Deep learning of quasar spectra to discover and characterize damped Lyα systems-Reference-Cited by-同舟云学术

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Deep learning of quasar spectra to discover and characterize damped Lyα systems

Published:2018-01-29 Issue:1 Volume:476 Page:1151-1168
ISSN:0035-8711
Container-title:Monthly Notices of the Royal Astronomical Society
language:en
Short-container-title:

Author:

Parks David¹,Prochaska J Xavier²,Dong Shawfeng³,Cai Zheng²

Affiliation:

1. Computer Science, UC Santa Cruz, 1156 High St., Santa Cruz, CA 95064, USA

2. Astronomy and Astrophysics, UC Santa Cruz, 1156 High St., Santa Cruz, CA 95064, USA

3. Applied Mathematics and Statistics, UC Santa Cruz, 1156 High St., Santa Cruz, CA 95064, USA

Funder

NSF

Publisher

Oxford University Press (OUP)

Subject

Space and Planetary Science,Astronomy and Astrophysics

Link

http://academic.oup.com/mnras/article-pdf/476/1/1151/24261051/sty196.pdf

Reference39 articles.

1. A study of the behavior of several methods for balancing machine learning training data

2. Statistical properties of damped Lyman-alpha systems from Sloan Digital Sky Survey DR12

3. A GLIMPSE AT QUASAR HOST GALAXY FAR-UV EMISSION USING DAMPED Lyα's AS NATURAL CORONAGRAPHS

4. MAPPING THE MOST MASSIVE OVERDENSITY THROUGH HYDROGEN (MAMMOTH). I. METHODOLOGY

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