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Heterodyne 2.0.2.dev2 documentation
Heterodyne 2.0.2.dev2 documentation

User Guide

  • User Guide
    • Fundamentals
      • What Is XPCS?
      • Heterodyne Package Overview
      • Parameter Guide
    • Data and Fitting
      • Data Loading
      • NLSQ Fitting
      • Result Interpretation
    • Advanced Topics
      • Bayesian Inference
      • Per-Angle Scaling
      • CMA-ES Global Optimisation
      • Diagnostics and Convergence
    • Practical Guides
      • Configuration
      • Visualization
      • Performance Tuning
      • Batch Processing
    • Appendices
      • Troubleshooting
      • Frequently Asked Questions
      • Glossary

Theory & Physics

  • Theory & Physics
    • Transport Coefficient J(t)
    • Correlation Functions
    • Heterodyne Scattering Model
    • Classical Stochastic Processes
    • Computational Methods
    • Analysis Modes
    • Anti-Degeneracy Defense System
    • References

Configuration

  • Configuration
    • Configuration Templates
    • Configuration Options Reference

API Reference

  • API Reference
    • Core Physics
    • Heterodyne Model
    • JAX Backend
    • Model Hierarchy
    • Optimization
      • NLSQ Optimization
      • CMC (Bayesian)
    • Data
    • Configuration
    • CLI
    • Device Management
    • I/O Utilities
    • Visualization
    • Utilities

Examples

  • Examples

Developer Guide

  • Developer Guide
    • Contributing Guide
    • Testing Guide
    • Architecture Overview
    • Parameter Bounds Verification
    • Architecture Decision Records
      • ADR-001: JAX CPU-Only Backend
      • ADR-002: NLSQ / CMC Architectural Split
      • ADR-003: Anti-Degeneracy Layer for Velocity-Phase Model
      • ADR-004: Consensus Monte Carlo for Bayesian Inference
      • ADR-005: Per-Angle Scaling Modes
      • ADR-006: No GPU Acceleration on Consumer Hardware

Architecture Deep Dives

  • Architecture Deep Dives

Additional Resources

  • Installation
  • Quick Start
  • Contributing
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Advanced TopicsΒΆ

This section covers Bayesian inference, per-angle fitting modes, global optimisation with CMA-ES, and convergence diagnostics.

  • Bayesian Inference
  • Per-Angle Scaling
  • CMA-ES Global Optimisation
  • Diagnostics and Convergence
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Bayesian Inference
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Result Interpretation
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