ELG Spectroscopic Systematics Analysis of the DESI Data Release 1
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arXiv
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| Format: | Preprint |
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2024
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| author | Yu, Jiaxi Ross, Ashley J. Rocher, Antoine Alves, Otávio de Mattia, Arnaud Forero-Sánchez, Daniel Kneib, Jean-Paul Krolewski, Alex Lan, TingWen Rashkovetskyi, Michael Aguilar, Jessica Nicole Ahlen, Steven Bailey, Stephen Brooks, David Chaussidon, Edmond Claybaugh, Todd de la Macorra, Axel Dey, Arjun Dey, Biprateep Doel, Peter Fanning, Kevin Forero-Romero, Jaime E. Gaztañaga, Enrique Gontcho, Satya Gontcho A Honscheid, Klaus Howlett, Cullan Juneau, Stephanie Kisner, Theodore Kremin, Anthony Lambert, Andrew Landriau, Martin Guillou, Laurent Le Levi, Michael E. Manera, Marc Martini, Paul Meisner, Aaron Miquel, Ramon Moustakas, John Mueller, Eva-Maria Muñoz-Gutiérrez, Andrea Myers, Adam D. Nie, Jundan Niz, Gustavo Palanque-Delabrouille, Nathalie Percival, Will J. Poppett, Claire Prada, Francisco Rezaie, Mehdi Rossi, Graziano Sanchez, Eusebio Schlafly, Edward F. Schlegel, David Schubnell, Michael Seo, Hee-Jong Sprayberry, David Tarlé, Gregory Weaver, Benjamin A. Zarrouk, Pauline Zhao, Cheng Zhou, Rongpu Zou, Hu |
| author_facet | Yu, Jiaxi Ross, Ashley J. Rocher, Antoine Alves, Otávio de Mattia, Arnaud Forero-Sánchez, Daniel Kneib, Jean-Paul Krolewski, Alex Lan, TingWen Rashkovetskyi, Michael Aguilar, Jessica Nicole Ahlen, Steven Bailey, Stephen Brooks, David Chaussidon, Edmond Claybaugh, Todd de la Macorra, Axel Dey, Arjun Dey, Biprateep Doel, Peter Fanning, Kevin Forero-Romero, Jaime E. Gaztañaga, Enrique Gontcho, Satya Gontcho A Honscheid, Klaus Howlett, Cullan Juneau, Stephanie Kisner, Theodore Kremin, Anthony Lambert, Andrew Landriau, Martin Guillou, Laurent Le Levi, Michael E. Manera, Marc Martini, Paul Meisner, Aaron Miquel, Ramon Moustakas, John Mueller, Eva-Maria Muñoz-Gutiérrez, Andrea Myers, Adam D. Nie, Jundan Niz, Gustavo Palanque-Delabrouille, Nathalie Percival, Will J. Poppett, Claire Prada, Francisco Rezaie, Mehdi Rossi, Graziano Sanchez, Eusebio Schlafly, Edward F. Schlegel, David Schubnell, Michael Seo, Hee-Jong Sprayberry, David Tarlé, Gregory Weaver, Benjamin A. Zarrouk, Pauline Zhao, Cheng Zhou, Rongpu Zou, Hu |
| contents | Dark Energy Spectroscopic Instrument (DESI) uses more than 2.4 million Emission Line Galaxies (ELGs) for 3D large-scale structure (LSS) analyses in its Data Release 1 (DR1). Such large statistics enable thorough research on systematic uncertainties. In this study, we focus on spectroscopic systematics of ELGs. The redshift success rate ($f_{\rm goodz}$) is the relative fraction of secure redshifts among all measurements. It depends on observing conditions, thus introduces non-cosmological variations to the LSS. We, therefore, develop the redshift failure weight ($w_{\rm zfail}$) and a per-fibre correction ($η_{\rm zfail}$) to mitigate these dependences. They have minor influences on the galaxy clustering. For ELGs with a secure redshift, there are two subtypes of systematics: 1) catastrophics (large) that only occur in a few samples; 2) redshift uncertainty (small) that exists for all samples. The catastrophics represent 0.26\% of the total DR1 ELGs, composed of the confusion between O\,\textsc{ii} and sky residuals, double objects, total catastrophics and others. We simulate the realistic 0.26\% catastrophics of DR1 ELGs, the hypothetical 1\% catastrophics, and the truncation of the contaminated $1.31<z<1.33$ in the \textsc{AbacusSummit} ELG mocks. Their $P_\ell$ show non-negligible bias from the uncontaminated mocks. But their influences on the redshift space distortions (RSD) parameters are smaller than $0.2σ$. The redshift uncertainty of \Yone ELGs is 8.5 km/s with a Lorentzian profile. The code for implementing the catastrophics and redshift uncertainty on mocks can be found in https://github.com/Jiaxi-Yu/modelling_spectro_sys. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2405_16657 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | ELG Spectroscopic Systematics Analysis of the DESI Data Release 1 Yu, Jiaxi Ross, Ashley J. Rocher, Antoine Alves, Otávio de Mattia, Arnaud Forero-Sánchez, Daniel Kneib, Jean-Paul Krolewski, Alex Lan, TingWen Rashkovetskyi, Michael Aguilar, Jessica Nicole Ahlen, Steven Bailey, Stephen Brooks, David Chaussidon, Edmond Claybaugh, Todd de la Macorra, Axel Dey, Arjun Dey, Biprateep Doel, Peter Fanning, Kevin Forero-Romero, Jaime E. Gaztañaga, Enrique Gontcho, Satya Gontcho A Honscheid, Klaus Howlett, Cullan Juneau, Stephanie Kisner, Theodore Kremin, Anthony Lambert, Andrew Landriau, Martin Guillou, Laurent Le Levi, Michael E. Manera, Marc Martini, Paul Meisner, Aaron Miquel, Ramon Moustakas, John Mueller, Eva-Maria Muñoz-Gutiérrez, Andrea Myers, Adam D. Nie, Jundan Niz, Gustavo Palanque-Delabrouille, Nathalie Percival, Will J. Poppett, Claire Prada, Francisco Rezaie, Mehdi Rossi, Graziano Sanchez, Eusebio Schlafly, Edward F. Schlegel, David Schubnell, Michael Seo, Hee-Jong Sprayberry, David Tarlé, Gregory Weaver, Benjamin A. Zarrouk, Pauline Zhao, Cheng Zhou, Rongpu Zou, Hu Cosmology and Nongalactic Astrophysics Dark Energy Spectroscopic Instrument (DESI) uses more than 2.4 million Emission Line Galaxies (ELGs) for 3D large-scale structure (LSS) analyses in its Data Release 1 (DR1). Such large statistics enable thorough research on systematic uncertainties. In this study, we focus on spectroscopic systematics of ELGs. The redshift success rate ($f_{\rm goodz}$) is the relative fraction of secure redshifts among all measurements. It depends on observing conditions, thus introduces non-cosmological variations to the LSS. We, therefore, develop the redshift failure weight ($w_{\rm zfail}$) and a per-fibre correction ($η_{\rm zfail}$) to mitigate these dependences. They have minor influences on the galaxy clustering. For ELGs with a secure redshift, there are two subtypes of systematics: 1) catastrophics (large) that only occur in a few samples; 2) redshift uncertainty (small) that exists for all samples. The catastrophics represent 0.26\% of the total DR1 ELGs, composed of the confusion between O\,\textsc{ii} and sky residuals, double objects, total catastrophics and others. We simulate the realistic 0.26\% catastrophics of DR1 ELGs, the hypothetical 1\% catastrophics, and the truncation of the contaminated $1.31<z<1.33$ in the \textsc{AbacusSummit} ELG mocks. Their $P_\ell$ show non-negligible bias from the uncontaminated mocks. But their influences on the redshift space distortions (RSD) parameters are smaller than $0.2σ$. The redshift uncertainty of \Yone ELGs is 8.5 km/s with a Lorentzian profile. The code for implementing the catastrophics and redshift uncertainty on mocks can be found in https://github.com/Jiaxi-Yu/modelling_spectro_sys. |
| title | ELG Spectroscopic Systematics Analysis of the DESI Data Release 1 |
| topic | Cosmology and Nongalactic Astrophysics |
| url | https://arxiv.org/abs/2405.16657 |