J/A+A/674/A33 Gaia synthetic phot. cat. of white dwarfs (Gaia Coll., 2023)
Gaia Data Release 3: The Galaxy in your preferred colours.
Synthetic photometry from Gaia low-resolution spectra.
Gaia Collaboration, Montegriffo P., Bellazzini M., De Angeli F., Andrae R.,
Barstow M.A., Bossini D., Bragaglia A., Burgess P.W., Cacciari C.,
Carrasco J.M., Chornay N., Delchambre L., Evans D.W., Fouesneau M.,
Fremat Y., Garabato D., Jordi C., Manteiga M., Massari D., Palaversa L.,
Pancino E., Riello M., Ruz Mieres D., Sanna N., Santovena R., Sordo R.,
Vallenari A., Walton N.A., Brown A.G.A., Prusti T., de Bruijne J.H.J.,
Arenou F., Babusiaux C., Biermann M., Creevey O.L., Ducourant C., Eyer L.,
Guerra R., Hutton A., Klioner S.A., Lammers U.L., Lindegren L., Luri X.,
Mignard F., Panem C., Pourbaixy D., Randich S., Sartoretti P., Soubiran C.,
Tanga P., Bailer-Jones C.A.L., Bastian U., Drimmel R., Jansen F., Katz D.,
Lattanzi M.G., van Leeuwen F., Bakker J., Castaneda J., Fabricius C.,
Galluccio L., Guerrier A., Heiter U., Masana E., Messineo R., Mowlavi N.,
Nicolas C., Nienartowicz K., Pailler F., Panuzzo P., Riclet F., Roux W.,
Seabroke G.M., Thevenin F., Gracia-Abril G., Portell J., Teyssier D.,
Altmann M., Audard M., Bellas-Velidis I., Benson K., Berthier J., Blomme R.,
Busonero D., Busso G., Canovas H., Carry B., Cellino A., Cheek N.,
Clementini G., Damerdji Y., Davidson M., de Teodoro P., Nunez Campos M.,
Dell'Oro A., Esquej P., Fernandez-Hernandez J., Fraile E., Garcia-Lario P.,
Gosset E., Haigron R., Halbwachs J.-L., Hambly N.C., Harrison D.L.,
Hernandez J., Hestroer D., Hodgkin S.T., Holl B., Janssen K.,
Jevardat de Fombelle G., Jordan S., Krone-Martins A., Lanzafame A.C.,
Loffleer W., Marchal O., Marrese P.M., Moitinho A., Muinonen K., Osborne P.,
Pauwels T., Recio-Blanco A., Reyle C., Rimoldini L., Roegiers T.,
Rybizki J., Sarro L.M., Siopis C., Smith M., Sozzetti A., Utrilla E.,
van Leeuwen M., Abbas U., Abraham P., Abreu Aramburu A., Aerts C.,
Aguado J.J., Ajaj M., Aldea-Montero F., Altavilla G., Alvarez M.A.,
Alves J., Anderson R.I., Anglada Varela E., Antoja T., Baines D.,
Baker S.G., Balaguer-Nunez L., Balbinot E., Balog Z., Barache C.,
Barbato D., Barros M., Bartolome S., Bassilana J.-L., Bauchet N.,
Becciani U., Berihuete A., Bernet M., Bertone S., Bianchi L., Binnenfeld A.,
Blanco-Cuaresma S., Boch T., Bombrun A., Bouquillon S., Bramante L.,
Breedt E., Bressan A., Brouillet N., Brugaletta E., Bucciarelli B.,
Burlacu A., Butkevich A.G., Buzzi R., Caau E., Cancelliere R.,
Cantat-Gaudin T., Carballo R., Carlucci T., Carnerero M.I., Casamiquela L.,
Castellani M., Castro-Ginard A., Chaoul L., Charlot P., Chemin L.,
Chiaramida V., Chiavassa A., Comoretto G., Contursi G., Cooper W.J.,
Cornez T., Cowell S., Crifo F., Cropper M., Crosta M., Crowley C.,
Dafonte C., Dapergolas A., David P., de Laverny P., De Luise F.,
De March R., De Ridder J., de Souza R., de Torres A., del Peloso E.F.,
del Pozo E., Delbo M., Delgado A., Delisle J.-B., Demouchy C.,
