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1. Validation of the Scientific Program for the Dark Energy Spectroscopic Instrument

Author

DESI Collaboration, A. G. Adame, J. Aguilar, S. Ahlen, S. Alam, G. Aldering, D. M. Alexander, R. Alfarsy, C. Allende Prieto, M. Alvarez, O. Alves, A. Anand, F. Andrade-Oliveira, E. Armengaud, J. Asorey, S. Avila, A. Aviles, S. Bailey, A. Balaguera-Antolínez, O. Ballester, C. Baltay, A. Bault, J. Bautista, J. Behera, S. F. Beltran, S. BenZvi, L. Beraldo e Silva, J. R. Bermejo-Climent, A. Berti, R. Besuner, F. Beutler, D. Bianchi, C. Blake, R. Blum, A. S. Bolton, S. Brieden, A. Brodzeller, D. Brooks, Z. Brown, E. Buckley-Geer, E. Burtin, L. Cabayol-Garcia, Z. Cai, R. Canning, L. Cardiel-Sas, A. Carnero Rosell, F. J. Castander, J. L. Cervantes-Cota, S. Chabanier, E. Chaussidon, J. Chaves-Montero, S. Chen, X. Chen, C. Chuang, T. Claybaugh, S. Cole, A. P. Cooper, A. Cuceu, T. M. Davis, K. Dawson, R. de Belsunce, R. de la Cruz, A. de la Macorra, A. de Mattia, R. Demina, U. Demirbozan, J. DeRose, A. Dey, B. Dey, G. Dhungana, J. Ding, Z. Ding, P. Doel, R. Doshi, K. Douglass, A. Edge, S. Eftekharzadeh, D. J. Eisenstein, A. Elliott, S. Escoffier, P. Fagrelius, X. Fan, K. Fanning, V. A. Fawcett, S. Ferraro, J. Ereza, B. Flaugher, A. Font-Ribera, D. Forero-Sánchez, J. E. Forero-Romero, C. S. Frenk, B. T. Gänsicke, L. Á. García, J. García-Bellido, C. Garcia-Quintero, L. H. Garrison, H. Gil-Marín, J. Golden-Marx, S. Gontcho A Gontcho, A. X. Gonzalez-Morales, V. Gonzalez-Perez, C. Gordon, O. Graur, D. Green, D. Gruen, J. Guy, B. Hadzhiyska, C. Hahn, J. J. Han, M. M. S Hanif, H. K. Herrera-Alcantar, K. Honscheid, J. Hou, C. Howlett, D. Huterer, V. Iršič, M. Ishak, A. Jana, L. Jiang, J. Jimenez, Y. P. Jing, S. Joudaki, E. Jullo, R. Joyce, S. Juneau, N. Kizhuprakkat, N. G. Karaçaylı, T. Karim, R. Kehoe, S. Kent, A. Khederlarian, S. Kim, D. Kirkby, T. Kisner, F. Kitaura, J. Kneib, S. E. Koposov, A. Kovács, A. Kremin, A. Krolewski, B. L’Huillier, O. Lahav, A. Lambert, C. Lamman, T.-W. Lan, M. Landriau, D. Lang, J. U. Lange, J. Lasker, L. Le Guillou, A. Leauthaud, M. E. Levi, T. S. Li, E. Linder, A. Lyons, C. Magneville, M. Manera, C. J. Manser, D. Margala, P. Martini, P. McDonald, G. E. Medina, L. Medina-Varela, A. Meisner, J. Mena-Fernández, J. Meneses-Rizo, M. Mezcua, R. Miquel, P. Montero-Camacho, J. Moon, S. Moore, J. Moustakas, E. Mueller, J. Mundet, A. Muñoz-Gutiérrez, A. D. Myers, S. Nadathur, L. Napolitano, R. Neveux, J. A. Newman, J. Nie, G. Niz, P. Norberg, H. E. Noriega, E. Paillas, N. Palanque-Delabrouille, A. Palmese, P. Zhiwei, D. Parkinson, S. Penmetsa, W. J. Percival, A. Pérez-Fernández, I. Pérez-Ràfols, M. Pieri, C. Poppett, A. Porredon, F. Prada, R. Pucha, A. Raichoor, C. Ramírez-Pérez, S. Ramirez-Solano, M. Rashkovetskyi, C. Ravoux, A. Rocher, C. Rockosi, A. J. Ross, G. Rossi, R. Ruggeri, V. Ruhlmann-Kleider, C. G. Sabiu, K. Said, A. Saintonge, L. Samushia, E. Sanchez, C. Saulder, E. Schaan, E. F. Schlafly, D. Schlegel, D. Scholte, M. Schubnell, H. Seo, A. Shafieloo, R. Sharples, W. Sheu, J. Silber, F. Sinigaglia, M. Siudek, Z. Slepian, A. Smith, D. Sprayberry, L. Stephey, J. Suárez-Pérez, Z. Sun, T. Tan, G. Tarlé, R. Tojeiro, L. A. Ureña-López, R. Vaisakh, D. Valcin, F. Valdes, M. Valluri, M. Vargas-Magaña, A. Variu, L. Verde, M. Walther, B. Wang, M. S. Wang, B. A. Weaver, N. Weaverdyck, R. H. Wechsler, M. White, Y. Xie, J. Yang, C. Yèche, J. Yu, S. Yuan, H. Zhang, Z. Zhang, C. Zhao, Z. Zheng, R. Zhou, Z. Zhou, H. Zou, S. Zou, and Y. Zu

