Wavelet theory applied to the study of spectra of trans-Neptunian objects

Abstract

Context. Reflection spectroscopy in the near-infrared (NIR) is used to investigate the surface composition of trans-Neptunian objects (TNOs). In general, these spectra are difficult to interpret due to the low apparent brightness of the TNOs, causing low signal-to-noise ratio even in spectra obtained with the largest telescopes available on Earth, making it necessary to use filtering techniques to analyze and interpret them. Aims. The purpose of this paper is to present a methodology to analyze the spectra of TNOs. Specifically, our aim was to filter these spectra in the best possible way: maximizing noise removal, while minimizing the loss of signal. Methods. We used wavelets to filter the spectra. Wavelets are a mathematical tool that decompose the signal into its constituent parts, allowing us to analyze the data in different areas of frequencies with the resolution of each component tied to its scale. To check the reliability of our method, we compared the filtered spectra with the spectra of water and methanol ices to identify some common structures between them. Results. Of the 50 TNOs in our sample, we identify traces of water ices and methanol in the spectra of several of them, some with previous reports, while for other objects there were no previous reports. Conclusions. We conclude that the wavelet technique is successful in filtering spectra of TNOs.