Dharmawardena T.E., Diakite S., Diener C., Distefano E., Dolding C.,
Enke H., Fabre C., Fabrizio M., Faigler S., Fedorets G., Fernique P.,
Figueras F., Fournier Y., Fouron C., Fragkoudi F., Gai M.,
Garcia-Gutierrez A., Garcia-Reinaldos M., Garcia-Torres M., Garofalo A.,
Gavel A., Gavras P., Gerlach E., Geyer R., Giacobbe P., Gilmore G.,
Girona S., Giurida G., Gomel R., Gomez A., Gonzalez-Nunez J.,
Gonzalez-Santamaria I., Gonzalez-Vidal J.J., Granvik M., Guillout P.,
Guiraud J., Gutierrez-Sanchez R., Guy L.P., Hatzidimitriou D., Hauser M.,
Haywood M., Helmer A., Helmi A., Sarmiento M.H., Hidalgo S.L., Hladczuk N.,
Hobbs D., Holland G., Huckle H.E., Jardine K., Jasniewicz G.,
Jean-Antoine Piccolo A., Jimenez-Arranz O., Juaristi Campillo J., Julbe F.,
Karbevska L., Kervella P., Khanna S., Kordopatis G., Korn A.J., Kospal A.,
Kostrzewa-Rutkowska Z., Kruszynska K., Kun M., Laizeau P., Lambert S.,
Lanza A.F., Lasne Y., Le Campion J.-F., Lebreton Y., Lebzelter T.,
Leccia S., Leclerc N., Lecoeur-Taibi I., Liao S., Licata E.L.,
Lindstrom H.E.P., Lister T.A., Livanou E., Lobel A., Lorca A., Loup C.,
Madrero P., Pardo , Magdaleno Romeo A., Managau S., Mann R.G.,
Marchant J.M., Marconi M., Marcos J., Marcos Santos M.M.S., Marin Pina D.,
Marinoni S., Marocco F., Marshall D.J., Martin Polo L., Martin-Fleitas J.M.,
Marton G., Mary N., Masip A., Mastrobuono-Battisti A., Mazeh T.,
McMillan P.J., Messina S., Michalik D., Millar N.R., Mints A., Molina D.,
Molinaro R., Molnar L., Monari G., Monguio M., Montero A., Mor R., Mora A.,
Morbidelli R., Morel T., Morris D., Muraveva T., Murphy C.P., Musella I.,
Nagy Z., Noval L., Ocana F., Ogden A., Ordenovic C., Osinde J.O., Pagani C.,
Pagano I., Palicio P.A., Pallas-Quintela L., Panahi A., Payne-Wardenaar S.,
Penalosa Esteller X., Penttilae A., Pichon B., Piersimoni A.M.,
Pineau F.-X., Plachy E., Plum G., Poggio E., Prsa A., Pulone L., Racero E.,
Ragaini S., Rainer M., Raiteri C.M., Ramos P., Ramos-Lerate M.,
Re Fiorentin P., Regibo S., Richards P.J., Rios Diaz C., Ripepi V., Riva A.,
Rix H.-W., Rixon G., Robichon N., Robin A.C., Robin C., Roelens M.,
Rogues H.R.O., Rohrbasser L., Romero-Gomez M., Rowell N., Royer F.,
Rybicki K.A., Sadowski G., Saez Nunez A., Sagrista Selles A., Sahlmann J.,
Salguero E., Samaras N., Sanchez Gimenez V., Sarasso M., Schultheis M.S.,
Sciacca E., Segol M., Segovia J.C., Segransan D., Semeux D., Shahaf S.,
Siddiqui H.I., Siebert A., Siltala L., Silvelo A., Slezak E., Slezak I.,
Smart R.L., Snaith O.N., Solano E., Solitro F., Souami D., Souchay J.,
Spagna A., Spina L., Spoto F., Steele I.A., Steidelmueller H.,
Stephenson C.A., Sueveges M., Surdej J., Szabados L., Szegedi-Elek E.,
Taris F., Taylor M.B., Teixeira R., Tolomei L., Tonello N., Torra F.,
Torray J., Torralba Elipe G., Trabucchi M., Tsounis A.T., Turon C.,
Ulla A., Unger N., Vaillant M.V., van Dillen E., van Reeven W., Vanel O.,
Vecchiato A., Viala Y., Vicente D., Voutsinas S., Wevers T., Wyrzykowski L.,
Yoldas A., Yvard P., Zhao H., Zorec J., Zucker S., Zwitter T.