Subjects
Cosmology, Redshift surveys, Astronomy, QB1-991
Abstract

The Dark Energy Spectroscopic Instrument (DESI) was designed to conduct a survey covering 14,000 deg ^2 over 5 yr to constrain the cosmic expansion history through precise measurements of baryon acoustic oscillations (BAO). The scientific program for DESI was evaluated during a 5 month survey validation (SV) campaign before beginning full operations. This program produced deep spectra of tens of thousands of objects from each of the stellar Milky Way Survey (MWS), Bright Galaxy Survey (BGS), luminous red galaxy (LRG), emission line galaxy (ELG), and quasar target classes. These SV spectra were used to optimize redshift distributions, characterize exposure times, determine calibration procedures, and assess observational overheads for the 5 yr program. In this paper, we present the final target selection algorithms, redshift distributions, and projected cosmology constraints resulting from those studies. We also present a One-Percent Survey conducted at the conclusion of SV covering 140 deg ^2 using the final target selection algorithms with exposures of a depth typical of the main survey. The SV indicates that DESI will be able to complete the full 14,000 deg ^2 program with spectroscopically confirmed targets from the MWS, BGS, LRG, ELG, and quasar programs with total sample sizes of 7.2, 13.8, 7.46, 15.7, and 2.87 million, respectively. These samples will allow exploration of the Milky Way halo, clustering on all scales, and BAO measurements with a statistical precision of 0.28% over the redshift interval z < 1.1, 0.39% over the redshift interval 1.1 < z < 1.9, and 0.46% over the redshift interval 1.9 < z < 3.5.

Published
2024
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2. The Early Data Release of the Dark Energy Spectroscopic Instrument

