ELISA

Efficient Likelihood Inference for Stellar Ages

ELISA is a Python package for Bayesian inference of stellar cluster parameters from Gaia photometry. It provides two complementary inference engines:

• MCMC isochrone fitting — infers cluster-level parameters (age, metallicity, distance modulus, extinction) by fitting PARSEC isochrones with emcee.

• Binary-star SBI — estimates individual star parameters (primary mass, mass ratio) using Simulation-Based Inference with neural posterior estimation.

Contents

• Installation
  • Requirements
  • From Source
  • Optional Dependencies
• Quick Start
  • Step 1: Download an Isochrone Grid
  • Step 2: Load Observed Data
  • Step 3: Set Up the Posterior
  • Step 4: Run MCMC
  • Step 5: Analyze Results
• Binary Star SBI
  • Workflow Overview
  • Step 1: Load Stellar Tracks
  • Step 2: Build Error Splines
  • Step 3: Define a Prior
  • Step 4: Train the Posterior
  • Step 5: Run Inference
  • Full Example
• API Reference
  • ElisaClusterInference
  • Posterior
  • ElisaBinary
  • StellarPrior
  • build_error_splines
  • ElisaQuery