分类： 天文学 >> 天文学 提交时间： 2023-02-19
Cheng Zhao
Chia-Hsun Chuang
Julian Bautista
Arnaud de Mattia
Anand Raichoor
Ashley J. Ross
Jiamin Hou
Richard Neveux
Charling Tao
Etienne Burtin
Kyle S. Dawson
Sylvain de la Torre
Héctor Gil-Marín
Jean-Paul Kneib
Will J. Percival
Graziano Rossi
Amélie Tamone
Jeremy L. Tinker
Gong-Bo Zhao
Shadab Alam
摘要： We produce 1000 realizations of synthetic clustering catalogues for each type of the tracers used for the baryon acoustic oscillation and redshift space distortion analysis of the Sloan Digital Sky Surveys-IV extended Baryon Oscillation Spectroscopic Survey final data release (eBOSS DR16), covering the redshift range from 0.6 to 2.2, to provide reliable estimates of covariance matrices and test the robustness of the analysis pipeline with respect to observational systematics. By extending the Zel'dovich approximation density field with an effective tracer bias model calibrated with the clustering measurements from the observational data, we accurately reproduce the two- and three-point clustering statistics of the eBOSS DR16 tracers, including their cross-correlations in redshift space with very low computational costs. In addition, we include the gravitational evolution of structures and sample selection biases at different redshifts, as well as various photometric and spectroscopic systematic effects. The agreements on the auto-clustering statistics between the data and mocks are generally within 1 $\sigma$ variances inferred from the mocks, for scales down to a few $h^{-1}\,{\rm Mpc}$ in configuration space, and up to $0.3\,h\,{\rm Mpc}^{-1}$ in Fourier space. For the cross correlations between different tracers, the same level of consistency presents in configuration space, while there are only discrepancies in Fourier space for scales above $0.15\,h\,{\rm Mpc}^{-1}$. The accurate reproduction of the data clustering statistics permits reliable covariances for multi-tracer analysis.
分类： 天文学 >> 天文学 提交时间： 2023-02-19
Cheng Zhao
Andrei Variu
Mengfan He
Daniel Forero Sanchez
Amélie Tamone
Chia-Hsun Chuang
Francisco-Shu Kitaura
Charling Tao
Jiaxi Yu
Jean-Paul Kneib
Will J. Percival
Huanyuan Shan
Gong-Bo Zhao
Etienne Burtin
Kyle S. Dawson
Graziano Rossi
Donald P. Schneider
Axel de la Macorra
摘要： We construct cosmic void catalogues with the DIVE void finder upon SDSS BOSS DR12 and eBOSS DR16 galaxy samples with BAO reconstruction applied, and perform a joint BAO analysis using different types of galaxies and the corresponding voids. The BAO peak is evident for the galaxy-galaxy, galaxy-void, and void-void correlation functions of all datasets, including the ones cross correlating luminous red galaxy and emission line galaxy samples. Two multi-tracer BAO fitting schemes are then tested, one combining the galaxy and void correlation functions with a weight applied to voids, and the other using a single BAO dilation parameter for all clustering measurements of different tracers. Both methods produce consistent results with mock catalogues, and on average ~10 per cent improvements of the BAO statistical uncertainties are observed for all samples, compared to the results from galaxies alone. By combining the clustering of galaxies and voids, the uncertainties of BAO measurements from the SDSS data are reduced by 5 to 15 per cent, yielding 0.9, 0.8, 1.1, 2.3, and 2.9 per cent constraints on the distance $D_{_{\rm V}}(z)$, at effective redshifts of 0.38, 0.51, 0.70, 0.77, and 0.85, respectively. When combined with BAO measurements from SDSS MGS, QSO, and Ly$\alpha$ samples, as well as the BBN results, we obtain $H_0 = 67.58 \pm 0.91\,{\rm km}\,{\rm s}^{-1}\,{\rm Mpc}^{-1}$, $\Omega_{\rm m} = 0.290 \pm 0.015$, and $\Omega_\Lambda h^2 = 0.3241 \pm 0.0079$ in the flat-$\Lambda$CDM framework, where the 1$\,\sigma$ uncertainties are around 6, 6, and 17 per cent smaller respectively, compared to constraints from the corresponding anisotropic BAO measurements without voids and LRG-ELG cross correlations.
分类： 天文学 >> 天文学 提交时间： 2023-02-19
Andrei Variu
Cheng Zhao
Daniel Forero-Sánchez
Chia-Hsun Chuang
Francisco-Shu Kitaura
Charling Tao
Amélie Tamone
Jean-Paul Kneib
摘要： Baryonic Acoustic Oscillations (BAOs) studies based on the clustering of voids and matter tracers provide important constraints on cosmological parameters related to the expansion of the Universe. However, modelling the void exclusion effect is an important challenge for fully exploiting the potential of these kind of analyses. We thus develop two numerical methods to describe the clustering of cosmic voids. Neither model requires additional cosmological information beyond that assumed within the galaxy de-wiggled model. The models consist in power spectra whose performance we assess in comparison to a parabolic model on both Patchy boxes and light-cones. Moreover, we test their robustness against systematic effects and the reconstruction technique. The void model power spectra and the parabolic model with a fixed parameter provide strongly correlated values for the Alcock-Paczynski ($\alpha$) parameter, for boxes and light-cones likewise. The resulting $\alpha$ values - for all three models - are unbiased and their uncertainties are correctly estimated. However, the numerical models show less variation with the fitting range compared to the parabolic one. The Bayesian evidence suggests that the numerical techniques are often favoured compared to the parabolic model. Moreover, the void model power spectra computed on boxes can describe the void clustering from light-cones as well as from boxes. The same void model power spectra can be used for the study of pre- and post-reconstructed data-sets. Lastly, the two numerical techniques are resilient against the studied systematic effects. Consequently, using either of the two new void models, one can more robustly measure cosmological parameters.
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