J/A+A/685/A130 Gaia FPR. Analysis of QSO environment (Gaia Collaboration+, 2024)
Gaia Focused Product Release:
A catalogue of sources around quasars to search for strongly lensed quasars.
Gaia collaboration, Krone-Martins A., Ducourant C., Galluccio L.,
Delchambre L., Oreshina-Slezak I., Teixeira R., Braine J., Le Campion J.-F.,
Mignard F., Roux W., Blazere A., Pegoraro L., Brown A.G.A., Vallenari A.,
Prusti T., de Bruijne J.H.J., Arenou F., Babusiaux C., Barbier A.,
Biermann M., Creevey O.L., Evans D.W., Eyer L., Guerra R., Hutton A.,
Jordi C., Klioner S.A., Lammers U., Lindegren L., Luri X., Randich S.,
Sartoretti P., Smiljanic R., Tanga P., Walton N.A., Bailer-Jones C.A.L.,
Bastian U., Cropper M., Drimmel R., Katz D., Soubiran C., van Leeuwen F.,
Audard M., Bakker J., Blomme R., Castaneda J., De Angeli F., Fabricius C.,
Fouesneau M., Fremat Y., Guerrier A., Masana E., Messineo R., Nicolas C.,
Nienartowicz K., Pailler F., Panuzzo P., Riclet F., Seabroke G.M., Sordo R.,
Thevenin F., Gracia-Abril G., Portell J., Teyssier D., Altmann M.,
Benson K., Berthier J., Burgess P.W., Busonero D., Busso G., Canovas H.,
Carry B., Cheek N., Clementini G., Damerdji Y., Davidson M., de Teodoro P.,
Dell'Oro A., Fraile Garcia E., Garabato D., Garcia-Lario P.,
Garralda Torres N., Gavras P., Haigron R., Hambly N.C., Harrison D.L.,
Hatzidimitriou D., Hernandez J., Hodgkin S.T., Holl B., Jamal S., Jordan S.,
Lanzafame A.C., Loeffler W., Lorca A., Marchal O., Marrese P.M.,
Moitinho A., Muinonen K., Nunez Campos M., Osborne P., Pancino E.,
Pauwels T., Recio-Blanco A., Riello M., Rimoldini L., Robin A.C.,
Roegiers T., Sarro L.M., Schultheis M., Siopis C., Smith M., Sozzetti A.,
Utrilla E., van Leeuwen M., Weingrill K., Abbas U., Abraham P.,
Abreu Aramburu A., Aerts C., Altavilla G., Alvarez M.A., Alves J.,
Anderson R.I., Antoja T., Baines D., Baker S.G., Balog Z., Barache C.,
Barbato D., Barros M., Barstow M.A., Bartolome S., Bashi D., Bauchet N.,
Baudeau N., Becciani U., Bedin L.R., Bellas-Velidis I., Bellazzini M.,
Beordo W., Berihuete A., Bernet M., Bertolotto C., Bertone S., Bianchi L.,
Binnenfeld A., Boch T., Bombrun A., Bouquillon S., Bragaglia A.,
Bramante L., Breedt E., Bressan A., Brouillet N., Brugaletta E.,
Bucciarelli B., Butkevich A.G., Buzzi R., Caffau E., Cancelliere R.,
Cannizzo S., Carballo R., Carlucci T., Carnerero M.I., Carrasco J.M.,
Carretero J., Carton S., Casamiquela L., Castellani M., Castro-Ginard A.,
Cesare V., Charlot P., Chemin L., Chiaramida V., Chiavassa A., Chornay N.,
Collins R., Contursi G., Cooper W.J., Cornez T., Crosta M., Crowley C.,
Dafonte C., de Laverny P., De Luise F., De March R., de Souza R.,
de Torres A., del Peloso E.F., Delbo M., Delgado A., Dharmawardena T.E.,
Diakite S., Diener C., Distefano E., Dolding C., Dsilva K., Duran J.,
Enke H., Esquej P., Fabre C., Fabrizio M., Faigler S., Fatovi'c M.,
Fedorets G., Fernandez-Hernandez J., Fernique P., Figueras F., Fournier Y.,
Fouron C., Gai M., Galinier M., Garcia-Gutierrez A., Garcia-Torres M.,
Garofalo A., Gerlach E., Geyer R., Giacobbe P., Gilmore G., Girona S.,
Giuffrida G., Gomel R., Gomez A., Gonzalez-Nunez J., Gonzalez-Santamaria I.,
Gosset E., Granvik M., Gregori Barrera V., Gutierrez-Sanchez R., Haywood M.,