<Astron. Astrophys. 674, A33 (2023)>
=2023A&A...674A..33G 2023A&A...674A..33G (SIMBAD/NED BibCode)
ADC_Keywords: Surveys ; Milky Way ; Stars, white dwarf ; Photometry, UBVRI ;
Photometry, SDSS
Keywords: catalogs - surveys - techniques: photometric -
techniques: spectroscopic - stars: general - Galaxy: general
Abstract:
Gaia Data Release 3 provides novel flux-calibrated low-resolution
spectrophotometry for approximately 220 million sources in the
wavelength range 330nm ≤ lambda ≤ 1050nm (XP spectra). Synthetic
photometry directly tied to a flux in physical units can be obtained
from these spectra for any passband fully enclosed in this wavelength
range. We describe how synthetic photometry can be obtained from XP
spectra, illustrating the performance that can be achieved under a
range of different conditions - for example passband width and
wavelength range - as well as the limits and the problems affecting
it.
Existing top-quality photometry can be reproduced within a few per
cent over a wide range of magnitudes and colour, for wide and medium
bands, and with up to millimag accuracy when synthetic photometry is
standardised with respect to these external sources. Some examples of
potential scientific application are presented, including the
detection of multiple populations in globular clusters, the estimation
of metallicity extended to the very metal-poor regime, and the
classification of white dwarfs.
A catalogue providing standardised photometry for approximately
2.2x10^8 sources in several wide bands of widely used photometric
systems is provided (Gaia Synthetic Photometry Catalogue; GSPC) as
well as a catalogue of approximately 105 white dwarfs with DA/non-DA
classification obtained with a Random Forest algorithm (Gaia Synthetic
Photometry Catalogue for White Dwarfs; GSPC-WD).
Description:
We have made the GSPC-WD synthetic photometry available as a
stand-alone catalogue, including SDSS, JKC and JPLUS XPSP and the DA
classification probability. The photometry of the individual J-PAS
bands, used in the random forest analysis, is not included due to
their low signal-to-noise. For WDs classified in SDSS, a subset of
which were used in the training/validation of the random forest
algorithm, we also include the full SDSS classifications as a separate
column in the GSPC-WD catalogue table. When the synthetic spectral
bands are very narrow a significant number of sources will have low
signal-to-noise. Furthermore, at the edges of the Gaia spectral range,
away from the peak of the effective area, this is also true for some
stars in the wider bands included in the catalogue. In some extreme
cases, there is no significant detection of the object. The random
forest algorithm is only able to classify a WD when valid flux
measurements are available for every photometric band we include in
the analysis. Therefore, no classification is recorded in the
catalogue when data for one or more bands is "missing". In total
15,003 WDs from the total sample of 101,783 are not classified. For
completeness, we have made all the flux measurements and corresponding
magnitudes available for all objects in the GSPC-WD. Hence
magnitude/fluxes with very large errors, up to several times the flux
itself, are included. However, where fluxes are negative, the
magnitudes are not defined. When using the catalogue, appropriate
signal-to-noise cuts are advisable for the specific work in-hand, to
ensure data quality.
File Summary:
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FileName Lrecl Records Explanations
