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In this repository, we describe the most basic routines to use GALAH Data Release 2.

License: GNU General Public License v3.0

galah_dr2's Introduction

GALAH_DR2

In this repository, we describe the most basic routines to use GALAH Data Release 2. The GALAH collaboration released its second Data Release April 2018.

You can download the FITS file of GALAH DR2 from:

https://datacentral.org.au/teamdata/GALAH/public/

An example X-match with Gaia DR1 could be:

SELECT *
FROM gaiadr1.gaia_source AS gaia
INNER JOIN gaiadr1.tmass_best_neighbour AS tmass_xmatch
	ON gaia.source_id = tmass_xmatch.source_id
INNER JOIN gaiadr1.tmass_original_valid AS tmass
	ON tmass.tmass_oid = tmass_xmatch.tmass_oid
INNER JOIN user_sbuder.galah_dr2 AS galah_dr2
	ON tmass.designation = galah_dr2.star_id

If you have downloaded the file e.g. as 'GALAH_DR2.fits', do the following:

from astropy import table
t = table.Table()
galah_dr2 = t.read('GALAH_DR2.fits')

The FITS files contains the keywords in the table below

Field Units Data type Description
star_id char[16] 2MASS ID number by default, UCAC4 ID number if 2MASS unavailable (begins with UCAC4-)
star_id char[16] 2MASS ID number by default, UCAC4 ID number if 2MASS unavailable (begins with UCAC4-)
sobject_id int64 Unique per-observation star ID
gaia_id int64 \Gaia\ DR1 identifier
ndfclass char[8] Observation type (MFOBJECT (regular observation) or MFFLX (benchmark observation))
field_id int64 GALAH field identification number
raj2000 deg float64 Right ascension from 2MASS, J2000
dej2000 deg float64 Declination from 2MASS, J2000
jmag mag float64 J magnitude from 2MASS
hmag mag float64 H magnitude from 2MASS
kmag mag float64 K magnitude from 2MASS
vmag_jk mag float64 Synthetic V magnitude calculated from JHK, used for target selection
e_jmag mag float64 Uncertainty in J magnitude, from 2MASS
e_hmag mag float64 Uncertainty in H magnitude, from 2MASS
e_kmag mag float64 Uncertainty in K magnitude, from 2MASS
snr_c1 float64 Signal to noise per pixel in the HERMES blue channel
snr_c2 float64 Signal to noise per pixel in the HERMES green channel
snr_c3 float64 Signal to noise per pixel in the HERMES red channel
snr_c4 float64 Signal to noise per pixel in the HERMES IR channel
rv_synt km/s float64 Radial velocity from cross-correlation against synthetic spectra
rv_obst km/s float64 Radial velocity from internal cross-correlation against data
rv_nogr_obst km/s float64 Radial velocity from internal cross-correlation against data, uncorrected for gravitational redshift
e_rv_synt km/s float64 Uncertainty in rv_synt
e_rv_obst km/s float64 Uncertainty in rv_obst
e_rv_nogr_obst km/s float64 Uncertainty in rv_nogr_obst
chi2_cannon float64 Summed chi-squared over all spectral pixels
sp_label_distance float64 Label distance similar to \citet{Ho2017
flag_cannon int64 Flags for spectrum information in a bitmask format
0=No flag
+1 The Cannon starts to extrapolate. For some stars the values could be incorrect.
+2 The chi2 of the best fitting model spectrum is significantly higher or lower
+4 Reduction flag raised
+8 Binary star
+16 Negative flux
+32 Oscillating continuum
+64 General reduction issues
+128 Emission lines
teff K float64 Effective temperature
e_teff K float64 Uncertainty of teff
logg dex float64 Surface gravity
e_logg dex float64 Uncertainty of logg
fe_h dex float64 Iron abundance (not overall metallicity [M/H])
e_fe_h dex float64 Uncertainty in fe_h
vmic km/s float64 Microturbulent velocity
e_vmic km/s float64 Uncertainty in vmic
vsini km/s float64 Line of sight rotational velocity
e_vsini km/s float64 Uncertainty in vsini
alpha_fe dex float64 alpha-enhancement, determined as an error-weighted combination of Mg, Si, Ca, Ti abundances
e_alpha_fe dex float64 Uncertainty in alpha_fe
x_fe dex float64 [X/Fe] abundance for element X.
e_x_fe dex float64 Uncertainty in x_fe
flag_x_fe int64 Flags indicating difficulty in abundance determination in a bitmask format
0=No flag
+1 Line strength below 2-sigma upper limit
+2 The Cannon starts to extrapolate. For some stars the values could be incorrect.
+4 The chi2 of the best fitting model spectrum is significantly higher or lower.
+8 flag_cannon is not 0

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