Helmer A., Helmi A., Henares K., Hidalgo S.L., Hilger T., Hobbs D.,
Hottier C., Huckle H.E., Jablonska M., Jansen F., Jimenez-Arranz O.,
Juaristi Campillo J., Khanna S., Kordopatis G., Kospal A.,
Kostrzewa-Rutkowska Z., Kun M., Lambert S., Lanza A.F., Lebreton Y.,
Lebzelter T., Leccia S., Lecoeur-Taibi I., Lecoutre G., Liao S.,
Liberato L., Licata E., Lindstrom H.E.P., Lister T.A., Livanou E., Lobel A.,
Loup C., Mahy L., Mann R.G., Manteiga M., Marchant J.M., Marconi M.,
Marin Pina D., Marinoni S., Marshall D.J., Martin Lozano J.,
Martin-Fleitas J.M., Marton G., Mary N., Masip A., Massari D.,
Mastrobuono-Battisti A., Mazeh T., McMillan P.J., Meichsner J., Messina S.,
Michalik D., Millar N.R., Mints A., Molina D., Molinaro R., Molnar L.,
Monari G., Monguio M., Montegriffo P., Montero A., Mor R., Mora A.,
Morbidelli R., Morel T., Morris D., Mowlavi N., Munoz D., Muraveva T.,
Murphy C.P., Musella I., Nagy Z., Nieto S., Noval L., Ogden A.,
Ordenovic C., Pagani C., Pagano I., Palaversa L., Palicio P.A.,
Pallas-Quintela L., Panahi A., Panem C., Payne-Wardenaar S., Penttilae A.,
Pesciullesi P., Piersimoni A.M., Pinamonti M., Pineau F.-X., Plachy E.,
Plum G., Poggio E., Pourbaix+ D., Prsa A., Pulone L., Racero E., Rainer M.,
Raiteri C.M., Ramos P., Ramos-Lerate M., Ratajczak M., Re Fiorentin P.,
Regibo S., Reyle C., Ripepi V., Riva A., Rix H.-W., Rixon G., Robichon N.,
Robin C., Romero-Gomez M., Rowell N., Royer F., Ruz Mieres D., Rybicki K.A.,
Sadowski G., Saez Nunez A., Sagrista Selles A., Sahlmann J.,
Sanchez Gimenez V., Sanna N., Santovena R., Sarasso M., Sarrate Riera C.,
Sciacca E., Segovia J.C., Segransan D., Shahaf S., Siebert A., Siltala L.,
Slezak E., Smart R.L., Snaith O.N., Solano E., Solitro F., Souami D.,
Souchay J., Spina L., Spitoni E., Spoto F., Squillante L.A., Steele I.A.,
Steidelmueller H., Surdej J., Szabados L., Taris F., Taylor M.B.,
Tisanic K., Tolomei L., Torra F., Torralba Elipe G., Trabucchi M.,
Tsantaki M., Ulla A., Unger N., Vanel O., Vecchiato A., Vicente D.,
Voutsinas S., Weiler M., Wyrzykowski L., Zhao H., Zorec J., Zwitter T.,
Balaguer-Nunez L., Leclerc N., Morgenthaler S., Robert G., Zucker S.
<Astron. Astrophys. 685, A130 (2024)>
=2024A&A...685A.130G 2024A&A...685A.130G (SIMBAD/NED BibCode)
ADC_Keywords: Surveys ; QSOs ; Gravitational lensing ; Optical
Keywords: gravitational - gravitational lensing: strong -
methods: data analysis - catalogues - surveys - quasars: general
Abstract:
Strongly lensed quasars are fundamental sources for cosmology. The
Gaia space mission covers the entire sky with the unprecedented
resolution of 0.18" in the optical, making it an ideal instrument to
search for gravitational lenses down to the limiting magnitude of 21.
Nevertheless, the previous Gaia Data Releases are known to be
incomplete for small angular separations such as those expected for
most lenses.
We present the Data Processing and Analysis Consortium GravLens
pipeline, which was built to analyse all Gaia detections around
quasars and to cluster them into sources, thus producing a catalogue
of secondary sources around each quasar. We analysed the resulting
catalogue to produce scores that indicate source configurations that
are compatible with strongly lensed quasars.
