Catalog of quasars from the Kilo-Degree Survey Data Release 3
A&A, 624 (2019) A13
Published online: 2019-04-01
Articles citing this article
The Citing articles tool gives a list of articles citing the current article.
The citing articles come from EDP Sciences database, as well as other publishers participating in CrossRef Cited-by Linking Program. You can set up your personal account to receive an email alert each time this article is cited by a new article (see the menu on the right-hand side of the abstract page).
Cited article:
This article has been cited by the following article(s):
Morpho-photometric Classification of KiDS DR5 Sources Based on Neural Networks: A Comprehensive Star–Quasar–Galaxy Catalog
Hai-Cheng Feng, Rui Li, Nicola R. Napolitano, Sha-Sha Li, J. M. Bai, Yue Dong, Ran Li, H. T. Liu, Kai-Xing Lu, Zhi-Wei Pan, Mario Radovich, Huan-Yuan Shan, Jian-Guo Wang, Wen-Zhe Xi, Ling-Hua Xie, Zun-Li Yuan and Yang-Wei ZhangThe Astrophysical Journal Supplement Series 279 (1) 26 (2025)
https://doi.org/10.3847/1538-4365/adde5a
A Brief Review of Unsupervised Machine Learning Algorithms in Astronomy: Dimensionality Reduction and Clustering
Chih-Ting Kuo, Duo Xu and Rachel FriesenUniverse 11 (12) 412 (2025)
https://doi.org/10.3390/universe11120412
QZO: A Catalog of 5 Million Quasars from the Zwicky Transient Facility
S. J. Nakoneczny, M. J. Graham, D. Stern, G. Helou, S. G. Djorgovski, E. C. Bellm, T. X. Chen, R. Dekany, A. Drake, A. A. Mahabal, T. A. Prince, R. Riddle, B. Rusholme and N. SravanThe Astrophysical Journal 992 (1) 153 (2025)
https://doi.org/10.3847/1538-4357/adf4e4
Semi-supervised classification of stars, galaxies and quasars using K-means and random-forest approaches
V. Asadi, H. Haghi and A. H. ZonooziAstronomy & Astrophysics 700 A259 (2025)
https://doi.org/10.1051/0004-6361/202555620
Predicting the Spectroscopic Features of Galaxies by Applying Manifold Learning on Their Broadband Colors: Proof of Concept and Potential Applications for Euclid, Roman, and Rubin LSST
Marziye Jafariyazani, Daniel Masters, Andreas L. Faisst, Harry I. Teplitz and Olivier IlbertThe Astrophysical Journal 967 (1) 60 (2024)
https://doi.org/10.3847/1538-4357/ad38b8
Machine Learning–based Search of High-redshift Quasars
Guangping 广平 Ye 叶, Huanian 华年 Zhang 张 and Qingwen 庆文 Wu 吴The Astrophysical Journal Supplement Series 275 (1) 19 (2024)
https://doi.org/10.3847/1538-4365/ad79ee
Model independent estimation of expansion rate from low and high redshift SNIa
Mohammad Hadi Mohammadi and Ahmad MehrabiInternational Journal of Modern Physics D 33 (13) (2024)
https://doi.org/10.1142/S0218271824500512
Applying machine learning to Galactic Archaeology: how well can we recover the origin of stars in Milky Way-like galaxies?
Andrea Sante, Andreea S Font, Sandra Ortega-Martorell, Ivan Olier and Ian G McCarthyMonthly Notices of the Royal Astronomical Society 531 (4) 4363 (2024)
https://doi.org/10.1093/mnras/stae1398
The miniJPAS survey quasar selection – II. Machine learning classification with photometric measurements and uncertainties
Natália V N Rodrigues, L Raul Abramo, Carolina Queiroz, Ginés Martínez-Solaeche, Ignasi Pérez-Ràfols, Silvia Bonoli, Jonás Chaves-Montero, Matthew M Pieri, Rosa M González Delgado, Sean S Morrison, Valerio Marra, Isabel Márquez, A Hernán-Caballero, L A Díaz-García, Narciso Benítez, A Javier Cenarro, Renato A Dupke, Alessandro Ederoclite, Carlos López-Sanjuan, Antonio Marín-Franch, Claudia Mendes de Oliveira, Mariano Moles, Laerte Sodré, Jesús Varela, Héctor Vázquez Ramió and Keith TaylorMonthly Notices of the Royal Astronomical Society 520 (3) 3494 (2023)
https://doi.org/10.1093/mnras/stac2836
Depthwise convolutional neural network for multiband automatic quasars classification in ATLAS
Astrid E San-Martín-Jiménez, Karim Pichara, Luis Felipe Barrientos, Felipe Rojas and Cristobal Moya-SierraltaMonthly Notices of the Royal Astronomical Society 524 (4) 5080 (2023)
