Optimizing Galaxy Samples for Clustering Measurements in Photometric Surveys
Abstract
When analyzing galaxy clustering in multiband imaging surveys, there is a tradeoff between selecting the largest galaxy samples (to minimize the shot noise) and selecting samples with the best photometric redshift (photoz) precision, which generally include only a small subset of galaxies. In this paper, we systematically explore this tradeoff. 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 $z = 0.20.95$. 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 tradeoff between sample size and photoz precision is sensitive to 1) whether crosscorrelations between redshift bins are included or not, and 2) the ratio of the redshift bin width $$\delta z$$ and the photoz precision $$\sigma_z$$. When crosscorrelations 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 $510$ redshift bins, optimal results are reached when we use larger, less precise photoz samples, provided that we include crosscorrelations. For samples with higher $$\sigma_{z}$$, the overlap between redshift bins is larger, leading to higher crosscorrelation amplitudes. This leads to the selfcalibration of the photoz 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:

 Chicago U., Astron. Astrophys. Ctr.
 Chicago U., KICP
 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) (SC25)
 OSTI Identifier:
 1569241
 Report Number(s):
 arXiv:1908.07150; FERMILABPUB19486A
oai:inspirehep.net:1750379
 DOE Contract Number:
 AC0207CH11359
 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 multiband imaging surveys, there is a tradeoff between selecting the largest galaxy samples (to minimize the shot noise) and selecting samples with the best photometric redshift (photoz) precision, which generally include only a small subset of galaxies. In this paper, we systematically explore this tradeoff. 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 $z = 0.20.95$. 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 tradeoff between sample size and photoz precision is sensitive to 1) whether crosscorrelations between redshift bins are included or not, and 2) the ratio of the redshift bin width $\delta z$ and the photoz precision $\sigma_z$. When crosscorrelations 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 $510$ redshift bins, optimal results are reached when we use larger, less precise photoz samples, provided that we include crosscorrelations. For samples with higher $\sigma_{z}$, the overlap between redshift bins is larger, leading to higher crosscorrelation amplitudes. This leads to the selfcalibration of the photoz 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}
}