GravLens uses the DBSCAN unsupervised clustering algorithm to detect
sources around quasars. The resulting catalogue of multiplets is then
analysed with several methods to identify potential gravitational
lenses. We developed and applied an outlier scoring method, a
comparison between the average BP and RP spectra of the components,
and we also used an extremely randomised tree algorithm. These methods
produce scores to identify the most probable configurations and to
establish a list of lens candidates.
We analysed the environment of 3760032 quasars. A total of 4760920
sources, including the quasars, were found within 6" of the quasar
positions. This list is given in the Gaia archive. In 87% of cases,
the quasar remains a single source, and in 501 385 cases neighbouring
sources were detected. We propose a list of 381 lensed candidates, of
which we identified 49 as the most promising. Beyond these candidates,
the associate tables in this Focused Product Release allow the entire
community to explore the unique Gaia data for strong lensing studies
further.
Description:
The Gaia Focus Product Release (FPR) provides a catalogue of the
quasars environment for the search of gravitational lenses
(I/361/lenscand). This catalogue contains 501385 multiplets found
within 6" of known quasars (I/361/lenscatn). We analyse the
combinations of the components of 476207 such multiplets with 2-6
components in table2.dat and report the most promising candidates in
table3.dat.
The analysis done in table2.dat relies on four different methods:
i) When Gaia spectra are available for all the components in the
combination, a comparison of the component spectra is done using a
reduced chi-square approach, described in Equations 1 (Chi2r) and 2
(Gof) of (Gaia Collaboration+, 2024). This approach is complemented by
another technique based on the Wasserstein distance presented in
Equation 3 (SWd) of the same manuscript. Auxiliary data computed along
this comparison (integrated flux, colours, resampling chi-square and
S/N of the spectra) are concurrently provided in table2.dat.
ii) For combinations composed of three or four components, we compute
a discriminant value, called the extremely randomized trees (ERT)
score. This score reflects the ability for the combination to be
matched to the image positions and relative magnitudes produced
through simulations of gravitational lens systems.
See (Delchambre et al., 2019A&A...622A.165D 2019A&A...622A.165D) for details.
iii) For the 3 760 032 QSOs contained in our input list of quasars, we
compute a lens score based on Gaia DR3 (2023A&A...674A...1G 2023A&A...674A...1G) and
unWISE (2014AJ....147..108L 2014AJ....147..108L) data. The handling of missing data in
these catalogues and the subsequent imputation of a lens score is done
using the Heuristical Ensemble Splitting Imputation and Organization
of Data (HESIOD) outlier detection method.
iv) Finally, we combine the spectra comparison scores (Chi2r, Gof and
SWd); the ERT scores (SertABCD, SertABC, SertABD, SertACD and SertBCD)
and the HESIOD score (SHesiod) with the galactic latitude, (GLAT);
maximal separation between pair of components (Size); G magnitudes
(GmagMin and GmagMax); minimal S/N (SnrMin); integrated fluxes (Fmin
and Fmax) and maximal absolute difference in colours (Dcolor) into a
combined score (Scomb) using a Random Forest classifier
(2001MachL..45....5B 2001MachL..45....5B).
The 381 lens candidates considered as promising (ranked 'A') or
plausible candidates (ranked 'B') are provided in table3.dat along
with their lens scores.
File Summary:
--------------------------------------------------------------------------------
FileName Lrecl Records Explanations
--------------------------------------------------------------------------------
ReadMe 80 . This file
table2.dat 773 1957559 Multiplet analysis
table3.dat 118 381 Gravitational lens candidates
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See also:
I/361 : Gaia Focused Product Release (Gaia FPR) (Gaia Collaboration, 2023)
https://www.cosmos.esa.int/web/gaia/fpr : Gaia FPR Home Page
Byte-by-byte Description of file: table2.dat
--------------------------------------------------------------------------------
Bytes Format Units Label Explanations
--------------------------------------------------------------------------------
1- 7 I7 --- Seq [1/1957559] Unique combination identifier
9- 35 A27 --- Name Name of the multiplet, taken from
