The Quasar Catalogue for S-PLUS DR4 (QuCatS) and the estimation of photometric redshifts
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| Autores principales: | , , , , , , , , , , , , , , |
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| Formato: | Preprint |
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2024
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| author | Nakazono, L. Valença, R. R. Soares, G. Izbicki, R. Ivezić, Ž. Lima, E. V. R. Hirata, N. S. T. Sodré Jr., L. Overzier, R. Almeida-Fernandes, F. Schwarz, G. B. Oliveira Schoenell, W. Kanaan, A. Ribeiro, T. de Oliveira, C. Mendes |
| author_facet | Nakazono, L. Valença, R. R. Soares, G. Izbicki, R. Ivezić, Ž. Lima, E. V. R. Hirata, N. S. T. Sodré Jr., L. Overzier, R. Almeida-Fernandes, F. Schwarz, G. B. Oliveira Schoenell, W. Kanaan, A. Ribeiro, T. de Oliveira, C. Mendes |
| contents | The advent of massive broad-band photometric surveys enabled photometric redshift estimates for unprecedented numbers of galaxies and quasars. These estimates can be improved using better algorithms or by obtaining complementary data such as narrow-band photometry, and broad-band photometry over an extended wavelength range. We investigate the impact of both approaches on photometric redshifts for quasars using data from Southern Photometric Local Universe Survey (S-PLUS) DR4, Galaxy Evolution Explorer (GALEX) DR6/7, and the unWISE catalog for the Wide-field Infrared Survey Explorer (WISE) in three machine learning methods: Random Forest, Flexible Conditional Density Estimation (FlexCoDE), and Bayesian Mixture Density Network (BMDN). Including narrow-band photometry improves the root-mean-square error by 11% in comparison to a model trained with only broad-band photometry. Narrow-band information only provided an improvement of 3.8% when GALEX and WISE colours were included. Thus narrow bands play a more important role for objects that do not have GALEX or WISE counterparts, which respectively makes 92% and 25% of S-PLUS data considered here. Nevertheless, the inclusion of narrow-band information provided better estimates of the probability density functions obtained with FlexCoDE and BMDN. We publicly release a value-added catalogue of photometrically selected quasars with the photo-z predictions from all methods studied here. The catalogue provided with this work covers the S-PLUS DR4 area (~3000deg$^2$), containing 645 980, 244 912, 144 991 sources with the probability of being a quasar higher than, 80%, 90%, 95% up to r < 21.3 and good photometry quality in the detection image. More quasar candidates can be retrieved from the S-PLUS data base by considering less restrictive selection criteria. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2404_09925 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | The Quasar Catalogue for S-PLUS DR4 (QuCatS) and the estimation of photometric redshifts Nakazono, L. Valença, R. R. Soares, G. Izbicki, R. Ivezić, Ž. Lima, E. V. R. Hirata, N. S. T. Sodré Jr., L. Overzier, R. Almeida-Fernandes, F. Schwarz, G. B. Oliveira Schoenell, W. Kanaan, A. Ribeiro, T. de Oliveira, C. Mendes Cosmology and Nongalactic Astrophysics Instrumentation and Methods for Astrophysics The advent of massive broad-band photometric surveys enabled photometric redshift estimates for unprecedented numbers of galaxies and quasars. These estimates can be improved using better algorithms or by obtaining complementary data such as narrow-band photometry, and broad-band photometry over an extended wavelength range. We investigate the impact of both approaches on photometric redshifts for quasars using data from Southern Photometric Local Universe Survey (S-PLUS) DR4, Galaxy Evolution Explorer (GALEX) DR6/7, and the unWISE catalog for the Wide-field Infrared Survey Explorer (WISE) in three machine learning methods: Random Forest, Flexible Conditional Density Estimation (FlexCoDE), and Bayesian Mixture Density Network (BMDN). Including narrow-band photometry improves the root-mean-square error by 11% in comparison to a model trained with only broad-band photometry. Narrow-band information only provided an improvement of 3.8% when GALEX and WISE colours were included. Thus narrow bands play a more important role for objects that do not have GALEX or WISE counterparts, which respectively makes 92% and 25% of S-PLUS data considered here. Nevertheless, the inclusion of narrow-band information provided better estimates of the probability density functions obtained with FlexCoDE and BMDN. We publicly release a value-added catalogue of photometrically selected quasars with the photo-z predictions from all methods studied here. The catalogue provided with this work covers the S-PLUS DR4 area (~3000deg$^2$), containing 645 980, 244 912, 144 991 sources with the probability of being a quasar higher than, 80%, 90%, 95% up to r < 21.3 and good photometry quality in the detection image. More quasar candidates can be retrieved from the S-PLUS data base by considering less restrictive selection criteria. |
| title | The Quasar Catalogue for S-PLUS DR4 (QuCatS) and the estimation of photometric redshifts |
| topic | Cosmology and Nongalactic Astrophysics Instrumentation and Methods for Astrophysics |
| url | https://arxiv.org/abs/2404.09925 |