Author

DESI Collaboration, A. G. Adame, J. Aguilar, S. Ahlen, S. Alam, G. Aldering, D. M. Alexander, R. Alfarsy, C. Allende Prieto, M. Alvarez, O. Alves, A. Anand, F. Andrade-Oliveira, E. Armengaud, J. Asorey, S. Avila, A. Aviles, S. Bailey, A. Balaguera-Antolínez, O. Ballester, C. Baltay, A. Bault, J. Bautista, J. Behera, S. F. Beltran, S. BenZvi, L. Beraldo e Silva, J. R. Bermejo-Climent, A. Berti, R. Besuner, F. Beutler, D. Bianchi, C. Blake, R. Blum, A. S. Bolton, S. Brieden, A. Brodzeller, D. Brooks, Z. Brown, E. Buckley-Geer, E. Burtin, L. Cabayol-Garcia, Z. Cai, R. Canning, L. Cardiel-Sas, A. Carnero Rosell, F. J. Castander, J. L. Cervantes-Cota, S. Chabanier, E. Chaussidon, J. Chaves-Montero, S. Chen, X. Chen, C. Chuang, T. Claybaugh, S. Cole, A. P. Cooper, A. Cuceu, T. M. Davis, K. Dawson, R. de Belsunce, R. de la Cruz, A. de la Macorra, J. Della Costa, A. de Mattia, R. Demina, U. Demirbozan, J. DeRose, A. Dey, B. Dey, G. Dhungana, J. Ding, Z. Ding, P. Doel, R. Doshi, K. Douglass, A. Edge, S. Eftekharzadeh, D. J. Eisenstein, A. Elliott, J. Ereza, S. Escoffier, P. Fagrelius, X. Fan, K. Fanning, V. A. Fawcett, S. Ferraro, B. Flaugher, A. Font-Ribera, J. E. Forero-Romero, D. Forero-Sánchez, C. S. Frenk, B. T. Gänsicke, L. Á. García, J. García-Bellido, C. Garcia-Quintero, L. H. Garrison, H. Gil-Marín, J. Golden-Marx, S. Gontcho A Gontcho, A. X. Gonzalez-Morales, V. Gonzalez-Perez, C. Gordon, O. Graur, D. Green, D. Gruen, J. Guy, B. Hadzhiyska, C. Hahn, J. J. Han, M. M. S Hanif, H. K. Herrera-Alcantar, K. Honscheid, J. Hou, C. Howlett, D. Huterer, V. Iršič, M. Ishak, A. Jacques, A. Jana, L. Jiang, J. Jimenez, Y. P. Jing, S. Joudaki, R. Joyce, E. Jullo, S. Juneau, N. G. Karaçaylı, T. Karim, R. Kehoe, S. Kent, A. Khederlarian, S. Kim, D. Kirkby, T. Kisner, F. Kitaura, N. Kizhuprakkat, J. Kneib, S. E. Koposov, A. Kovács, A. Kremin, A. Krolewski, B. L’Huillier, O. Lahav, A. Lambert, C. Lamman, T.-W. Lan, M. Landriau, D. Lang, J. U. Lange, J. Lasker, A. Leauthaud, L. Le Guillou, M. E. Levi, T. S. Li, E. Linder, A. Lyons, C. Magneville, M. Manera, C. J. Manser, D. Margala, P. Martini, P. McDonald, G. E. Medina, L. Medina-Varela, A. Meisner, J. Mena-Fernández, J. Meneses-Rizo, M. Mezcua, R. Miquel, P. Montero-Camacho, J. Moon, S. Moore, J. Moustakas, E. Mueller, J. Mundet, A. Muñoz-Gutiérrez, A. D. Myers, S. Nadathur, L. Napolitano, R. Neveux, J. A. Newman, J. Nie, R. Nikutta, G. Niz, P. Norberg, H. E. Noriega, E. Paillas, N. Palanque-Delabrouille, A. Palmese, Z. Pan, D. Parkinson, S. Penmetsa, W. J. Percival, A. Pérez-Fernández, I. Pérez-Ràfols, M. Pieri, C. Poppett, A. Porredon, S. Pothier, F. Prada, R. Pucha, A. Raichoor, C. Ramírez-Pérez, S. Ramirez-Solano, M. Rashkovetskyi, C. Ravoux, A. Rocher, C. Rockosi, A. J. Ross, G. Rossi, R. Ruggeri, V. Ruhlmann-Kleider, C. G. Sabiu, K. Said, A. Saintonge, L. Samushia, E. Sanchez, C. Saulder, E. Schaan, E. F. Schlafly, D. Schlegel, D. Scholte, M. Schubnell, H. Seo, A. Shafieloo, R. Sharples, W. Sheu, J. Silber, F. Sinigaglia, M. Siudek, Z. Slepian, A. Smith, M. T. Soumagnac, D. Sprayberry, L. Stephey, J. Suárez-Pérez, Z. Sun, T. Tan, G. Tarlé, R. Tojeiro, L. A. Ureña-López, R. Vaisakh, D. Valcin, F. Valdes, M. Valluri, M. Vargas-Magaña, A. Variu, L. Verde, M. Walther, B. Wang, M. S. Wang, B. A. Weaver, N. Weaverdyck, R. H. Wechsler, M. White, Y. Xie, J. Yang, C. Yèche, J. Yu, S. Yuan, H. Zhang, Z. Zhang, C. Zhao, Z. Zheng, R. Zhou, Z. Zhou, H. Zou, S. Zou, and Y. Zu

