• Corpus ID: 245668748

Deep Learning of DESI Mock Spectra to Find Damped Ly{\alpha} Systems

@inproceedings{Wang2022DeepLO,
  title={Deep Learning of DESI Mock Spectra to Find Damped Ly\{\alpha\} Systems},
  author={Ben Wang and Jiaqi Zou and Zheng Cai and Jason Xavier Prochaska and Zechang Sun and Jiani Ding and Andreu Font-Ribera and Alma Gonzalez and Hiram K. Herrera-Alcantar and Vid Ir{\vs}i{\vc} and Xiaojing Lin and David D. Brooks and Sol{\'e}ne Chabanier and Roger de Belsunce and Nathalie Palanque-Delabrouille and Gregory G. Tarl{\'e} and Zhi-min Zhou},
  year={2022}
}
We have updated and applied a convolutional neural network (CNN) machine learning model to discover and characterize damped Lyα systems (DLAs) based on Dark Energy Spectroscopic Instrument (DESI) mock spectra. We have optimized the training process and constructed a CNN model that yields a DLA classification accuracy above 99% for spectra which have signal-to-noise (S/N) above 5 per pixel. Classification accuracy is the rate of correct classifications. This accuracy remains above 97% for lower… 

References

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MASTER’S THESIS

The author of this thesis aimed at investigating the positive and negative effects of using social media through collecting the users' experiences and professionals' viewpoints, and identified other practical effects and aspects of social media.

2016a, arXiv e-prints, arXiv:1611.00036

  • 2016