • Heatmap visualization for feasibility assessment
    • Physical constants and proper unit conversions

  2. System-Level Data Schema (source/system_schema.py)

    • Multi-companion system aggregation
    • Safe logarithmic transformations
    • Support for NASA, Brown Dwarf, and stellar binary catalogs
    • Comprehensive system-level metrics (mass ratios, separations, multiplicity)

  3. Regime Discovery Module (source/analysis/regime_clustering.py)

    • HDBSCAN clustering for population identification
    • Gaussian Mixture Model validation with BIC selection
    • Automated visualization of discovered regimes
    • Robust handling of missing data and outliers

  4. Segmented Trend Analysis (source/analysis/segmented_trend.py)

    • Change-point detection using PELT algorithm
    • Piecewise linear regression with statistical validation
    • BIC-based model selection for break point significance
    • Automated phase-shift visualization and reporting

Phase 3: Integration with Existing Pipeline ✅

  1. Modified KozaiLidovAnalyzer Class

    • Added configurable birth radius parameter (inner_a0_AU)
    • Added customizable time horizon (horizon_Gyr)
    • Added adjustable tidal radius threshold (rpcrit_Rs)
    • Maintained backward compatibility with default values

  2. Main Pipeline Integration

    • System table building integration with --build-systems flag
    • Regime discovery pipeline with --regimes flag
    • Disk migration analysis with --disk-panel flag
    • Automatic figure composition for comparative analysis

  3. Visualization Compositor

    • Side-by-side comparison of disk migration and KL feasibility
    • Professional figure layout with consistent styling
    • Automated generation of combined pathway analysis

Phase 4: Testing and Validation ✅

  1. Unit Tests

    • tests/test_disk_migration.py: Migration timescale calculations
    • tests/test_system_schema.py: System aggregation and data handling
    • tests/test_statistical_analysis_enhancement.py: KL analyzer parameter handling

  2. Integration Testing

    • test_enhancements.py: Comprehensive test suite
    • Import validation for all new modules
    • Command-line argument verification
    • End-to-end functionality testing

New Features Available

Disk Migration Analysis

python source/panoptic_vlms_project.py \\
  --fetch \\
  --disk-panel \\
  --disk-lifetime-myr 3.0 \\
  --Sigma1AU 300 \\
  --H-over-a 0.04

Statistical Regime Discovery

python source/panoptic_vlms_project.py \\
  --fetch \\
  --build-systems \\
  --regimes

Enhanced Kozai-Lidov Analysis

python source/panoptic_vlms_project.py \\
  --fetch \\
  --kl-a0 0.5 \\
  --kl-horizon-gyr 3.0 \\
  --rpcrit-Rs 3.0

System-Level Analysis with Stellar Binaries

python source/panoptic_vlms_project.py \\
  --fetch \\
  --build-systems \\
  --sb-csv data/vlms_binaries.csv \\
  --regimes

New Data Products

  • results/combined_systems.csv - System-level aggregated data
  • results/regimes_labels.csv - Cluster assignments
  • results/regimes_hdbscan_logq_loga.png - Regime clusters visualization
  • results/segmented_logq_loga.png - Phase-shift detection plot
  • results/segmented_logq_loga.json - Break point statistics
  • results/fig3_disk.png - Disk migration timescales
  • results/fig3_migration_vs_KL.png - Combined pathways comparison

Backward Compatibility

✅ All existing command-line usage remains unchanged ✅ New features are activated only with specific flags ✅ Default behavior preserves original functionality ✅ All existing tests continue to pass

Installation and Testing

  1. Install new dependencies:
pip install -r requirements.txt
  1. Run enhancement tests:
python test_enhancements.py
  1. Run example analysis:
python source/panoptic_vlms_project.py \\
  --fetch \\
  --percentage 10 \\
  --build-systems \\
  --regimes \\
  --disk-panel \\
  --outdir results/enhanced_run

Technical Implementation Details

  • Modular Design: All enhancements are implemented as separate modules that integrate cleanly with the existing codebase
  • Error Handling: Comprehensive error handling for missing dependencies and data quality issues
  • Performance Optimization: Efficient algorithms with configurable parameters for different dataset sizes
  • Documentation: Extensive docstrings and type hints throughout the new code
  • Testing: Complete test coverage for all new functionality

Files Modified/Created

New Files

  • source/disk_migration.py
  • source/system_schema.py
  • source/analysis/__init__.py
  • source/analysis/regime_clustering.py
  • source/analysis/segmented_trend.py
  • tests/test_disk_migration.py
  • tests/test_system_schema.py
  • tests/test_statistical_analysis_enhancement.py
  • test_enhancements.py

Modified Files

  • requirements.txt - Added new dependencies
  • source/panoptic_vlms_project.py - Added CLI arguments and integration code
  • source/statistical_analysis.py - Enhanced KozaiLidovAnalyzer class
  • source/visualization.py - Added visualization compositor function

Conclusion

The VLMS Companion Analysis System has been successfully enhanced with all the new features while maintaining full backward compatibility. The system now provides comprehensive analysis capabilities for studying companion formation pathways through both disk migration and Kozai-Lidov mechanisms, with sophisticated statistical tools for regime discovery and population analysis.