4.7 Article

Measuring baryon acoustic oscillations from the clustering of voids

期刊

出版社

OXFORD UNIV PRESS
DOI: 10.1093/mnras/stw884

关键词

methods: observational; galaxies: statistics; cosmology: observations; large-scale structure of Universe

资金

  1. Tsinghua University
  2. 985 grant
  3. 973 programme [2013CB834906]
  4. NSFC [11033003, 11173017]
  5. Sino French CNRS-CAS international laboratories LIA Origins and FCPPL
  6. Alfred P. Sloan Foundation
  7. National Science Foundation
  8. US Department of Energy Office of Science
  9. University of Arizona
  10. Brazilian Participation Group
  11. Brookhaven National Laboratory
  12. Carnegie Mellon University
  13. University of Florida
  14. French Participation Group
  15. German Participation Group
  16. Harvard University
  17. Instituto de Astrofisica de Canarias
  18. Michigan State/Notre Dame/JINA Participation Group
  19. Johns Hopkins University
  20. Lawrence Berkeley National Laboratory
  21. Max Planck Institute for Astrophysics
  22. Max Planck Institute for Extraterrestrial Physics
  23. New Mexico State University
  24. New York University
  25. Ohio State University
  26. Pennsylvania State University
  27. University of Portsmouth
  28. Princeton University
  29. Spanish Participation Group
  30. University of Tokyo
  31. University of Utah
  32. Vanderbilt University
  33. University of Virginia
  34. University of Washington
  35. Yale University

向作者/读者索取更多资源

We investigate the necessary methodology to optimally measure the baryon acoustic oscillation (BAO) signal from voids, based on galaxy redshift catalogues. To this end, we study the dependence of the BAO signal on the population of voids classified by their sizes. We find for the first time the characteristic features of the correlation function of voids including the first robust detection of BAOs in mock galaxy catalogues. These show an anti-correlation around the scale corresponding to the smallest size of voids in the sample (the void exclusion effect), and dips at both sides of the BAO peak, which can be used to determine the significance of the BAO signal without any priori model. Furthermore, our analysis demonstrates that there is a scale-dependent bias for different populations of voids depending on the radius, with the peculiar property that the void population with the largest BAO significance corresponds to tracers with approximately zero bias on the largest scales. We further investigate the methodology on an additional set of 1000 realistic mock galaxy catalogues reproducing the SDSS-III/BOSS CMASS DR11 data, to control the impact of sky mask and radial selection function. Our solution is based on generating voids from randoms including the same survey geometry and completeness, and a post-processing cleaning procedure in the holes and at the boundaries of the survey. The methodology and optimal selection of void populations validated in this work have been used to perform the first BAO detection from voids in observations, presented in a companion paper.

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