Subjects
Astronomy data reduction, Observational cosmology, Astronomy databases, Astronomy data analysis, Astronomy software, Surveys, Astronomy, QB1-991
Abstract

The Dark Energy Spectroscopic Instrument (DESI) completed its 5 month Survey Validation in 2021 May. Spectra of stellar and extragalactic targets from Survey Validation constitute the first major data sample from the DESI survey. This paper describes the public release of those spectra, the catalogs of derived properties, and the intermediate data products. In total, the public release includes good-quality spectral information from 466,447 objects targeted as part of the Milky Way Survey, 428,758 as part of the Bright Galaxy Survey, 227,318 as part of the Luminous Red Galaxy sample, 437,664 as part of the Emission Line Galaxy sample, and 76,079 as part of the Quasar sample. In addition, the release includes spectral information from 137,148 objects that expand the scope beyond the primary samples as part of a series of secondary programs. Here, we describe the spectral data, data quality, data products, Large-Scale Structure science catalogs, access to the data, and references that provide relevant background to using these spectra.

Published
2024
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3. The DESI Survey Validation: Results from Visual Inspection of the Quasar Survey Spectra

Author

David M. Alexander, Tamara M. Davis, E. Chaussidon, V. A. Fawcett, Alma X. Gonzalez-Morales, Ting-Wen Lan, Christophe Yèche, S. Ahlen, J. N. Aguilar, E. Armengaud, S. Bailey, D. Brooks, Z. Cai, R. Canning, A. Carr, S. Chabanier, Marie-Claude Cousinou, K. Dawson, A. de la Macorra, A. Dey, Biprateep Dey, G. Dhungana, A. C. Edge, S. Eftekharzadeh, K. Fanning, James Farr, A. Font-Ribera, J. Garcia-Bellido, Lehman Garrison, E. Gaztañaga, Satya Gontcho A Gontcho, C. Gordon, Stefany Guadalupe Medellin Gonzalez, J. Guy, Hiram K. Herrera-Alcantar, L. Jiang, S. Juneau, N. G. Karaçaylı, R. Kehoe, T. Kisner, A. Kovács, M. Landriau, Michael E. Levi, C. Magneville, P. Martini, Aaron M. Meisner, M. Mezcua, R. Miquel, P. Montero Camacho, J. Moustakas, Andrea Muñoz-Gutiérrez, Adam D. Myers, S. Nadathur, L. Napolitano, J. D. Nie, N. Palanque-Delabrouille, Z. Pan, W. J. Percival, I. Pérez-Ràfols, C. Poppett, F. Prada, César Ramírez-Pérez, C. Ravoux, D. J. Rosario, M. Schubnell, Gregory Tarlé, M. Walther, B. Weiner, S. Youles, Zhimin Zhou, H. Zou, and Siwei Zou

Subjects
Quasars, Cosmology, Observational cosmology, Astronomy, QB1-991
Abstract