I/361/lenscand, DR3GaiaHHMMSS.sss+DDMMSS.ss
37- 55 I19 --- Source Unique source identifier of the QSO,
taken from I/361/lenscand (source_id)
57 I1 --- Ncomp [2/6] Number of components in the multiplet,
taken from I/361/lenscand (n_components)
59 I1 --- Ncomb [2/6] Number of components in this
combination (7)
61- 71 A11 --- Comps Indices of the components in this combination,
taken from I/361/lenscand (component_id) (1)
73- 86 F14.10 deg RAdeg Mean right ascension of the QSO (ICRS)
88-101 F14.10 deg DEdeg Mean declination of the QSO (ICRS)
103-110 F8.2 mas Size [300/12000] The maximal angular separation
between any pair of components in this
combination
112-117 F6.3 mag GmagMin Minimal onboard G magnitude of the components
in this combination
119-124 F6.3 mag GmagMax Maximal onboard G magnitude of the components
in this combination
126-139 F14.10 deg GLON Mean galactic longitude of the QSO
141-154 F14.10 deg GLAT Mean galactic latitude of the QSO
156-159 F4.2 --- SertABCD [0/1]? ERT score associated with this
candidate (8)
161-164 F4.2 --- SertABC [0/1]? ERT score computed based on the
ABC model (empty if Ncomb=4)
166-169 F4.2 --- SertABD [0/1]? ERT score computed based on the
ABD model (empty if Ncomb=4)
171-174 F4.2 --- SertACD [0/1]? ERT score computed based on the
ACD model (empty if Ncomb=4)
176-179 F4.2 --- SertBCD [0/1]? ERT score computed based on the
BCD model (empty if Ncomb=4)
181-185 F5.3 --- SHesiod [0/1]? Minimal HESIOD score amongst the
components in this combination
187-196 F10.3 --- Chi2r ? Reduced chi-square coming from the
comparison of the epoch spectra in this
combination (2)
198-200 I3 --- Dof ? Degree of freedom associated with Chi2r
202-209 F8.3 --- Gof ? Goodness of fit associated with Chi2r,
Gof=(4.5*Dof)1/2*( Chi2r1/3+2/9/Dof-1)
211-212 I2 --- f_Chi2r [0/31]? Flags associated with Chi2r (3)
214-223 F10.3 --- SWd ? Maximal Wasserstein distance between any
two pair of components in this combination
225-231 F7.2 --- SnrMin ? Minimal S/N of the components in this
combination
233-238 F6.3 mag Dcolor ? Maximal absolute difference in the BP-RP
colour over all pair of components in this
combination
240-248 F9.1 e-/s FMin ? Minimal integrated BP+RP flux of the
components in this combination. Fluxes are
integrated over the entire BP+RP pseudo-pixel
ranges
250-258 F9.1 e-/s FMax ? Maximal integrated BP+RP flux of the
components in this combination. Fluxes are
integrated over the entire BP+RP pseudo-pixel
ranges
260-277 A18 --- Nbp ? Number of epoch BP spectra of the components
in this combination (1)
279-296 A18 --- Nrp ? Number of epoch RP spectra of the components
in this combination (1)
298-300 I3 --- NXpMin ? Minimal value in Nbp and Nrp
302-348 A47 e-/s Fbp ? Integrated BP flux of the components in
this combination (1) (2)
350-396 A47 e-/s Frp ? Integrated RP flux of the components in
this combination (1) (2)
398-438 A41 e-/s e_Fbp ? Uncertainties on Fbp (1)
440-480 A41 e-/s e_Frp ? Uncertainties on Frp (1)
482-522 A41 --- Chi2rBp ? Reduced chi-square coming from the
resampling of the epoch BP spectra of the
components in this combination (1) (4)
524-564 A41 --- Chi2rRp ? Reduced chi-square coming from the
resampling of the epoch RP spectra of the
components in this combination (1) (4)
566-571 F6.3 --- Chi2rMax ? Maximal value in Chi2rBp and Chi2rRp.
Empty if Chi2rBp and Chi2rRp contain NaN's
573-601 A29 --- DofBp ? Degree of freedom associated with
Chi2rBp (1)
603-631 A29 --- DofRp ? Degree of freedom associated with
Chi2rRp (1)
633-673 A41 --- SnrBp ? S/N of the resampled BP spectra of the
components in this combination (1) (5)
675-715 A41 --- SnrRp ? S/N of the resampled RP spectra of the
components in this combination (1) (5)
717 A1 --- Class [CL] Status of this combination (6)
719-742 A24 --- Known ? Lens identifier
744-762 A19 --- BibCode ? Bibliographic code reporting the discovery.
Confirmed lenses discovered by the Gaia GraL
group that are not yet published have the
special value BibCode="GraL2024InPrep"
764-773 E10.3 --- Scomb [0/1]? Combined score
--------------------------------------------------------------------------------
Note (1): Field containing information that are specific to each component in
the combination. Component information are separated by slashes '/'
and contain Ncomb elements. Example: if Ncomb=3, Comps="2/3/4" and
Fbp="103.1/39.1/261.7", then component 2 has Fbp=103.1, component 3
has Fbp=39.1 and component 4 has Fbp=261.7.
