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Title: Optimizing Galaxy Samples for Clustering Measurements in Photometric Surveys

Abstract

When analyzing galaxy clustering in multi-band imaging surveys, there is a trade-off between selecting the largest galaxy samples (to minimize the shot noise) and selecting samples with the best photometric redshift (photo-z) precision, which generally include only a small subset of galaxies. In this paper, we systematically explore this trade-off. Our analysis is targeted towards the third year data of the Dark Energy Survey (DES), but our methods hold generally for other data sets. Using a simple Gaussian model for the redshift uncertainties, we carry out a Fisher matrix forecast for cosmological constraints from angular clustering in the redshift range $z = 0.2-0.95$. We quantify the cosmological constraints using a Figure of Merit (FoM) that measures the combined constraints on $$\Omega_m$$ and $$\sigma_8$$ in the context of $$\Lambda$$CDM cosmology. We find that the trade-off between sample size and photo-z precision is sensitive to 1) whether cross-correlations between redshift bins are included or not, and 2) the ratio of the redshift bin width $$\delta z$$ and the photo-z precision $$\sigma_z$$. When cross-correlations are included and the redshift bin width is allowed to vary, the highest FoM is achieved when $$\delta z \sim \sigma_z$$. We find that for the typical case of $5-10$ redshift bins, optimal results are reached when we use larger, less precise photo-z samples, provided that we include cross-correlations. For samples with higher $$\sigma_{z}$$, the overlap between redshift bins is larger, leading to higher cross-correlation amplitudes. This leads to the self-calibration of the photo-z parameters and therefore tighter cosmological constraints. These results can be used to help guide galaxy sample selection for clustering analysis in ongoing and future photometric surveys.

Authors:
ORCiD logo [1];  [2];  [3]
  1. Chicago U., Astron. Astrophys. Ctr.
  2. Chicago U., KICP
  3. Fermilab
Publication Date:
Research Org.:
Fermi National Accelerator Lab. (FNAL), Batavia, IL (United States)
Sponsoring Org.:
USDOE Office of Science (SC), High Energy Physics (HEP) (SC-25)
OSTI Identifier:
1569241
Report Number(s):
arXiv:1908.07150; FERMILAB-PUB-19-486-A
oai:inspirehep.net:1750379
DOE Contract Number:  
AC02-07CH11359
Resource Type:
Journal Article
Journal Name:
TBD
Additional Journal Information:
Journal Name: TBD
Country of Publication:
United States
Language:
English
Subject:
79 ASTRONOMY AND ASTROPHYSICS

Citation Formats

Tanoglidis, Dimitrios, Chang, Chihway, and Frieman, Joshua. Optimizing Galaxy Samples for Clustering Measurements in Photometric Surveys. United States: N. p., 2019. Web.
Tanoglidis, Dimitrios, Chang, Chihway, & Frieman, Joshua. Optimizing Galaxy Samples for Clustering Measurements in Photometric Surveys. United States.
Tanoglidis, Dimitrios, Chang, Chihway, and Frieman, Joshua. Mon . "Optimizing Galaxy Samples for Clustering Measurements in Photometric Surveys". United States. https://www.osti.gov/servlets/purl/1569241.
@article{osti_1569241,
title = {Optimizing Galaxy Samples for Clustering Measurements in Photometric Surveys},
author = {Tanoglidis, Dimitrios and Chang, Chihway and Frieman, Joshua},
abstractNote = {When analyzing galaxy clustering in multi-band imaging surveys, there is a trade-off between selecting the largest galaxy samples (to minimize the shot noise) and selecting samples with the best photometric redshift (photo-z) precision, which generally include only a small subset of galaxies. In this paper, we systematically explore this trade-off. Our analysis is targeted towards the third year data of the Dark Energy Survey (DES), but our methods hold generally for other data sets. Using a simple Gaussian model for the redshift uncertainties, we carry out a Fisher matrix forecast for cosmological constraints from angular clustering in the redshift range $z = 0.2-0.95$. We quantify the cosmological constraints using a Figure of Merit (FoM) that measures the combined constraints on $\Omega_m$ and $\sigma_8$ in the context of $\Lambda$CDM cosmology. We find that the trade-off between sample size and photo-z precision is sensitive to 1) whether cross-correlations between redshift bins are included or not, and 2) the ratio of the redshift bin width $\delta z$ and the photo-z precision $\sigma_z$. When cross-correlations are included and the redshift bin width is allowed to vary, the highest FoM is achieved when $\delta z \sim \sigma_z$. We find that for the typical case of $5-10$ redshift bins, optimal results are reached when we use larger, less precise photo-z samples, provided that we include cross-correlations. For samples with higher $\sigma_{z}$, the overlap between redshift bins is larger, leading to higher cross-correlation amplitudes. This leads to the self-calibration of the photo-z parameters and therefore tighter cosmological constraints. These results can be used to help guide galaxy sample selection for clustering analysis in ongoing and future photometric surveys.},
doi = {},
journal = {TBD},
number = ,
volume = ,
place = {United States},
year = {2019},
month = {8}
}