A key component of the Dark Energy Spectroscopic Instrument (DESI) survey validation (SV) is a detailed visual inspection (VI) of the optical spectroscopic data to quantify key survey metrics. In this paper we present results from VI of the quasar survey using deep coadded SV spectra. We show that the majority (≈70%) of the main-survey targets are spectroscopically confirmed as quasars, with ≈16% galaxies, ≈6% stars, and ≈8% low-quality spectra lacking reliable features. A nonnegligible fraction of the quasars are misidentified by the standard spectroscopic pipeline, but we show that the majority can be recovered using post-pipeline “afterburner” quasar-identification approaches. We combine these “afterburners” with our standard pipeline to create a modified pipeline to increase the overall quasar yield. At the depth of the main DESI survey, both pipelines achieve a good-redshift purity (reliable redshifts measured within 3000 km s ^−1 ) of ≈99%; however, the modified pipeline recovers ≈94% of the visually inspected quasars, as compared to ≈86% from the standard pipeline. We demonstrate that both pipelines achieve a median redshift precision and accuracy of ≈100 km s ^−1 and ≈70 km s ^−1 , respectively. We constructed composite spectra to investigate why some quasars are missed by the standard pipeline and find that they are more host-galaxy dominated (i.e., distant analogs of “Seyfert galaxies”) and/or more dust reddened than the standard-pipeline quasars. We also show example spectra to demonstrate the overall diversity of the DESI quasar sample and provide strong-lensing candidates where two targets contribute to a single spectrum.

Published
2023
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4. Overview of the Instrumentation for the Dark Energy Spectroscopic Instrument