Note (2): Computed over the 399.55-663.33 nm wavelength range in BP and over the
644.79-1006.7 nm wavelength range in RP.
Note (3): Bit Value Description:
--- ----- -----------
0 1 This is a sub-combination of all the available components,
raised if Ncomp != Ncomb
1 2 Chi2r was not computed
2 4 Some of the Chi2rBp or Chi2rRp can not be computed
3 8 Some spectra are based on less than 5 transits
4 16 Some of the integrated flux, Fbp or Frp are negative
Note (4): Large values of Chi2rBp or Chi2Rp are indicative of an improper
resampling and/or artefacts in the epoch spectra.
Note (5): S/N of the flux vector, f, having uncertainties given by ferr is here
defined as |f|2/|ferr|2-1.
Note (6): L are known lenses while C are contaminants.
Contaminants include
(a) unknown lenses as of January 21, 2022
(b) candidate lenses whose status is inconclusive
(c) known lenses with components that are not lensed images: stars,
lensing galaxy(ies) or QSO(s) along the line-of-sight.
Note (7): All combinations of 2-6 components from the multiplets are considered
to enable the detection of cases consisting of multiple images of a lens
system, plus contaminants (e.g. deflecting galaxy or nearby star)
Note (8): ERT score:
If Ncomb=4, then this parameter corresponds to the ERT score computed
based on the ABCD model.
If Ncomb=3, then this field is taken as the maximum of SertABC, SertABD,
SertACD, and SertBCD
--------------------------------------------------------------------------------
Byte-by-byte Description of file: table3.dat
--------------------------------------------------------------------------------
Bytes Format Units Label Explanations
--------------------------------------------------------------------------------
1- 7 I7 --- Seq Unique combination identifier
9- 35 A27 --- Name Name of the gravitational lens candidate,
taken from I/361/lenscand,
DR3GaiaHHMMSS.sss+DDMMSS.ss
37- 38 A2 --- Grade Lensing grade (1)
40- 53 F14.10 deg RAdeg Mean right ascension of the QSO (ICRS)
55- 68 F14.10 deg DEdeg Mean declination of the QSO (ICRS)
70- 73 F4.2 --- SertABCD [0/1]? ERT score associated with this candidate
75- 79 F5.3 --- SHesiod [0/1]? Minimal HESIOD score amongst the
components in this combination
81- 88 F8.3 --- Gof ? Goodness of fit (2)
90- 99 F10.3 --- SWd ? Maximal Wasserstein distance between any two
pair of components in this combination (2)
101-110 E10.3 --- Scomb [0/1]? Combined score
112-118 I7 --- SpecSeq ? Unique combination identifier of the pair of
components selected for computing Gof and SWd
--------------------------------------------------------------------------------
Note (1): Grade Description as follows:
A+ = Promising candidate where all components have similar spectra, image(s)
that support the lensing hypothesis while exhibiting a potential
deflector
A- = Promising candidate with a potential deflector, but inconclusive spectra
B+ = Plausible candidate with interesting lens-like features
B- = Plausible candidate with low-confidence lens-like features
Note (2): If the combination is composed of more than two components, we
selected the pair of components having the most convincing spectra for the
computation of Gof and SWd. The selected pair is then identified by the
SpecSeq identifier.
--------------------------------------------------------------------------------
Acknowledgements:
Alberto Krone-Martins, algol(at)sim.ul.pt
Ludovic Delchambre, ldelchambre(at)uliege.be
References:
Krone-Martins et al., GraL paper I 2018A&A...616L..11K 2018A&A...616L..11K
Ducourant et al., GraL paper II 2018A&A...618A..56D 2018A&A...618A..56D, Cat. J/A+A/618/A56
Delchambre et al., GraL paper III 2019A&A...622A.165D 2019A&A...622A.165D, Cat. J/A+A/622/A165
Wertz et al., GraL Paper IV 2019A&A...628A..17W 2019A&A...628A..17W
Krone-Martins et al., GraL Paper V 2019arXiv191208977K 2019arXiv191208977K
Stern et al., GraL Paper VI 2021ApJ...921...42S 2021ApJ...921...42S, Cat. J/ApJ/921/42
Connor et al., GraL Paper VII 2022ApJ...927...45C 2022ApJ...927...45C
(End) Patricia Vannier [CDS] 05-Mar-2024