J/MNRAS/498/1951  Lyman limit systems in large quasar surveys (Fumagalli+, 2020)

Detecting neutral hydrogen at z≳3 in large spectroscopic surveys of quasars. Fumagalli M., Fotopoulou S., Thomson L. <Mon. Not. R. Astron. Soc., 498, 1951-1962 (2020)> =2020MNRAS.498.1951F 2020MNRAS.498.1951F (SIMBAD/NED BibCode)
ADC_Keywords: QSOs ; Redshifts ; Intergalactic medium ; Spectra, optical Keywords: methods: data analysis - galaxies: haloes - intergalactic medium - quasars: absorption lines Abstract: We present a pipeline based on a random forest classifier for the identification of high column density clouds of neutral hydrogen (i.e. the Lyman limit systems, LLSs) in absorption within large spectroscopic surveys of z≳3 quasars. We test the performance of this method on mock quasar spectra that reproduce the expected data quality of the Dark Energy Spectroscopic Instrument and the WHT (William Herschel Telescope) Enhanced Area Velocity Explorer surveys, finding ≳90 per cent completeness and purity for NHI≳1017.2cm-2 LLSs against quasars of g<23mag at z∼3.5-3.7. After training and applying our method on 10000 quasar spectra at z∼3.5-4.0 from the Sloan Digital Sky Survey (Data Release 16), we identify ∼6600 LLSs with NHI≳1017.5cm-2 between z∼3.1 and 4.0 with a completeness and purity of ≳90 per cent for the classification of LLSs. Using this sample, we measure a number of LLSs per unit redshift of l(z)=2.32±0.08 at z=[3.3,3.6]. We also present results on the performance of random forest for the measurement of the LLS redshifts and HI column densities, and for the identification of broad absorption line quasars. Description: We present the development of a pipeline designed to identify and measure the physical properties of τ≥>2 LLSs in large surveys. Differently from previous searches for strong absorption line systems like DLAs that target the characteristic shape of the Ly α absorption line, we rely on the distinctive flux drop at the Lyman limit around 912Å in the system's rest frame. Algorithmically, we choose the random forest implementation in scikit-learn using the classifier for the identification of LLSs and the regressor for the measurements of physical properties (redshift and column density). To test the reliability of the results and to develop the pipeline, we build a library of 180000 mock quasar spectra including DLAs and LLSs, with data quality comparable to that achievable in upcoming surveys such as DESI and WEAVE. We apply the developed pipeline to ∼10000 SDSS DR16 spectra observed with the BOSS spectrograph (Dawson et al. 2013AJ....145...10D 2013AJ....145...10D) and classified as quasars by the automatic pipeline (Bolton et al. 2012AJ....144..144B 2012AJ....144..144B). In the full sample, we allow for duplication of spectra for quasars that have been observed more than once. For this proof-of-concept analysis, we elect the redshift range 3.5=<z=<4.0, which offers optimal coverage of the Lyman limit down to z∼3 and includes a sufficiently large number of quasars. File Summary: -------------------------------------------------------------------------------- FileName Lrecl Records Explanations -------------------------------------------------------------------------------- ReadMe 80 . This file table1.dat 67 9911 Final classification for the full sample -------------------------------------------------------------------------------- See also: VII/289 : SDSS quasar catalog, sixteenth data release (DR16Q) (Lyke+, 2020) Byte-by-byte Description of file: table1.dat -------------------------------------------------------------------------------- Bytes Format Units Label Explanations -------------------------------------------------------------------------------- 1- 21 A21 --- Name Quasar name in the SDSS convention (spec-Plate-MJD-Fiber) 23- 31 F9.5 deg RAdeg Right ascension (J2000) 33- 43 F11.7 deg DEdeg Declination (J2000) 45- 49 F5.3 --- z Quasar redshift from the SDSS pipeline 51- 55 F5.1 --- S/N Signal to noise ratio measured at 1150Å in the quasar rest-frame 57 A1 --- Primary [Y/N] Flag indicating if the quasar is a "Science Primary" observation 59 A1 --- Train [Y/N] Flag indicating if the quasar is included in the training set 61 I1 --- Class Flag describing the outcome of the classification (1) 63- 67 F5.3 --- zLLS Measured redshift of the Lyman limit system (LLS) -------------------------------------------------------------------------------- Note (1): Class as follows: 1 = quasar with LLS 2 = quasar without LLS 4 = non-quasar -------------------------------------------------------------------------------- History: From electronic version of the journal
(End) Ana Fiallos [CDS] 03-Aug-2023
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