Salvato in:
| Autori principali: | , , , , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| Soggetti: | |
| Accesso online: | https://arxiv.org/abs/2510.02449 |
| Tags: |
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Sommario:
- The 4-metre Multi-Object Spectroscopic Telescope Cosmology Redshift Survey (4MOST CRS) will obtain 5.4 million spectroscopic redshifts over ~5700 deg^2 to map large-scale structure and enable measurements of baryon acoustic oscillations, growth rates via redshift-space distortions, and cross-correlations with weak-lensing surveys. We validate the target selections, photometry, masking, systematics, and redshift distributions of the bright galaxy (BG) and luminous red galaxy (LRG) target catalogues selected from the Dark Energy Spectroscopic Instrument (DESI) Legacy Survey DR10.1 (LS) imaging. We measure the angular two-point correlation function, $w(θ)$, test masking strategies, and recover redshift distributions via cross-correlation with DESI DR1 spectroscopy. For BGs, we adopt LS MASKBITS that veto bright stars and extended sources; for LRGs, we pair these with unblurred coadds of the WISE imaging (unWISE) W1 artefact masks. These choices suppress small-scale excess power without imprinting large-scale modes. A Limber-scaling test across BG $r$-band magnitude slices shows that, after applying the scaling, the $w(θ)$ curves collapse to a near-common power law, demonstrating photometric uniformity with depth and consistency between the North and South Galactic Caps. Cross-correlations with DESI spectroscopy recover the expected N(z), albeit with high shot noise at the brightest magnitudes. For LRGs, angular clustering in photo-$z$ slices ($0.4\le z<1.0$) is consistent between the Dark Energy Camera Legacy Survey (DECaLS) and Dark Energy Survey (DES) footprints and is well described by an approximate power law once photo-$z$ smearing is included; halo-occupation fits are consistent with recent LRG studies. Together, these tests indicate that the masks and target selections yield reliable clustering statistics, supporting precision large-scale structure analyses with 4MOST CRS.