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ReadMe 80 . This file
gspc-wd.dat 1569 101786 Gaia WD DR3 catalogue
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See also:
I/355 : Gaia DR3 Part 1. Main source (Gaia Collaboration, 2022)
I/357 : Gaia DR3 Part 3. Non-single stars (Gaia Collaboration, 2022)
I/358 : Gaia DR3 Part 4. Variability (Gaia Collaboration, 2022)
I/360 : Gaia DR3 Part 6. Performance verification (Gaia Collaboration, 2022)
Byte-by-byte Description of file: gspc-wd.dat
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Bytes Format Units Label Explanations
--------------------------------------------------------------------------------
1- 19 I19 --- GaiaDR3 The unique Gaia DR3 source identifier
(source_id)
21- 42 F22.18 deg RAdeg Right ascension (ICRS) at Ep=2016.0 (ra)
44- 55 F12.10 mas e_RAdeg Right ascension uncertainty
(ICRS) at Ep=2016.0 (ra_error)
57- 78 E22.19 deg DEdeg Declination (ICRS)at Ep=2016.0 (dec)
80- 91 F12.10 mas e_DEdeg Declination uncertainty
(ICRS) at Ep=2016.0 (dec_error)
93- 110 F18.15 mag UmagJHN ? Johnson U Standard magnitude
(JohnsonStdmagU)
112- 129 F18.15 mag BmagJHN ? Johnson B Standard magnitude
(JohnsonStdmagB)
131- 148 F18.15 mag VmagJHN ? Johnson V Standard magnitude
(JohnsonStdmagV)
150- 167 F18.15 mag RmagJHN Johnson R Standard magnitude
(JohnsonStdmagR)
169- 186 F18.15 mag ImagJHN Johnson I Standard magnitude
(JohnsonStdmagI)
188- 209 E22.17 W/m2/nm FUJHN ? Johnson U Standard flux
(JohnsonStdfluxU)
211- 233 E23.17 W/m2/nm FBJHN ? Johnson B Standard flux
(JohnsonStdfluxB) (1)
235- 256 E22.17 W/m2/nm FVJHN ? Johnson V Standard flux
(JohnsonStdfluxV)
258- 279 E22.17 W/m2/nm FRJHN Johnson R Standard flux
(JohnsonStdfluxR)
281- 302 E22.17 W/m2/nm FIJHN Johnson I Standard flux uncertainty
(JohnsonStdfluxI)
304- 325 E22.17 W/m2/nm e_FUJHN ? Johnson U Standard flux uncertainty
(JohnsonStdfluxerror_U)
327- 348 E22.17 W/m2/nm e_FBJHN ? Johnson B Standard flux uncertainty
(JohnsonStdfluxerror_B)
350- 371 E22.17 W/m2/nm e_FVJHN ? Johnson V Standard flux uncertainty
(JohnsonStdfluxerror_V)
373- 394 E22.17 W/m2/nm e_FRJHN Johnson R Standard flux uncertainty
(JohnsonStdfluxerror_R)
396- 417 E22.17 W/m2/nm e_FIJHN Johnson I Standard flux uncertainty
(JohnsonStdfluxerror_I)
419- 436 F18.15 mag umagSDSS ? SDSS u magnitude (SdssStdmagu)
438- 455 F18.15 mag gmagSDSS ? SDSS g magnitude (SdssStdmagg)
457- 474 F18.15 mag rmagSDSS ? SDSS r magnitude (SdssStdmagr)
476- 493 F18.15 mag imagSDSS SDSS i magnitude (SdssStdmagi)
495- 512 F18.15 mag zmagSDSS ? SDSS z magnitude (SdssStdmagz)
514- 535 E22.17 W/m2/nm FuSDSS ? SDSS u flux (SdssStdfluxu)
537- 558 E22.17 W/m2/nm FgSDSS ? SDSS g flux (SdssStdfluxg) (1)
560- 582 E23.17 W/m2/nm FrSDSS ? SDSS r flux (SdssStdfluxr) (1)
584- 605 E22.17 W/m2/nm FiSDSS SDSS i flux (SdssStdfluxi)
607- 628 E22.17 W/m2/nm FzSDSS SDSS z flux (SdssStdfluxz) (1)
630- 651 E22.17 W/m2/nm e_FuSDSS ? SDSS u flux uncertainty
(SdssStdfluxerror_u)
653- 674 E22.17 W/m2/nm e_FgSDSS ? SDSS g flux uncertainty
(SdssStdfluxerror_g)
676- 697 E22.17 W/m2/nm e_FrSDSS ? SDSS r flux uncertainty
(SdssStdfluxerror_r)
699- 720 E22.17 W/m2/nm e_FiSDSS SDSS i flux uncertainty
(SdssStdfluxerror_i)
722- 743 E22.17 W/m2/nm e_FzSDSS SDSS z flux uncertainty
(SdssStdfluxerror_z)
745- 762 F18.15 mag uJAVAmag ? Jplus uJAVA magnitude (JplusmaguJAVA)
764- 781 F18.15 mag J0378mag ? Jplus J0378 magnitude (JplusmagJ0378)
783- 800 F18.15 mag J0395mag ? Jplus J0395 magnitude (JplusmagJ0395)
802- 819 F18.15 mag J0410mag ? Jplus J0410 magnitude (JplusmagJ0410)