Author

DESI Collaboration, B. Abareshi, J. Aguilar, S. Ahlen, Shadab Alam, David M. Alexander, R. Alfarsy, L. Allen, C. Allende Prieto, O. Alves, J. Ameel, E. Armengaud, J. Asorey, Alejandro Aviles, S. Bailey, A. Balaguera-Antolínez, O. Ballester, C. Baltay, A. Bault, S. F. Beltran, B. Benavides, S. BenZvi, A. Berti, R. Besuner, Florian Beutler, D. Bianchi, C. Blake, P. Blanc, R. Blum, A. Bolton, S. Bose, D. Bramall, S. Brieden, A. Brodzeller, D. Brooks, C. Brownewell, E. Buckley-Geer, R. N. Cahn, Z. Cai, R. Canning, R. Capasso, A. Carnero Rosell, P. Carton, R. Casas, F. J. Castander, J. L. Cervantes-Cota, S. Chabanier, E. Chaussidon, C. Chuang, C. Circosta, S. Cole, A. P. Cooper, L. da Costa, M.-C. Cousinou, A. Cuceu, T. M. Davis, K. Dawson, R. de la Cruz-Noriega, A. de la Macorra, A. de Mattia, J. Della Costa, P. Demmer, M. Derwent, A. Dey, B. Dey, G. Dhungana, Z. Ding, C. Dobson, P. Doel, J. Donald-McCann, J. Donaldson, K. Douglass, Y. Duan, P. Dunlop, J. Edelstein, S. Eftekharzadeh, D. J. Eisenstein, M. Enriquez-Vargas, S. Escoffier, M. Evatt, P. Fagrelius, X. Fan, K. Fanning, V. A. Fawcett, S. Ferraro, J. Ereza, B. Flaugher, A. Font-Ribera, J. E. Forero-Romero, C. S. Frenk, S. Fromenteau, B. T. Gänsicke, C. Garcia-Quintero, L. Garrison, E. Gaztañaga, F. Gerardi, H. Gil-Marín, S. Gontcho A Gontcho, Alma X. Gonzalez-Morales, G. Gonzalez-de-Rivera, V. Gonzalez-Perez, C. Gordon, O. Graur, D. Green, C. Grove, D. Gruen, G. Gutierrez, J. Guy, C. Hahn, S. Harris, D. Herrera, Hiram K. Herrera-Alcantar, K. Honscheid, C. Howlett, D. Huterer, V. Iršič, M. Ishak, P. Jelinsky, L. Jiang, J. Jimenez, Y. P. Jing, R. Joyce, E. Jullo, S. Juneau, N. G. Karaçaylı, M. Karamanis, A. Karcher, T. Karim, R. Kehoe, S. Kent, D. Kirkby, T. Kisner, F. Kitaura, S. E. Koposov, A. Kovács, A. Kremin, Alex Krolewski, B. L’Huillier, O. Lahav, A. Lambert, C. Lamman, Ting-Wen Lan, M. Landriau, S. Lane, D. Lang, J. U. Lange, J. Lasker, L. Le Guillou, A. Leauthaud, A. Le Van Suu, Michael E. Levi, T. S. Li, C. Magneville, M. Manera, Christopher J. Manser, B. Marshall, Paul Martini, W. McCollam, P. McDonald, Aaron M. Meisner, J. Mena-Fernández, J. Meneses-Rizo, M. Mezcua, T. Miller, R. Miquel, P. Montero-Camacho, J. Moon, J. Moustakas, E. Mueller, Andrea Muñoz-Gutiérrez, Adam D. Myers, S. Nadathur, J. Najita, L. Napolitano, E. Neilsen, Jeffrey A. Newman, J. D. Nie, Y. Ning, G. Niz, P. Norberg, Hernán E. Noriega, T. O’Brien, A. Obuljen, N. Palanque-Delabrouille, A. Palmese, P. Zhiwei, D. Pappalardo, X. PENG, W. J. Percival, S. Perruchot, R. Pogge, C. Poppett, A. Porredon, F. Prada, J. Prochaska, R. Pucha, A. Pérez-Fernández, I. Pérez-Ràfols, D. Rabinowitz, A. Raichoor, S. Ramirez-Solano, César Ramírez-Pérez, C. Ravoux, K. Reil, M. Rezaie, A. Rocher, C. Rockosi, N. A. Roe, A. Roodman, A. J. Ross, G. Rossi, R. Ruggeri, V. Ruhlmann-Kleider, C. G. Sabiu, S. Gaines, K. Said, A. Saintonge, Javier Salas Catonga, L. Samushia, E. Sanchez, C. Saulder, E. Schaan, E. Schlafly, D. Schlegel, J. Schmoll, D. Scholte, M. Schubnell, A. Secroun, H. Seo, S. Serrano, Ray M. Sharples, Michael J. Sholl, Joseph Harry Silber, D. R. Silva, M. Sirk, M. Siudek, A. Smith, D. Sprayberry, R. Staten, B. Stupak, T. Tan, Gregory Tarlé, Suk Sien Tie, R. Tojeiro, L. A. Ureña-López, F. Valdes, O. Valenzuela, M. Valluri, M. Vargas-Magaña, L. Verde, M. Walther, B. Wang, M. S. Wang, B. A. Weaver, C. Weaverdyck, R. Wechsler, Michael J. Wilson, J. Yang, Y. Yu, S. Yuan, Christophe Yèche, H. Zhang, K. Zhang, Cheng Zhao, Rongpu Zhou, Zhimin Zhou, H. Zou, J. Zou, S. Zou, and Y. Zu

Subjects
Dark energy, Spectroscopy, Astronomical instrumentation, Spectrometers, Optical telescopes, Astronomy, QB1-991
Abstract

The Dark Energy Spectroscopic Instrument (DESI) embarked on an ambitious 5 yr survey in 2021 May to explore the nature of dark energy with spectroscopic measurements of 40 million galaxies and quasars. DESI will determine precise redshifts and employ the baryon acoustic oscillation method to measure distances from the nearby universe to beyond redshift z > 3.5, and employ redshift space distortions to measure the growth of structure and probe potential modifications to general relativity. We describe the significant instrumentation we developed to conduct the DESI survey. This includes: a wide-field, 3.°2 diameter prime-focus corrector; a focal plane system with 5020 fiber positioners on the 0.812 m diameter, aspheric focal surface; 10 continuous, high-efficiency fiber cable bundles that connect the focal plane to the spectrographs; and 10 identical spectrographs. Each spectrograph employs a pair of dichroics to split the light into three channels that together record the light from 360–980 nm with a spectral resolution that ranges from 2000–5000. We describe the science requirements, their connection to the technical requirements, the management of the project, and interfaces between subsystems. DESI was installed at the 4 m Mayall Telescope at Kitt Peak National Observatory and has achieved all of its performance goals. Some performance highlights include an rms positioner accuracy of better than 0.″1 and a median signal-to-noise ratio of 7 of the [O ii ] doublet at 8 × 10 ^−17 erg s ^−1 cm ^−2 in 1000 s for galaxies at z = 1.4–1.6. We conclude with additional highlights from the on-sky validation and commissioning, key successes, and lessons learned.

