J/A+A/699/A212         DA DWD candidates based on DESI EDR        (Jiang+, 2025)

The survey of DA double white dwarf candidates based on DESI EDR. Jiang Z., Yuan H., Bai Z., Yang M., Yang X., Liu Q., He Y., Li G., Dong Y., Wang M., Zhou M., Zhang H. <Astron. Astrophys. 699, A212 (2025)> =2025A&A...699A.212J 2025A&A...699A.212J (SIMBAD/NED BibCode)
ADC_Keywords: Binaries, spectroscopic ; Stars, white dwarf ; Radial velocities ; Optical Keywords: techniques: radial velocities - binaries: spectroscopic - white dwarfs Abstract: Mergers of double white dwarfs (DWDs) are considered significant potential progenitors of type Ia supernovae (SNe Ia), which serve as "standard candles" in cosmology to measure the expansion rate of the Universe and explore the nature of dark energy. Although there is no direct observational evidence to definitively determine the formation pathways of SNe Ia, studying the physical properties of DWDs provides valuable insights into their evolutionary processes, interaction modes, and merger mechanisms, which are essential for understanding the explosion mechanisms of SNe Ia. This study aims to identify DWD candidates through spectroscopic radial velocity (RV) measurements and analyze their physical properties based on DESI EDR. We crossmatched DESI EDR with Gaia EDR3 WD catalog to select DA spectra. Spectroscopic RV was measured using the cross-correlation function (CCF), with RV variability assessed via a chi-squared method. We derived spectroscopic Teff and log g by fitting hydrogen Balmer lines, applying 3D convection corrections. Orbital periods and semi-amplitudes came from Lomb-Scargle analysis of RV time series. WD cooling models and Monte Carlo simulations were used to calculate masses, cooling ages, radii, and uncertainties. We also analyzed photometric and SED properties to derive temperatures and radii, comparing them with spectroscopic parameters. We identified 33 DA DWD candidates with significant RV variability, including 28 new discoveries. Among them, an extremely low mass (ELM) DWD candidate and a potential triple system were found. We measured key parameters like Teff, logg, mass, and radius for these candidates and estimated their orbital periods from the data. Of these, 17 showed clear periodic RV variability, and we reported their best-fitting periods and RV semi-amplitudes. Description: In this study, we have searched for DA DWD candidates by measuring spectroscopic RV and selecting sources with significant RV variability. We crossmatched DESI EDR spectra with Gaia WD catalog to select DA samples with S/N greater than 10. File Summary: -------------------------------------------------------------------------------- FileName Lrecl Records Explanations -------------------------------------------------------------------------------- ReadMe 80 . This file tableb2.dat 228 33 Parameters for 33 DWD candidates tableb1.dat 53 381 Radial velocities of single-exposure spectra tableb3.dat 54 165 Orbital parameters for 33 DWD candidates -------------------------------------------------------------------------------- See also: I/350 : Gaia EDR3 (Gaia Collaboration, 2020) J/MNRAS/508/3877 : Catalogue of white dwarfs in Gaia EDR3 (Gentile+, 2021) J/ApJ/970/181 : Categorizing WDs with Gaia XP spectra and UMAP (Kao+, 2024) Byte-by-byte Description of file: tableb2.dat -------------------------------------------------------------------------------- Bytes Format Units Label Explanations -------------------------------------------------------------------------------- 1- 22 A22 --- WDJname WDJ name (WDJHHMMSS.ssDDMMSS.ss, equinox and epoch 2000) 24- 35 F12.8 deg RAdeg Right ascension (J2000) 37- 47 F11.8 deg DEdeg Declination (J2000) 49- 52 F4.1 mag Gmag Gaia EDR3 G-band mean magnitude 54- 60 F7.4 mas plx Gaia EDR3 Absolute stellar parallax at Ep=2016.0 62- 70 F9.6 mag BP-RP Gaia EDR3 BP-RP colour 72- 75 F4.1 mag GMAG Gaia EDR3 Absolute G magnitude 77- 88 F12.10 mag E(B-V) 3D extinction obtained from dustmaps (1) 90- 91 I2 --- N Number of observations 93- 97 F5.2 --- eta ? RV Variability parameter η 98 A1 --- n_eta [I] i means a very large eta 100-102 I3 km/s deltaRV Maximum difference in RV 104-108 I5 K Teff1d Effective temperature obtained from wd-tools (2) 110-113 I4 K e_Teff1d Error of effective temperature obtained from wdtools (2) 115-118 F4.2 [cm/s2] logg1d Surface gravity obtained from wdtools 120-123 F4.2 [cm/s2] e_logg1d Error of surface gravity obtained from wdtools (2) 125-129 I5 K Teff Effective temperature after 3D corrections (3) 131-134 F4.2 [cm/s2] logg Surface gravity after 3D corrections (3) 136-139 I4 K e_Teff Error of Teff 141-144 F4.2 [cm/s2] e_logg Error of logg 146-151 F6.4 Msun Mass Mass obtained by interpolating Teff and logg into WD evolutionary models 153-158 F6.4 Msun e_Mass ? Error of mass 160-165 F6.4 Gyr Agecool ? Cooling age obtained by interpolating Teff and logg into WD evolutionary models 167-172 F6.4 Gyr e_Agecool ? Error of Agecool 174-179 F6.4 Rsun Radsp Radius obtained by interpolating Teff and logg into WD evolutionary models 181-186 F6.4 Rsun e_Radsp Error of Radsp 188-192 I5 K Teffsed ? Effective temperature obtained from the single-DA SED fitting 194-199 F6.4 Rsun Radsed ? Radius obtained from the single-DA SED fitting 201-205 I5 K TeffDESIsp1d ? Effective temperature from DESI spectroscopic fitting (4) 207-210 F4.2 [cm/s2] loggDESIsp1d ? Surface gravity from DESI spectroscopic fitting (4) 212-216 I5 K TeffDESIsp3d ? Effective temperature after 3D corrections from DESI spectroscopic fitting (4) 218-221 F4.2 [cm/s2] loggDESIsp3d ? Surface gravity after 3D corrections from DESI spectroscopic fitting (4) 223-228 F6.4 Rsun RadDESI ? Radius obtained by interpolating TeffDESIsp3d and loggDESIsp3d into WD evolutionary models -------------------------------------------------------------------------------- Note (1): Gree, 2018, The Journal of Open Source Software, 3, 695 Note (2): Chandra et al., 2020MNRAS.497.2688C 2020MNRAS.497.2688C; Chandra, 2020, wdtools: Computational Tools for the Spectroscopic Analysis of White Dwarfs Note (3): Tremblay et al., 2013A&A...559A.104T 2013A&A...559A.104T Note (4): by Manser et al., 2024MNRAS.535..254M 2024MNRAS.535..254M -------------------------------------------------------------------------------- Byte-by-byte Description of file: tableb1.dat -------------------------------------------------------------------------------- Bytes Format Units Label Explanations -------------------------------------------------------------------------------- 1- 22 A22 --- WDJname WDJ name (WDJHHMMSS.ss+DDMMSS.ss) 24- 35 F12.6 d MJD MJD identifier for a unique DESI spectrum 37- 41 F5.1 --- MedS/N Median S/N for a unique DESI spectrum 43- 48 F6.1 km/s RV RV obtained from CCF of template-matching 50- 53 F4.1 km/s e_RV Error of RV obtained from Equation 2 of the paper -------------------------------------------------------------------------------- Byte-by-byte Description of file: tableb3.dat -------------------------------------------------------------------------------- Bytes Format Units Label Explanations -------------------------------------------------------------------------------- 1- 22 A22 --- WDJname WDJ name (WDJHHMMSS.ss+DDMMSS.ss) 24- 32 F9.6 d Per Period obtained from the Lomb-Scargle method 34 I1 --- Rank Power spectrum rank of the period 36- 47 F12.6 km/s K Semi-amplitude corresponding to the period 49- 54 F6.4 --- R2 R2 of the fitting curve -------------------------------------------------------------------------------- Acknowledgements: Ziyue Jiang, jiangziyue(at)bao.ac.cn References: Green, G. 2018, The Journal of Open Source Software, 3, 695 Chandra et al., 2020MNRAS.497.2688C 2020MNRAS.497.2688C Chandra, V. 2020, wdtools: Computational Tools for the Spectroscopic Analysis of White Dwarfs Tremblay et al., 2013A&A...559A.104T 2013A&A...559A.104T Manser et al., 2024MNRAS.535..254M 2024MNRAS.535..254M
(End) Ziyue Jiang [NAOC, CHINA], Patricia Vannier [CDS] 27-May-2025
The document above follows the rules of the Standard Description for Astronomical Catalogues; from this documentation it is possible to generate f77 program to load files into arrays or line by line