https://doi.org/10.1093/mnras/stad1859
Photometric classification of quasars from ALHAMBRA survey using random forest
Benjamín Arroquia-Cuadros, Néstor Sánchez, Vicent Gómez, et al.Astronomy & Astrophysics 673 A48 (2023)
https://doi.org/10.1051/0004-6361/202245531
Machine learning-based photometric classification of galaxies, quasars, emission-line galaxies, and stars
Fatemeh Zahra Zeraatgari, Fatemeh Hafezianzadeh, Yanxia Zhang, Liquan Mei, Ashraf Ayubinia, Amin Mosallanezhad and Jingyi ZhangMonthly Notices of the Royal Astronomical Society 527 (3) 4677 (2023)
https://doi.org/10.1093/mnras/stad3436
Discovery of strongly lensed quasars in the Ultraviolet Near Infrared Optical Northern Survey (UNIONS)
J. H. H. Chan, C. Lemon, F. Courbin, et al.Astronomy & Astrophysics 659 A140 (2022)
https://doi.org/10.1051/0004-6361/202142389
The Quasar Luminosity Function at z ∼ 5 via Deep Learning and Bayesian Information Criterion
Suhyun Shin, Myungshin Im and Yongjung KimThe Astrophysical Journal 937 (1) 32 (2022)
https://doi.org/10.3847/1538-4357/ac854b
Using Multivariate Imputation by Chained Equations to Predict Redshifts of Active Galactic Nuclei
Spencer James Gibson, Aditya Narendra, Maria Giovanna Dainotti, et al.Frontiers in Astronomy and Space Sciences 9 (2022)
https://doi.org/10.3389/fspas.2022.836215
Galaxy morphoto-Z with neural Networks (GaZNets)
Rui Li, Nicola R. Napolitano, Haicheng Feng, et al.Astronomy & Astrophysics 666 A85 (2022)
https://doi.org/10.1051/0004-6361/202244081
The Seventeenth Data Release of the Sloan Digital Sky Surveys: Complete Release of MaNGA, MaStar, and APOGEE-2 Data
Abdurro’uf, Katherine Accetta, Conny Aerts, Víctor Silva Aguirre, Romina Ahumada, Nikhil Ajgaonkar, N. Filiz Ak, Shadab Alam, Carlos Allende Prieto, Andrés Almeida, Friedrich Anders, Scott F. Anderson, Brett H. Andrews, Borja Anguiano, Erik Aquino-Ortíz, Alfonso Aragón-Salamanca, Maria Argudo-Fernández, Metin Ata, Marie Aubert, Vladimir Avila-Reese, Carles Badenes, Rodolfo H. Barbá, Kat Barger, Jorge K. Barrera-Ballesteros, Rachael L. Beaton, et al.The Astrophysical Journal Supplement Series 259 (2) 35 (2022)
https://doi.org/10.3847/1538-4365/ac4414
Inferring galaxy dark halo properties from visible matter with machine learning
Rodrigo von Marttens, Luciano Casarini, Nicola R Napolitano, et al.Monthly Notices of the Royal Astronomical Society 516 (3) 3924 (2022)
https://doi.org/10.1093/mnras/stac2449
Random Forests as a Viable Method to Select and Discover High-redshift Quasars
Lukas Wenzl, Jan-Torge Schindler, Xiaohui Fan, Irham Taufik Andika, Eduardo Bañados, Roberto Decarli, Knud Jahnke, Chiara Mazzucchelli, Masafusa Onoue, Bram P. Venemans, Fabian Walter and Jinyi YangThe Astronomical Journal 162 (2) 72 (2021)
https://doi.org/10.3847/1538-3881/ac0254
VEXAS: VISTA EXtension to Auxiliary Surveys
V. Khramtsov, C. Spiniello, A. Agnello and A. SergeyevAstronomy & Astrophysics 651 A69 (2021)
https://doi.org/10.1051/0004-6361/202040131
Active galactic nuclei catalog from the AKARI NEP-Wide field
Artem Poliszczuk, Agnieszka Pollo, Katarzyna Małek, et al.Astronomy & Astrophysics 651 A108 (2021)
https://doi.org/10.1051/0004-6361/202040219
Identifying RR Lyrae Variable Stars in Six Years of the Dark Energy Survey
K. M. Stringer, A. Drlica-Wagner, L. Macri, C. E. Martínez-Vázquez, A. K. Vivas, P. Ferguson, A. B. Pace, A. R. Walker, E. Neilsen, K. Tavangar, W. Wester, T. M. C. Abbott, M. Aguena, S. Allam, D. Bacon, K. Bechtol, E. Bertin, D. Brooks, D. L. Burke, A. Carnero Rosell, M. Carrasco Kind, J. Carretero, M. Costanzi, M. Crocce, L. N. da Costa, et al.The Astrophysical Journal 911 (2) 109 (2021)
https://doi.org/10.3847/1538-4357/abe873
Intelligent Astrophysics
Maurizio D’Addona, Giuseppe Riccio, Stefano Cavuoti, Crescenzo Tortora and Massimo BresciaEmergence, Complexity and Computation, Intelligent Astrophysics 39 225 (2021)
