#----  CATALOGS PRESENTATION ----#
The four lists contain sources selected as genuine Lyman-alpha emitting
candidates by the methodology detailed in Spinoso et al. (2020). In brief,
the J-PLUS narrow-bands J0395, J0410, J0430 and J0515 were used to
detect photometric excesses of sources within the DR1 dual-mode catalog
parent sample. This excess and its significance was estimated by using
the method detailed in Vilella-Rojo et al. (2015) and discussed in
Logrono-Garcia et al. (2019). Each of the four NBs were used to target
Lyman-alpha emission, respectively at redshift z=2.2, z=2.4, z=2.5 and
z=3.2. After the first selection based on the NB-excess significance of
each source, the resulting lists of objects were cleaned from the
presence of known interlopers, namely low-z galaxies, stars and AGN/QSOs
outside the redshift intervals probed by the narrow-bands for Lyman-alpha
emission. All the above steps are extensively detailed in Spinoso et al.
(2020). The four lists presented in this page include only the genuine
Lya-emitting candidates. These are defined as the sources selected on
the basis of their reliable NB excess, which do not present any
identification as low-z interlopers. We stress that genuine candidates
include Lya-emitting QSOs belonging to the SDSS spectroscopic sample
(Paris et al. - 2018), with redshift compatible to Lya-emission in the
wavelength ranges probed by each narrow-band.

#---- DATA FORMAT ----#
Each list is provided as an hdf5 binary file. These can be easily accessed
by using the "deepdish" python package and using the following commands:

  import deepdish as dd
  data = dd.io.load( path/to/filename )

in this way, single data columns are loaded as nD-arrays into the
dictionary-like structure "data" and can be accessed through their
keys, simply as e.g.:

  data['ALPHA_J2000']   --> RA column (one value per object)
  data['DELTA_J2000']   --> DEC column (one value per object)
  data['LYA_FLUX']      --> photometric estimate of the candidates Lyman-alpha flux

The following enumeration describes the data column associated to each
hdf5 key:

  'TILE_ID'         : int     : Identifier of the Tile image where the object was detected.
  'NUMBER'          : int     : Number identifier assigned by Sextractor for the object in the image.
  'ALPHA_J200'      : float   : Right ascension in equatorial coordinates.
  'DELTA_J200'      : float   : Declination in equatorial coordinates.
  'LYA_FLUX'        : float   : [erg cm^-2 s^-1] - photometric estimate of the integrated line-flux, corrected
                              : for filter-width losses (see Spinoso et al. 2020).
  'LYA_FLUX_ERR'    : float   : [erg cm^-2 s^-1] - error on 'LYA_FLUX' (see Spinoso et al. 2020).
  'LYA_LUM'         : float   : [erg s^-1] - Lya luminosity computed from the sources 'LYA_FLUX'and redshift
                                (see below) as detailed in Spinoso et al. (2020).
  'LYA_LUM_ERR'     : float   : [erg s^-1] - error on 'LYA_LUM' (see Spinoso et al. 2020).
  'LYA_EW'          : float   : [Angstrom] - Lya equivalent width; EW = 'LYA_FLUX'/NB_continuum, where NB_continuum
                                is computed with the method of Vilella-Rojo et al. 2015 (see Spinoso et al. 2020).
  'Z'               : float   : sources redshift assuming detection at the narrow-band central wavelength. For
                    :           objects with SDSS counterpart, 'Z' is equal to the SDSS zspec (Paris et al. 2018).
  'Z_ERR'           : float   : redshift error, namely half of the narrow-band FWHM for sources without SDSS
                    :           counterparts, otherwise 'Z_ERR' is the value given by SDSS (Paris et al. 2018).
  'SDSS_QSO'        : boolean : flag identifying the presence of SDSS QSOs counterparts (at any z).
  'SDSS_RIGHTz_QSO' : boolean : flag identifying the presence of SDSS QSOs counterparts (at the redshift
                                sampled by the NB used to select the candidates).
  'LQAC_QSO'        : boolean : flag identifying the presence of LQAC (Souchay et al. 2015) QSOs counterparts
                                (at any z).
  'WISE_QSO'        : boolean : Flag identifying the presence of counterparts in the allWISE catalog
                                (Wright et al. 2010), with WISE colors compatible with QSO color locus.
  'XRAY_SOURCE'     : boolean : Flag identifying the presence of X-ray counterparts in the 2RXS and XMMSLEW2
                                catalogs (Salvato et al. 2018)
  

Mathematical operations involving float "data" columns are possible.
Boolean "data" columns can be used as logic masks and/or combined:

  #- operation example -#
  rest_frame_EW = data['LYA_EW'] / (1. + data['Z'])

  #- masking example: selecting lya_flux of only candidates with x-ray counterparts -#
  lya_flux_xray_matches = data['LYA_FLUX'][ data['XRAY_SOURCE'] ]
  
  #- combining boolean masks: sources with both counterparts in SDSS QSOs and X-RAY catalogs -#
  qsos_and_xray_mask = ( data['SDSS_QSO'] & data['XRAY_SOURCE' ] )