Multiresolution and Hierarchical Analysis of Astronomical Spectroscopic Cubes using 3D Discrete Wavelet Transform

TL;DR

This paper introduces a multiresolution hierarchical analysis method for 3D astronomical spectroscopic cubes using wavelets and dendrograms, enabling automated source identification across scales in high-resolution data.

Contribution

It extends wavelet-based multiresolution analysis from 2D images to 3D spectroscopic data and combines it with dendrograms for hierarchical source connection representation.

Findings

Feasible to analyze spatial and spectral data simultaneously.

Effective in identifying sources at multiple scales.

Validated on real ALMA data.

Abstract

The intrinsically hierarchical and blended structure of interstellar molecular clouds, plus the always increasing resolution of astronomical instruments, demand advanced and automated pattern recognition techniques for identifying and connecting source components in spectroscopic cubes. We extend the work done in multiresolution analysis using Wavelets for astronomical 2D images to 3D spectroscopic cubes, combining the results with the Dendrograms approach to offer a hierarchical representation of connections between sources at different scale levels. We test our approach in real data from the ALMA observatory, exploring different Wavelet families and assessing the main parameter for source identification (i.e., RMS) at each level. Our approach shows that is feasible to perform multiresolution analysis for the spatial and frequency domains simultaneously rather than analyzing each spectral channel independently.