Final Planck CMB data confirms the flat 6-parameter ΛCDM model with Ω_c h² = 0.120 ± 0.001, Ω_b h² = 0.0224 ± 0.0001, n_s = 0.965 ± 0.004, τ = 0.054 ± 0.007, H_0 = 67.4 ± 0.5 km/s/Mpc, and no strong evidence for extensions.
The SDSS-IV extended Baryon Oscillation Spectroscopic Survey: Baryon Acoustic Oscillations at redshift of 0.72 with the DR14 Luminous Red Galaxy Sample
2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
abstract
The extended Baryon Oscillation Spectroscopic Survey (eBOSS) Data Release 14 sample includes 80,118 Luminous Red Galaxies. By combining these galaxies with the high-redshift tail of the BOSS galaxy sample, we form a sample of LRGs at an effective redshift $z=0.72$, covering an effective volume of 0.9~Gpc$^3$. We introduce new techniques to account for spurious fluctuations caused by targeting and by redshift failures which were validated on a set of mock catalogs. This analysis is sufficient to provide a $2.6$\% measurement of spherically averaged BAO, $D_V(z=0.72) = 2353^{+63}_{-61} (r_d/r_{d,\rm{fid}}) h^{-1}$Mpc, at 2.8$\sigma$ of significance. Together with the recent quasar-based BAO measurement at $z=1.5$, and forthcoming Emission Line Galaxy-based measurements, this measurement demonstrates that eBOSS is fulfilling its remit of extending the range of redshifts covered by such measurements, laying the ground work for forthcoming surveys such as the Dark Energy Spectroscopic Survey and Euclid.
fields
astro-ph.CO 2representative citing papers
Property-dependent systematic weights derived separately on ELG subsamples, with separate DES footprint treatment, mitigate spurious clustering in ~10% of subsamples but are not optimal for the full sample.
citing papers explorer
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Planck 2018 results. VI. Cosmological parameters
Final Planck CMB data confirms the flat 6-parameter ΛCDM model with Ω_c h² = 0.120 ± 0.001, Ω_b h² = 0.0224 ± 0.0001, n_s = 0.965 ± 0.004, τ = 0.054 ± 0.007, H_0 = 67.4 ± 0.5 km/s/Mpc, and no strong evidence for extensions.
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DESI Data Release 2 ELGs: Property-dependent subsamples, imaging systematics, and clustering
Property-dependent systematic weights derived separately on ELG subsamples, with separate DES footprint treatment, mitigate spurious clustering in ~10% of subsamples but are not optimal for the full sample.