Searching for Rare Quasar Ca II Absorbers in the Early Universe

The universe is still largely a mystery to scientists. Quasars are one such mystery, whose emission spectra produce absorption lines such as Ca II when passing through gas of distant galaxies. This data helps astronomers understand more about interstellar gas, dust, and galaxy and star formation and evolution (including my Milky Way). However, these current absorber databases are extremely limited, and traditional methods make them hard to detect. Thus, I seek to discover more Ca II absorbers by developing deep neural networks, which are more accurate and faster. I first found absorbers traditionally to produce a test set. I cropped, normalized, and handpicked through thousands of spectra and discovered 256 Ca II original absorbers. To obtain large training sets, I generated tens of thousands of artificial samples by inserting Ca II lines at corresponding wavelengths in real spectra. I preprocessed the data and created neural network models after testing different hyperparameter configurations. Overall, my accuracy for absorber detection is 95% (Ca II), 15 times higher than traditional methods, and I added significant amounts of new absorbers to the current dataset for Ca II, completing my goal. As for challenges, I concluded that most false negatives are due to noise and weak lines. Furthermore, my discovered absorbers agree with statistical tests of previous studies. In the future, I plan to discover more absorbers using my models and run statistical studies on them.