The PCA Filtering method for an unbiased spectral survey of Complex Organic Molecules (COMs)
Hyeong-Sik Yun, Jeong-Eun Lee

TL;DR
This paper introduces a PCA-based filtering technique to extract and enhance spectra of complex organic molecules in interstellar environments, improving signal-to-noise ratios while preserving line intensities.
Contribution
The novel PCA filtering method effectively isolates COM spectra from kinematic effects, outperforming previous methods by maintaining line intensities and reducing noise.
Findings
Reduces spectral noise by a factor of ~2.
Successfully extracts high-SNR spectra of COMs in V883 Ori.
Preserves original integrated line intensities.
Abstract
A variety of interstellar complex organic molecules (COMs) have been detected in various physical conditions. However, in the protostellar and protoplanetary environments, their complex kinematics make line profiles blend each other and the line strength of weak lines weaker. In this paper, we utilize the principal component analysis (PCA) technique to develop a filtering method which can extract COM spectra from the main kinematic component associated with COM emission and increase the signal-to-noise ratio (SNR) of spectra. This filtering method corrects non-Gaussian line profiles caused by the kinematics. For this development, we adopt the ALMA BAND 6 spectral survey data of V883 Ori, an eruptive young star with a Keplerian disk. A filter was, first, created using 34 strong and well-isolated COM lines and then applied to the entire spectral range of the dataset. The first principal…
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Taxonomy
TopicsSpectroscopy and Laser Applications · Astrophysics and Star Formation Studies
