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Title: Optimized clustering estimators for BAO measurements accounting for significant redshift uncertainty

Here, we determine an optimized clustering statistic to be used for galaxy samples with significant redshift uncertainty, such as those that rely on photometric redshifts. To do so, we study the baryon acoustic oscillation (BAO) information content as a function of the orientation of galaxy clustering modes with respect to their angle to the line-of-sight (LOS). The clustering along the LOS, as observed in a redshift-space with significant redshift uncertainty, has contributions from clustering modes with a range of orientations with respect to the true LOS. For redshift uncertainty $$\sigma_z \geq 0.02(1+z)$$ we find that while the BAO information is confined to transverse clustering modes in the true space, it is spread nearly evenly in the observed space. Thus, measuring clustering in terms of the projected separation (regardless of the LOS) is an efficient and nearly lossless compression of the signal for $$\sigma_z \geq 0.02(1+z)$$. For reduced redshift uncertainty, a more careful consideration is required. We then use more than 1700 realizations (combining two separate sets) of galaxy simulations mimicking the Dark Energy Survey Year 1 sample to validate our analytic results and optimized analysis procedure. We find that using the correlation function binned in projected separation, we can achieve uncertainties that are within 10 per cent of those predicted by Fisher matrix forecasts. We predict that DES Y1 should achieve a 5 per cent distance measurement using our optimized methods. We expect the results presented here to be important for any future BAO measurements made using photometric redshift data.
Authors:
ORCiD logo [1] ;  [2] ;  [3] ;  [4] ;  [5] ;  [6] ;  [7] ;  [8] ;  [9] ;  [10] ;  [11]
  1. The Ohio State Univ., Columbus, OH (United States); Univ. of Portsmouth, Portsmouth (United Kingdom)
  2. Univ. of Florida, Gainesville, FL (United States); Fermi National Accelerator Lab. (FNAL), Batavia, IL (United States)
  3. Univ. of Portsmouth, Portsmouth (United Kingdom); Univ. Autonoma de Madrid, Madrid (Spain)
  4. Univ. of Portsmouth, Portsmouth (United Kingdom)
  5. Fermi National Accelerator Lab. (FNAL), Batavia, IL (United States)
  6. Univ. Autonoma de Madrid, Madrid (Spain)
  7. Institut de Ciencies de l'Espai, Barcelona (Spain)
  8. Univ. of Manchester, Manchester (United Kingdom)
  9. Ludwig-Maximilians-Univ. Munchen, Munchen (Germany); Univ. of Cambridge, Cambridge (United Kingdom)
  10. Univ. of Cambridge, Cambridge (United Kingdom); Centre for Theoretical Cosmology, Cambridge (United Kingdom)
  11. Centro de Investigaciones Energeticas, Medioambientales y Tecnologicas (CIEMAT), Madrid (Spain)
Publication Date:
Report Number(s):
FERMILAB-PUB-17-162-A-AE; IFT-UAM-CSIC-17-044; arXiv:1705.05442
Journal ID: ISSN 0035-8711; 1599798
Grant/Contract Number:
AC02-07CH11359
Type:
Accepted Manuscript
Journal Name:
Monthly Notices of the Royal Astronomical Society
Additional Journal Information:
Journal Volume: 472; Journal Issue: 4; Journal ID: ISSN 0035-8711
Publisher:
Royal Astronomical Society
Research Org:
Fermi National Accelerator Lab. (FNAL), Batavia, IL (United States)
Sponsoring Org:
USDOE Office of Science (SC), High Energy Physics (HEP) (SC-25)
Country of Publication:
United States
Language:
English
Subject:
79 ASTRONOMY AND ASTROPHYSICS; distance scale; large-scale structure of Universe
OSTI Identifier:
1367905

Ross, Ashley Jacob, Banik, Nilanjan, Avila, Santiago, Percival, Will J., Dodelson, Scott, Garcia-Bellido, Juan, Crocce, Martin, Elvin-Poole, Jack, Giannantonio, Tommaso, Manera, Marc, and Sevilla-Noarbe, Ignacio. Optimized clustering estimators for BAO measurements accounting for significant redshift uncertainty. United States: N. p., Web. doi:10.1093/mnras/stx2120.
Ross, Ashley Jacob, Banik, Nilanjan, Avila, Santiago, Percival, Will J., Dodelson, Scott, Garcia-Bellido, Juan, Crocce, Martin, Elvin-Poole, Jack, Giannantonio, Tommaso, Manera, Marc, & Sevilla-Noarbe, Ignacio. Optimized clustering estimators for BAO measurements accounting for significant redshift uncertainty. United States. doi:10.1093/mnras/stx2120.
Ross, Ashley Jacob, Banik, Nilanjan, Avila, Santiago, Percival, Will J., Dodelson, Scott, Garcia-Bellido, Juan, Crocce, Martin, Elvin-Poole, Jack, Giannantonio, Tommaso, Manera, Marc, and Sevilla-Noarbe, Ignacio. 2017. "Optimized clustering estimators for BAO measurements accounting for significant redshift uncertainty". United States. doi:10.1093/mnras/stx2120. https://www.osti.gov/servlets/purl/1367905.
@article{osti_1367905,
title = {Optimized clustering estimators for BAO measurements accounting for significant redshift uncertainty},
author = {Ross, Ashley Jacob and Banik, Nilanjan and Avila, Santiago and Percival, Will J. and Dodelson, Scott and Garcia-Bellido, Juan and Crocce, Martin and Elvin-Poole, Jack and Giannantonio, Tommaso and Manera, Marc and Sevilla-Noarbe, Ignacio},
abstractNote = {Here, we determine an optimized clustering statistic to be used for galaxy samples with significant redshift uncertainty, such as those that rely on photometric redshifts. To do so, we study the baryon acoustic oscillation (BAO) information content as a function of the orientation of galaxy clustering modes with respect to their angle to the line-of-sight (LOS). The clustering along the LOS, as observed in a redshift-space with significant redshift uncertainty, has contributions from clustering modes with a range of orientations with respect to the true LOS. For redshift uncertainty $\sigma_z \geq 0.02(1+z)$ we find that while the BAO information is confined to transverse clustering modes in the true space, it is spread nearly evenly in the observed space. Thus, measuring clustering in terms of the projected separation (regardless of the LOS) is an efficient and nearly lossless compression of the signal for $\sigma_z \geq 0.02(1+z)$. For reduced redshift uncertainty, a more careful consideration is required. We then use more than 1700 realizations (combining two separate sets) of galaxy simulations mimicking the Dark Energy Survey Year 1 sample to validate our analytic results and optimized analysis procedure. We find that using the correlation function binned in projected separation, we can achieve uncertainties that are within 10 per cent of those predicted by Fisher matrix forecasts. We predict that DES Y1 should achieve a 5 per cent distance measurement using our optimized methods. We expect the results presented here to be important for any future BAO measurements made using photometric redshift data.},
doi = {10.1093/mnras/stx2120},
journal = {Monthly Notices of the Royal Astronomical Society},
number = 4,
volume = 472,
place = {United States},
year = {2017},
month = {8}
}