https://doi.org/10.1007/978-3-030-65867-0_10
Swift Multiwavelength Follow-up of LVC S200224ca and the Implications for Binary Black Hole Mergers
N. J. Klingler, A. Lien, S. R. Oates, J. A. Kennea, P. A. Evans, A. Tohuvavohu, B. Zhang, K. L. Page, S. B. Cenko, S. D. Barthelmy, A. P. Beardmore, M. G. Bernardini, A. A. Breeveld, P. J. Brown, D. N. Burrows, S. Campana, G. Cusumano, A. D’Aì, P. D’Avanzo, V. D’Elia, M. de Pasquale, S. W. K. Emery, J. Garcia, P. Giommi, C. Gronwall, et al.The Astrophysical Journal 907 (2) 97 (2021)
https://doi.org/10.3847/1538-4357/abd2c3
Photometric selection and redshifts for quasars in the Kilo-Degree Survey Data Release 4
S. J. Nakoneczny, M. Bilicki, A. Pollo, et al.Astronomy & Astrophysics 649 A81 (2021)
https://doi.org/10.1051/0004-6361/202039684
Intelligent Astrophysics
Vladislav Khramtsov, Volodymyr Akhmetov, Peter Fedorov, et al.Emergence, Complexity and Computation, Intelligent Astrophysics 39 137 (2021)
https://doi.org/10.1007/978-3-030-65867-0_6
Deep learning applications based on SDSS photometric data: detection and classification of sources
Zhendong He, Bo Qiu, A-Li Luo, et al.Monthly Notices of the Royal Astronomical Society 508 (2) 2039 (2021)
https://doi.org/10.1093/mnras/stab2243
Predicting the Redshift of γ-Ray-loud AGNs Using Supervised Machine Learning
Maria Giovanna Dainotti, Malgorzata Bogdan, Aditya Narendra, Spencer James Gibson, Blazej Miasojedow, Ioannis Liodakis, Agnieszka Pollo, Trevor Nelson, Kamil Wozniak, Zooey Nguyen and Johan LarrsonThe Astrophysical Journal 920 (2) 118 (2021)
https://doi.org/10.3847/1538-4357/ac1748
Surveying the reach and maturity of machine learning and artificial intelligence in astronomy
Christopher J. Fluke and Colin JacobsWIREs Data Mining and Knowledge Discovery 10 (2) (2020)
https://doi.org/10.1002/widm.1349
Unsupervised star, galaxy, QSO classification
C. H. A. Logan and S. FotopoulouAstronomy & Astrophysics 633 A154 (2020)
https://doi.org/10.1051/0004-6361/201936648
The optical luminosity function of LOFAR radio-selected quasars at 1.4 ≤ z ≤ 5.0 in the NDWFS-Boötes field
E. Retana-Montenegro and H. J. A. RöttgeringAstronomy & Astrophysics 636 A12 (2020)
https://doi.org/10.1051/0004-6361/201936577
Identifying galaxies, quasars, and stars with machine learning: A new catalogue of classifications for 111 million SDSS sources without spectra
A. O. Clarke, A. M. M. Scaife, R. Greenhalgh and V. GrigutaAstronomy & Astrophysics 639 A84 (2020)
https://doi.org/10.1051/0004-6361/201936770
The Northern Extragalactic WISE × Pan-STARRS (NEWS) catalogue
Vladislav Khramtsov, Volodymyr Akhmetov and Peter FedorovAstronomy & Astrophysics 644 A69 (2020)
https://doi.org/10.1051/0004-6361/201834122
The fourth data release of the Kilo-Degree Survey: ugri imaging and nine-band optical-IR photometry over 1000 square degrees
K. Kuijken, C. Heymans, A. Dvornik, et al.Astronomy & Astrophysics 625 A2 (2019)
https://doi.org/10.1051/0004-6361/201834918
Catalogues of active galactic nuclei from Gaia and unWISE data
Yiping Shu, Sergey E Koposov, N Wyn Evans, et al.Monthly Notices of the Royal Astronomical Society 489 (4) 4741 (2019)
https://doi.org/10.1093/mnras/stz2487
Astroinformatics-based search for globular clusters in the Fornax Deep Survey
G Angora, M Brescia, S Cavuoti, et al.Monthly Notices of the Royal Astronomical Society 490 (3) 4080 (2019)
https://doi.org/10.1093/mnras/stz2801
KiDS-SQuaD
Vladislav Khramtsov, Alexey Sergeyev, Chiara Spiniello, et al.Astronomy & Astrophysics 632 A56 (2019)
https://doi.org/10.1051/0004-6361/201936006
A classifier to detect elusive astronomical objects through photometry
Rama Krishna Sai S Gorthi, S K Ghosh, S Vig and Bhavana D.Monthly Notices of the Royal Astronomical Society 488 (2) 2263 (2019)
https://doi.org/10.1093/mnras/stz1823