Discovering Ca II Absorption Lines With a Neural Network

TL;DR

This paper presents a deep learning approach using a convolutional neural network to efficiently detect Ca II absorption lines in quasar spectra, significantly outperforming traditional methods in speed and accuracy.

Contribution

The authors developed a novel deep learning model trained on simulated data that accurately identifies Ca II absorbers, discovering 399 new cases and confirming 409 known ones.

Findings

Achieved 96% accuracy on real SDSS data

Ran thousands of times faster than traditional detection methods

Discovered 399 new Ca II absorbers in quasar spectra

Abstract

Quasar absorption line analysis is critical for studying gas and dust components and their physical and chemical properties as well as the evolution and formation of galaxies in the early universe. Ca II absorbers, which are one of the dustiest absorbers and are located at lower redshifts than most other absorbers, are especially valuable when studying physical processes and conditions in recent galaxies. However, the number of known quasar Ca II absorbers is relatively low due to the difficulty of detecting them with traditional methods. In this work, we developed an accurate and quick approach to search for Ca II absorption lines using deep learning. In our deep learning model, a convolutional neural network, tuned using simulated data, is used for the classification task. The simulated training data are generated by inserting artificial Ca II absorption lines into original quasar spectra from the Sloan Digital Sky Survey (SDSS) whilst an existing Ca II catalog is adopted as the test set. The resulting model achieves an accuracy of 96% on the real data in the test set. Our solution runs thousands of times faster than traditional methods, taking a fraction of a second to analyze thousands of quasars while traditional methods may take days to weeks. The trained neural network is applied to quasar spectra from SDSS's DR7 and DR12 and discovered 399 new quasar Ca II absorbers. In addition, we confirmed 409 known quasar Ca II absorbers identified previously by other research groups through traditional methods.