Published
2022
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5. The miniJPAS survey quasar selection III: Classification with artificial neural networks and hybridisation

Author

G. Martínez-Solaeche, C. Queiroz, R. M. González Delgado, N. V. N. Rodrigues, R. García-Benito, I. Pérez-Ràfols, L. Raul Abramo, L. Díaz-García, M. M. Pieri, J. Chaves-Montero, A. Hernán-Caballero, J. E. Rodríguez-Martín, S. Bonoli, S. S. Morrison, I. Márquez, J. M. Vílchez, J. A. Fernández-Ontiveros, V. Marra, J. Alcaniz, N. Benitez, A. J. Cenarro, D. Cristóbal-Hornillos, R. A. Dupke, A. Ederoclite, C. López-Sanjuan, A. Marín-Franch, C. Mendes de Oliveira, M. Moles, L. Sodré, K. Taylor, J. Varela, H. Vázquez Ramió, Laboratoire de Physique Nucléaire et de Hautes Énergies (LPNHE (UMR_7585)), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Laboratoire d'Astrophysique de Marseille (LAM), and Aix Marseille Université (AMU)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)

Subjects
Cosmology and Nongalactic Astrophysics (astro-ph.CO), Space and Planetary Science, Astrophysics of Galaxies (astro-ph.GA), FOS: Physical sciences, Astronomy and Astrophysics, [PHYS.ASTR]Physics [physics]/Astrophysics [astro-ph], Astrophysics - Astrophysics of Galaxies, Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract

This paper is part of large effort within the J-PAS collaboration that aims to classify point-like sources in miniJPAS, which were observed in 60 optical bands over ~1 deg2 in the AEGIS field. We developed two algorithms based on artificial neural networks (ANN) to classify objects into four categories: stars, galaxies, quasars at low redshift (z < 2.1), and quasars at high redshift (z ≥ 2.1). As inputs, we used miniJPAS fluxes for one of the classifiers (ANN1) and colours for the other (ANN2). The ANNs were trained and tested using mock data in the first place. We studied the effect of augmenting the training set by creating hybrid objects, which combines fluxes from stars, galaxies, and quasars. Nevertheless, the augmentation processing did not improve the score of the ANN. We also evaluated the performance of the classifiers in a small subset of the SDSS DR12Q superset observed by miniJPAS. In the mock test set, the f1-score for quasars at high redshift with the ANN1 (ANN2) are 0.99 (0.99), 0.93 (0.92), and 0.63 (0.57) for 17 < r ≤ 20, 20 < r ≤ 22.5, and 22.5 < r ≤ 23.6, respectively, where r is the J-PAS rSDSS band. In the case of low-redshift quasars, galaxies, and stars, we reached 0.97 (0.97), 0.82 (0.79), and 0.61 (0.58); 0.94 (0.94), 0.90 (0.89), and 0.81 (0.80); and 1.0 (1.0), 0.96 (0.94), and 0.70 (0.52) in the same r bins. In the SDSS DR12Q superset miniJPAS sample, the weighted f1-score reaches 0.87 (0.88) for objects that are mostly within 20 < r ≤ 22.5. We find that the most common confusion occurs between quasars at low redshift and galaxies in mocks and miniJPAS data. We discuss the origin of this confusion, and we show examples in which these objects present features that are shared by both classes. Finally, we estimate the number of point-like sources that are quasars, galaxies, and stars in miniJPAS.

