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Title: Optimizing galaxy samples for clustering measurements in photometric surveys

Abstract

When analysing galaxy clustering in multiband 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 includes 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 $Ωm$ and $$σ_8$$ in the context of Λ cold dark matter ($Λ$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 $δz$ to the photo-$z$ precision $$σ_z$$. When cross-correlations are included and the redshift bin width is allowed to vary, the highest FoM is achieved when $δz$ ~ $$σ_z$$. 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 $$σ_z$$, 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]; ORCiD logo [1];  [2]
  1. Univ. of Chicago, IL (United States). Kavli Inst. for Cosmological Physics
  2. Univ. of Chicago, IL (United States). Kavli Inst. for Cosmological Physics; Fermi National Accelerator Lab. (FNAL), Batavia, IL (United States). Accelerator Physics Center
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
Journal ID: ISSN 0035-8711; oai:inspirehep.net:1750379
Grant/Contract Number:  
AC02-07CH11359
Resource Type:
Accepted Manuscript
Journal Name:
Monthly Notices of the Royal Astronomical Society
Additional Journal Information:
Journal Volume: 491; Journal Issue: 3; Journal ID: ISSN 0035-8711
Publisher:
Royal Astronomical Society
Country of Publication:
United States
Language:
English
Subject:
79 ASTRONOMY AND ASTROPHYSICS; methods: data analysis; cosmology: observations; large-scale structure of Universe

Citation Formats

Tanoglidis, Dimitrios, Chang, Chihway, and Frieman, Joshua. Optimizing galaxy samples for clustering measurements in photometric surveys. United States: N. p., 2019. Web. doi:10.1093/mnras/stz3281.
Tanoglidis, Dimitrios, Chang, Chihway, & Frieman, Joshua. Optimizing galaxy samples for clustering measurements in photometric surveys. United States. doi:10.1093/mnras/stz3281.
Tanoglidis, Dimitrios, Chang, Chihway, and Frieman, Joshua. Sat . "Optimizing galaxy samples for clustering measurements in photometric surveys". United States. doi:10.1093/mnras/stz3281.
@article{osti_1569241,
title = {Optimizing galaxy samples for clustering measurements in photometric surveys},
author = {Tanoglidis, Dimitrios and Chang, Chihway and Frieman, Joshua},
abstractNote = {When analysing galaxy clustering in multiband 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 includes 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 $Ωm$ and $σ_8$ in the context of Λ cold dark matter ($Λ$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 $δz$ to the photo-$z$ precision $σ_z$. When cross-correlations are included and the redshift bin width is allowed to vary, the highest FoM is achieved when $δz$ ~ $σ_z$. 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 $σ_z$, 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 = {10.1093/mnras/stz3281},
journal = {Monthly Notices of the Royal Astronomical Society},
number = 3,
volume = 491,
place = {United States},
year = {2019},
month = {11}
}

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