Application of regularized Alternating Least Squares to an astrophysical problem

Determination of the compounds that are present in molecular clouds is carried out from the study of the infrared spectrum of astrophysical ices. This analysis plays a fundamental role in the prediction of the future evolution of the cloud under study. The process is simulated in the laboratory under similar conditions of thermal and energetic processing, recording the infrared absorption spectrum of the resultant ice. The spectrum of each ice can be modeled as the linear instantaneous superposition of the spectrum of the different compounds, so a Source Separation approach is appropriate. We propose the use of Alternating Least Squares and a Regularized version to identify the molecules that are present in the ice mixtures. Since the spectra and abundances are non-negative, a non-negativity constraint can be applied to obtain solutions with physical meaning. We perform several simulations of synthetic and real mixtures of ices in order to compare both solutions and to show how the proposed approach provides an efficient way to recover underlying spectral patterns that are physically meaningful.