Published
2023
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6. Forecasts for WEAVE-QSO: 3D clustering and connectivity of critical points with Lyman-α tomography

Author

K Kraljic, C Laigle, C Pichon, S Peirani, S Codis, J Shim, C Cadiou, D Pogosyan, S Arnouts, M Pieri, V Iršič, S S Morrison, J Oñorbe, I Pérez-Ràfols, G Dalton, Laboratoire d'Astrophysique de Marseille (LAM), Aix Marseille Université (AMU)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), Institut d'Astrophysique de Paris (IAP), Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Institut de Physique Théorique - UMR CNRS 3681 (IPHT), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Joseph Louis LAGRANGE (LAGRANGE), Université Nice Sophia Antipolis (1965 - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire de la Côte d'Azur, COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Université Côte d'Azur (UCA)-Université Côte d'Azur (UCA)-Centre National de la Recherche Scientifique (CNRS), Observatoire de la Côte d'Azur (OCA), Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), Astrophysique Interprétation Modélisation (AIM (UMR_7158 / UMR_E_9005 / UM_112)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Korea Institute for Advanced Study (KIAS), Department of Physics and Astronomy [UCL London], University College of London [London] (UCL), Department of Physics, University of Alberta, Kavli Institute for Cosmology [Cambridge] (KICC), University of Cambridge [UK] (CAM), Cavendish Laboratory, Department of Astronomy, University of Illinois, Faculty of Physics [Sevilla University] | Facultad de Física [Universidad de Sevilla], Universidad de Sevilla / University of Sevilla, Laboratoire de Physique Nucléaire et de Hautes Énergies (LPNHE (UMR_7585)), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Department of Physics [Oxford], University of Oxford, ANR-18-CE31-0009,SPHERES,Modéliser les grandes structures de l'Univers dans le régime non-linéaire(2018), and ANR-19-CE31-0023,DEEPDIP,Apprentissage profond pour les grands programmes d'imagerie(2019)

Subjects
Cosmology and Nongalactic Astrophysics (astro-ph.CO), surveys, Space and Planetary Science, Astrophysics of Galaxies (astro-ph.GA), FOS: Physical sciences, galaxies: formation, Astronomy and Astrophysics, Astrophysics::Cosmology and Extragalactic Astrophysics, galaxies: evolution, [PHYS.ASTR]Physics [physics]/Astrophysics [astro-ph], Astrophysics - Astrophysics of Galaxies, cosmology: large-scale structure of Universe, Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract

The upcoming WEAVE-QSO survey will target a high density of quasars over a large area, enabling the reconstruction of the 3D density field through Lyman-$\alpha$ tomography over unprecedented volumes smoothed on intermediate scales ($\approx$ 16 Mpc/$h$). We produce mocks of the Lyman-$\alpha$ forest using LyMAS, and reconstruct the 3D density field between sightlines through Wiener filtering in a configuration compatible with the future WEAVE-QSO observations. The fidelity of the reconstruction is assessed by measuring one- and two-point statistics from the distribution of critical points in the cosmic web. In addition, initial Lagrangian statistics are predicted from first principles, and measurements of the connectivity of the cosmic web are performed. The reconstruction captures well the expected features in the auto- and cross-correlations of the critical points. This remains true after a realistic noise is added to the synthetic spectra, even though sparsity of sightlines introduces systematics, especially in the cross-correlations of points with mixed signature. Specifically, for walls and filaments, the most striking clustering features could be measured with up to 4 sigma of significance with a WEAVE-QSO-like survey. Moreover, the connectivity of each peak identified in the reconstructed field is globally consistent with its counterpart in the original field, indicating that the reconstruction preserves the geometry of the density field not only statistically, but also locally. Hence the critical points relative positions within the tomographic reconstruction could be used as standard rulers for dark energy by WEAVE-QSO and similar surveys., Comment: 26 pages, 22 figures, submitted to MNRAS

Published
2022
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