Spectral Line Identification and Modelling (SLIM) in the MAdrid Data CUBe Analysis (MADCUBA) package: An interactive software for data cube analysis

TL;DR

This paper introduces MADCUBA and SLIM, interactive software tools that facilitate visualization, analysis, and modeling of large spectroscopic data cubes, enabling detailed physical parameter extraction using LTE models and automatic fitting algorithms.

Contribution

The paper presents a comprehensive, interactive software package with advanced modeling and fitting capabilities for spectroscopic data cubes, including a stand-alone database and full radiative transfer modeling.

Findings

SLIM provides accurate LTE synthetic spectra generation.

The software enables automatic fitting of physical parameters.

It allows interactive exploration of parameter uncertainties.

Abstract

In this paper we present the detailed formalism at the core of the Spectral Line Identification and Modelling (SLIM) within the MAdrid Data CUBe Analysis (MADCUBA) package and their main data handling functionalities. These tools have been developed to visualize, analyze and model large spectroscopic data cubes. We present the highly interactive on-the-fly visualization and modelling tools of MADCUBA and SLIM, which includes an stand-alone spectroscopic database. The parameters stored therein are used to solve the full radiative transfer equation under Local Thermodynamic Equilibrium (LTE). SLIM provides tools to generate synthetic LTE model spectra based on input physical parameters of column density, excitation temperature, velocity, line width and source size. SLIM also provides an automatic fitting algorithm to obtain the physical parameters (with their associated errors) better fitting the observations. Synthetic spectra can be overlayed in the data cubes/spectra to easy the task of multi-molecular line identification and modelling.We present the Java-based MADCUBA and its internal module SLIM packages which provide all the necessary tools for manipulation and analysis of spectroscopic data cubes. We describe in detail the spectroscopic fitting equations and make use of this tool to explore the breaking conditions and implicit errors of commonly used approximations in the literature. Easy-to-use tools like MADCUBA allow the users to derive the physical information from spectroscopic data without the need of resourcing to simple approximations. SLIM allows to use the full radiative transfer equation, and to interactively explore the space of physical parameters and associated uncertainties from observational data.