We report the discovery of a candidate to quadrupole gravitationally lensed
system KiDS0239-3211 based on the public data release 3 of the KiDS survey and
machine learning techniques

Agnello, A.

Bannikova, E.

Getman, F. I.

Khramtsov, V.

Napolitano, N. R.

Sergeyev, A.

Spiniello, C.

Tortora, C.

Research Notes of the AAS

English

arXiv

We report the discovery of a candidate to quadrupole gravitationally lensed system KiDS0239-3211 based on the public data release 3 of the KiDS survey and machine learning techniques

SPINIELLO, CHIARA

NAPOLITANO, NICOLA ROSARIO

TORTORA, CRESCENZO

GETMAN, FEDOR

OA@INAF - Istituto Nazionale di Astrofisica

2018Publication Year2021-01-25T10:36:34ZAcceptance in OA@INAFKiDS0239-3211: A New Gravitational Quadruple Lens CandidateTitleSergeyev, A.; SPINIELLO, CHIARA; Khramtsov, V.; NAPOLITANO, NICOLA ROSARIO; Bannikova, E.; et al.Authors10.3847/2515-5172/aae6c5DOIhttp://hdl.handle.net/20.500.12386/29960HandleRESEARCH NOTES OF THE AASJournal2NumberDraft version October 4, 2018Typeset using LATEX RNAAS style in AASTeX62KiDS0239-3211: A new gravitational quadruple lens candidateA. Sergeyev,1, 2 C. Spiniello,3, 4 V. Khramtsov,1, 5 N. R. Napolitano,3 E. Bannikova,1 C. Tortora,6 F. I. Getman,3 andA. Agnello41V.N. Karazin Kharkiv National University, Ukraine2Institute of Radio Astronomy of the National Academy of Sciences of Ukraine3INAF - Osservatorio Astronomico di Capodimonte, Naples, Italy4European Southern Observatory, Garching, Germany5Department of Astronomy and Space Informatics V.N. Karazin Kharkiv National University Kharkiv, Ukraine6INAF-Osservatorio Astrofisico di Arcetri, Firenze, ItalyKeywords: gravitational lensing: strong – galaxies: quasarsINTRODUCTIONStrongly lensed quasars (SLQSOs), particularly quadruply lensed systems, are very rare (Oguri & Marshall 2010),but very valuable probes of cosmology and extragalactic astrophysics.With the KiDS Strongly lensed QUAsar Detection project (KiDS-SQuaD, Spiniello et al. 2018, hereafter S18) wehave started a systematic census of lensed quasars in the Kilo Degree Survey (KiDS, de Jong et al. 2015), takingadvantage from the high spatial resolution of VST (0.2′′/pixel) and its stringent seeing constraints (< 0.8′′ in r-band).In S18 we selected qso-like objects based on infrared and optical colors and then used different methods to identifymultiple systems, that we then visually inspected. However, with these methods, the number of candidates highlydepends on the (somehow arbitrary and often calibrated on previous finding) selection criteria. Generally this numberis of the order of thousands every 100 deg2, making the visual inspection long and tedious. Thus, to make our researchmore effective and suitable to deal with larger amount of data coming with future data releases and new wide-skysurveys (e.g. Euclid or LSST), we developed a new method based on machine learning. These techniques have thegreat advantage to explore, with little computing time, large amount of candidates with less stringent pre-selectionsand with reasonably high precision (recovery rate) and little contamination (spurious detection). These have beenapplied already for the search of strong gravitational arcs in KiDS (Petrillo et al. 2018) and SLQSOs in other wide-skySurveys (Agnello et al. 2015).MINING STRONG LENSED QUASARS WITH MACHINE LEARNINGAlthough the combination of near-infrared and optical colours is the most effective way to separate quasars fromstars within photometric surveys (Akhmetov et al. 2017), infrared information is not always available and often notdeep enough. For this reason, we developed a machine learning based method to separate QSOs from stars using only 4photometric optical bands (u,g,r,i). We used Random Forests classifier (self-written python code) with spectroscopicallyconfirmed stars (622, 052) and QSOs (484, 372) from SDSS DR14 (Abolfathi et al. 2018). We worked in the 6-dimensional colour space, made of all possible