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Impact and mitigation of spectroscopic systematics on DESI DR1 clustering measurements

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arxiv 2405.17208 v2 pith:S5BHSYDF submitted 2024-05-27 astro-ph.CO

Impact and mitigation of spectroscopic systematics on DESI DR1 clustering measurements

classification astro-ph.CO
keywords desiredshiftfluctuationsgalaxyratesuccessdensitygalaxies
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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The large scale structure catalogs within DESI Data Release 1 (DR1) use nearly 6 million galaxies and quasars as tracers of the large-scale structure of the universe to measure the expansion history with baryon acoustic oscillations and the growth of structure with redshift-space distortions. In order to take advantage of DESI's unprecedented statistical power, we must ensure that the galaxy clustering measurements are unaffected by non-cosmological density fluctuations. One source of spurious fluctuations comes from variation in galaxy density with spectroscopic observing conditions, lowering the redshift efficiency (and thus galaxy density) in certain areas of the sky. We measure the uniformity of the redshift success rate for DESI luminous red galaxies (LRG), bright galaxies (BGS) and quasars (QSO), complementing the detailed discussion of emission line galaxy (ELG) systematics in a companion paper (Yu et al., 2024). We find small but significant fluctuations of up to 3% in redshift success rate with the effective spectroscopic signal-to-noise, and create and describe weights that remove these fluctuations. We also describe the process to identify and remove data from certain poorly performing fibers from DESI DR1, and measure the stability of the redshift success rate with time. Finally, we find small but significant correlations of redshift success rate with position on the focal plane, survey speed, and number of exposures required, and show the impact of weights correcting these trends on the power spectrum multipoles and on cosmological parameters from BAO and RSD fits. These corrections change the best-fit parameters by $<15\%$ of their statistical errors, and thus contribute negligibly to the overall DESI error budget.

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Cited by 9 Pith papers

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