821- 838 F18.15 mag J0430mag ? Jplus J0430 magnitude (JplusmagJ0430)
840- 857 F18.15 mag gJPLUSmag ? Jplus uJAVA magnitude (JplusmaggJPLUS)
859- 876 F18.15 mag J0515mag ? Jplus J0515 magnitude (JplusmagJ0515)
878- 895 F18.15 mag rJPLUSmag ? Jplus rJPLUS5 magnitude
(JplusmagrJPLUS)
897- 914 F18.15 mag J0660mag ? Jplus J0660 magnitude (JplusmagJ0660)
916- 933 F18.15 mag iJPLUSmag Jplus iJPLUS magnitude (JplusmagiJPLUS)
935- 952 F18.15 mag J0861mag ? Jplus J0861 magnitude (JplusmagJ0861)
954- 971 F18.15 mag zJPLUSmag ? Jplus zJPLUS magnitude
(JplusmagzJPLUS)
973- 995 E23.17 W/m2/nm FuJAVA ? Jplus uJAVA flux (JplusfluxuJAVA) (1)
997-1019 E23.17 W/m2/nm FJ0378 ? Jplus J0378 flux (JplusfluxJ0378) (1)
1021-1043 E23.17 W/m2/nm FJ0395 ? Jplus J0395 flux (JplusfluxJ0395) (1)
1045-1067 E23.17 W/m2/nm FJ0410 ? Jplus J0410 flux (JplusfluxJ0410) (1)
1069-1091 E23.17 W/m2/nm FJ0430 ? Jplus J0430 flux (JplusfluxJ0430) (1)
1093-1114 E22.17 W/m2/nm FgJPLUS ? Jplus uJAVA flux (JplusfluxgJPLUS) (1)
1116-1137 E22.17 W/m2/nm FJ0515 ? Jplus J0515 flux (JplusfluxJ0515) (1)
1139-1161 E23.17 W/m2/nm FrJPLUS ? Jplus rJPLUS5 flux
(JplusfluxrJPLUS) (1)
1163-1184 E22.17 W/m2/nm FJ0660 Jplus J0660 flux (JplusfluxJ0660) (1)
1186-1207 E22.17 W/m2/nm FiJPLUS Jplus iJPLUS flux (JplusfluxiJPLUS)
1209-1230 E22.17 W/m2/nm FJ0861 Jplus J0861 flux (JplusfluxJ0861) (1)
1232-1254 E23.17 W/m2/nm FzJPLUS Jplus zJPLUS flux (JplusfluxzJPLUS) (1)
1256-1277 E22.17 W/m2/nm e_FuJAVA ? Jplus uJAVA flux uncertainty
(Jplusfluxerror_uJAVA)
1279-1300 E22.17 W/m2/nm e_FJ0378 ? Jplus J0378 flux uncertainty
(Jplusfluxerror_J0378)
1302-1323 E22.17 W/m2/nm e_FJ0395 ? Jplus J0395 flux uncertainty
(Jplusfluxerror_J0395)
1325-1346 E22.17 W/m2/nm e_FJ0410 ? Jplus J0410 flux uncertainty
(Jplusfluxerror_J0410)
1348-1369 E22.17 W/m2/nm e_FJ0430 ? Jplus J0430 flux uncertainty
(Jplusfluxerror_J0430)
1371-1392 E22.17 W/m2/nm e_FgJPLUS ? Jplus uJAVA flux uncertainty
(Jplusfluxerror_gJPLUS)
1394-1415 E22.17 W/m2/nm e_FJ0515 ? Jplus J0515 flux uncertainty
(Jplusfluxerror_J0515)
1417-1438 E22.17 W/m2/nm e_FrJPLUS ? Jplus rJPLUS5 flux uncertainty
(Jplusfluxerror_rJPLUS)
1440-1461 E22.17 W/m2/nm e_FJ0660 Jplus J0660 flux uncertainty
(Jplusfluxerror_J0660)
1463-1484 E22.17 W/m2/nm e_FiJPLUS Jplus iJPLUS flux uncertainty
(Jplusfluxerror_iJPLUS)
1486-1507 E22.17 W/m2/nm e_FJ0861 Jplus J0861 flux uncertainty
(Jplusfluxerror_J0861)
1509-1530 E22.17 W/m2/nm e_FzJPLUS Jplus zJPLUS flux uncertainty
(Jplusfluxerror_zJPLUS)
1532-1552 F21.19 --- pDA [0/1]? DA classification probability
(probability DA) (2)
1554-1569 A16 --- WDType SDSS WD classification (SDSS WD type)
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Note (1): For completeness, we have made all the flux measurements and
corresponding magnitudes available for all objects in the GSPC-WD.
Hence magnitude/fluxes with very large errors, up to several times the flux
itself, are included. However, where fluxes are negative, the magnitudes are
not defined.
Note (2): In some extreme cases, there is no significant detection of the
object. The random forest algorithm is only able to classify a WD when valid
flux measurements are available for every photometric band we include in the
analysis. Therefore, no classification is recorded in the catalogue when data
for one or more bands is "missing". In total 15003 WDs from the total sample
of 101783 are not classified.
--------------------------------------------------------------------------------
Acknowledgements:
Claudio Pagani, cp232(at)leicester.ac.uk
(End) Patricia Vannier [CDS] 11-Oct-2022