differences of magnitudes in the different bands. The classification wasperformed with a 5-fold cross-validation, obtaining 99% of purity and 65% of completeness of the quasar validatingsample. We thus apply this procedure on the KiDS-DR3 catalog and then select QSO-like multiple sources (with aseparation ≤ 10′′). We ended up with 3187 candidates, for which we inspected the combined ugr KiDS cutouts. Adetailed presentation of the method will be presented in a future publication.Corresponding author: Alexey Sergeyevalexey.v.sergeyev@gmail.comarXiv:1810.01633v1  [astro-ph.GA]  3 Oct 20182KIDS 0239-3211KiDS 0239-3211 (Ra: 02:39:29.69, Dec: −32:11:29.66) is without doubt the most promising candidate we found inthe public KiDS-DR3.In the figure we show the combined gri KiDS cutout of the quad, as well as single band images and GALFIT modeland residuals. The system is composed by a red galaxy in the middle (G) surrounded by five blue blobs within fewarcsec distance (listed in the Table) We obtained differential photometry directly from GALFIT, calibrating the zero-point with a reference star from the KiDS catalog. We note that all blobs have consistent colors, within the errors,which support the lensing hypothesis.Given the geometry, colors and shape of the blobs, we believe that four of them are multiple images of a point-likesource (A, B, C, D in green) whereas the fifth, more distant one is a contaminant (X in cyan). This hypothesis isfurther confirmed by the machine learning based estimate of the photometric redshifts (z ∼ 0.5 for G and X andz ∼ 1.6 − 2.0 for A and C, from the catalog in de Jong et al. 2017 and derived using the Multi Layer Perceptron withQuasi Newton Algorithm technique presented in Cavuoti et al. 2015).3DISCUSSION AND CONCLUSIONSThe discovery of KiDS 0239-3211, missed by other methods, demonstrates that our machine learning set-up, althoughstill preliminary, represents a considerable step further to effectively find new SLQSOs in present and future publicwide-sky photometric surveys.Nevertheless, to unambiguously confirm the lensing nature of the system and to translate the ‘geometric’ lens modelresults (e.g. Einstein radius) into physical measurements of luminous and dark masses, the redshifts of the sourceand of the deflector are needed. We are therefore setting up a systematic, multi-site, multi-facility campaign forspectroscopic observation of the best candidates in KiDS, including KiDS 0239-3211, but the publication of the objectcoordinates and fluxes is meant to encourage the community to help out with this task.ACKNOWLEDGMENTSWe thank the organizators and participants of the Italy-Ukraine Collaboration in Astronomy Meeting, during whichthis discovery was made. We acknowledge the KiDS collaboration for the work done to make the data publicly available.CS and NRN have received funding from the European Union’s Horizon 2020 research and innovation programme.under the Marie Sk lodowska-Curie actions grant agreements No 664931 and No 721463 to the SUNDIAL ITN network.4REFERENCESAbolfathi, B., Aguado, D. S., Aguilar, G., et al. 2018,ApJS, 235, 42Akhmetov V. S., Fedorov P. N., Velichko A. B., ShulgaV. M., 2017, MNRAS, 469, 763Agnello, A., Kelly, B. C., Treu, T., & Marshall, P. J. 2015,MNRAS, 448, 1446Cavuoti et al. 2015, MNRAS, 452, 3100de Jong J. T. A., Verdoes Kleijn, G. A., Boxhoorn, D. R.,et al., 2015, A&A, 582, A62de Jong, J. T. A., Verdois Kleijn, G. A., Erben, T., et al.2017, A&A, 604, A134Oguri, M., & Marshall, P. J. 2010, MNRAS, 405, 2579Petrillo, C. E., Tortora, C., Chatterjee, S., et al. 2018,arXiv:1807.04764Spiniello, C., Agnello, A., Napolitano, N. R., et al. 2018,MNRAS, 480, 1163

KiDS0239-3211: A New Gravitational Quadruple Lens Candidate

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KiDS0239-3211: A new gravitational quadruple lens candidate

KiDS0239-3211: A new gravitational quadruple lens candidate

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