Documentation of INFUSE

Authors: Fabio Rosario Ditrani

Date: 14/12/2025

Introduction

Project Name: INFUSE

INFUSE (Full-INdex Fitting for Uncovering Stellar Evolution) is a Python-based tool designed to infer stellar population properties from observed spectra of galaxies and stellar systems. The code performs a full-index fitting analysis by comparing observed spectral indices with predictions from stellar population synthesis (SPS) models (e.g. sMILES). INFUSE uses a nested sampling algorithm to efficiently explore the multi-dimensional parameter space and to derive robust posterior probability distributions for the stellar population parameters.

Installation

Requirements:

  • Python version: >=3.8

  • Dependencies: numpy, corner, astropy, ultranest, matplotlib

Steps to Install:

Clone the repository and run the main script from the repository root:

```bash git clone https://github.com/FabioDitrani/INFUSE.git cd INFUSE python infuse.py

Directory Contents

The github distribution includes a INFUSE/ directory that contains the following codes:

  • INFUSE.py: The main Python file containing the code for the extraction process.

  • models: Folder containing the stellar population models.

  • Functions.py: The Python file containing all the functions and class used in INFUSE.py.

Main Features

  • Reading and handling observed spectra

  • Loading stellar population synthesis models (e.g. sMILES)

  • Measurement and selection of spectral indices

  • Full-index fitting between models and observations

  • Bayesian inference using nested sampling

  • Diagnostic plots to inspect posterior distributions

  • Control plots comparing observed and best-fit spectral indices

Scientific Method

INFUSE implements a generalised full-index fitting approach based on a pixel-by-pixel flux comparison restricted to selected spectral features.

For each spectral index, both the observed spectrum and the SPS model spectra are normalised to the pseudo-continuum defined by the classical index bandpasses. The fitting is then performed by comparing the flux values at each wavelength pixel within the index feature window, rather than by directly comparing integrated index measurements.

The likelihood function is constructed by evaluating the agreement between the continuum-normalized observed and model fluxes within the selected index regions, taking into account the observational uncertainties at each pixel.

This approach preserves the conceptual framework of classical absorption-line index analysis, while extending it to a more flexible and information-rich fitting scheme.

The posterior distribution of the model parameters is sampled using a nested sampling approach, allowing for:

  • efficient parameter space exploration

  • evidence computation

  • robust uncertainty estimates

Applications

INFUSE is suited for:

  • Stellar population analysis of galaxies

  • studies of age, metallicity, and abundance patterns

  • comparison of different SPS model libraries

  • testing spectral diagnostics based on absorption-line indices

Changelog

Contributing

If you are interested in contributing to the project, please contact us and follow these steps:

  1. Fork the repository on GitHub.

  2. Create a new branch for your feature/bugfix.

  3. Submit a pull request.

API

None

License

Copyright (C) 2024 The Authors

This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License.