Optimizing galaxy samples for clustering measurements in photometric surveys

Tanoglidis, Dimitrios; Chang, C.; Frieman, Joshua A.

doi:10.1093/mnras/stz3281

Cited by 10 publications

(11 citation statements)

References 54 publications

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“…Clearly, having a fainter magnitude cut results in larger samples that yield higher FoM values. This trend is in agreement with the results presented in Tanoglidis et al (2019).…”

Section: Fom Dependency On Photometric Redshift Quality and Number Densitysupporting

confidence: 94%

“…The optimization of the sample of photometrically selected galaxies for galaxy clustering analyses has been already studied in the literature. In Tanoglidis et al (2019), the authors focus their analysis on galaxy clustering for the first three years of DES data. Also for DES but including galaxy-galaxy lensing, Porredon et al (2021) studies lens galaxy sample selections based on magnitude cuts as a function of photo-z, balancing density and photo-z accuracy to optimize cosmological constrains in the wCDM space.…”

Section: Introductionmentioning

confidence: 99%

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Euclidpreparation

Pocino¹,

Tutusaus²,

Castander³

et al. 2021

A&A

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Photometric redshifts (photo-zs) are one of the main ingredients in the analysis of cosmological probes. Their accuracy particularly affects the results of the analyses of galaxy clustering with photometrically selected galaxies (GCph) and weak lensing. In the next decade, space missions such as Euclid will collect precise and accurate photometric measurements for millions of galaxies. These data should be complemented with upcoming ground-based observations to derive precise and accurate photo-zs. In this article we explore how the tomographic redshift binning and depth of ground-based observations will affect the cosmological constraints expected from the Euclid mission. We focus on GCph and extend the study to include galaxy-galaxy lensing (GGL). We add a layer of complexity to the analysis by simulating several realistic photo-z distributions based on the Euclid Consortium Flagship simulation and using a machine learning photo-z algorithm. We then use the Fisher matrix formalism together with these galaxy samples to study the cosmological constraining power as a function of redshift binning, survey depth, and photo-z accuracy. We find that bins with an equal width in redshift provide a higher figure of merit (FoM) than equipopulated bins and that increasing the number of redshift bins from ten to 13 improves the FoM by 35% and 15% for GCph and its combination with GGL, respectively. For GCph, an increase in the survey depth provides a higher FoM. However, when we include faint galaxies beyond the limit of the spectroscopic training data, the resulting FoM decreases because of the spurious photo-zs. When combining GCph and GGL, the number density of the sample, which is set by the survey depth, is the main factor driving the variations in the FoM. Adding galaxies at faint magnitudes and high redshift increases the FoM, even when they are beyond the spectroscopic limit, since the number density increase compensates for the photo-z degradation in this case. We conclude that there is more information that can be extracted beyond the nominal ten tomographic redshift bins of Euclid and that we should be cautious when adding faint galaxies into our sample since they can degrade the cosmological constraints.

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“…Clearly, having a fainter magnitude cut results in larger samples that yield higher FoM values. This trend is in agreement with the results presented in Tanoglidis et al (2019).…”

Section: Fom Dependency On Photometric Redshift Quality and Number Densitysupporting

confidence: 94%

Section: Introductionmentioning

confidence: 99%

Euclidpreparation

Pocino¹,

Tutusaus²,

Castander³

et al. 2021

A&A

View full text Add to dashboard Cite

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“…This type of sample has been used in various analyses in the past, e. g. the galaxy clustering analysis of DES Science Verification data [29], and also in CFHTLS [30] and HSC [31]. In particular, [47] considers this approach, using DES Y1 data, to study the trade-off between number density and photo-z accuracy and its impact in terms of cosmological constraints from galaxy clustering with fixed bias parameters. Therefore, it is interesting to consider this type of sample here, and compare it with the other two samples, MAGLIM and REDMAGIC, described next.…”

Section: Flux-limited Samplementioning

confidence: 99%

“…The motivation for the latter is that, as seen in Figure 8, the MAGLIM sample has more overlap between z bins than the REDMAGIC sample, so galaxy clustering crosscorrelations could become important for our analysis. In addition, [47] shows that the improvement on the Ω m and σ 8 constraints can be greatly increased with the number of z bins and the inclusion of cross-correlations between z bins, especially for samples with large overlap between bins.…”

Section: A Tomographic Binning and Cross-correlationsmentioning

confidence: 99%

“…[47] shows that, for a flux-limited sample, the improvement on the cosmological constraints can be greatly increased with the number of z bins and the inclusion of cross-correlations between z bins. In [47] the authors consider only galaxy clustering, and fix all parameters except for Ω m , σ 8 , and the photo-z nuisance parameters. We have attempted to reproduce their results, and while we do not find the same level of gains on the constraints, we observe the same tendency.…”

Section: A Tomographic Binning and Cross-correlationsmentioning

confidence: 99%

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Dark Energy Survey Year 3 Results: Optimizing the Lens Sample in Combined Galaxy Clustering and Galaxy-Galaxy Lensing Analysis

Porredon,

Crocce,

Fosalba

et al. 2020

Preprint

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We investigate potential gains in cosmological constraints from the combination of galaxy clustering and galaxy-galaxy lensing by optimizing the lens galaxy sample selection using information from Dark Energy Survey (DES) Year 3 data and assuming the DES Year 1 METACALIBRATION sample for the sources. We explore easily reproducible selections based on magnitude cuts in i-band as a function of (photometric) redshift, z phot , and benchmark the potential gains against those using the well established REDMAGIC [1] sample. We focus on the balance between density and photometric redshift accuracy, while marginalizing over a realistic set of cosmological and systematic parameters. Our optimal selection, the MAGLIM sample, satisfies i < 4 z phot + 18 and has ∼ 30% wider redshift distributions but ∼ 3.5 times more galaxies than REDMAGIC. Assuming a wCDM model and equivalent scale cuts to mitigate nonlinear effects, this leads to 40% increase in the figure of merit for the pair combinations of Ωm, w, and σ8, and gains of 16% in σ8, 10% in Ωm, and 12% in w. Similarly, in ΛCDM we find an improvement of 19% and 27% on σ8 and Ωm, respectively. We also explore flux-limited samples with a flat magnitude cut finding that the optimal selection, i < 22.2, has ∼ 7 times more galaxies and ∼ 20% wider redshift distributions compared to MAGLIM, but slightly worse constraints. We show that our results are robust with respect to the assumed galaxy bias and photometric redshift uncertainties with only moderate further gains from increased number of tomographic bins or the inclusion of bin cross-correlations, except in the case of the flux-limited sample, for which these gains are more significant.

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Photo-z outlier self-calibration in weak lensing surveys

Schaan

Ferraro

Seljak

2020

J. Cosmol. Astropart. Phys.

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Calibrating photometric redshift errors in weak lensing surveys with external data is extremely challenging. We show that both Gaussian and outlier photo-z parameters can be self-calibrated from the data alone. This comes at no cost for the neutrino masses, curvature and dark energy equation of state w0, but with a 65% degradation when both w0 and wa are varied. We perform a realistic forecast for the Vera Rubin Observatory (VRO) Legacy Survey of Space and Time (LSST) 3× 2 analysis, combining cosmic shear, projected galaxy clustering and galaxy—galaxy lensing. We confirm the importance of marginalizing over photo-z outliers. We examine a subset of internal cross-correlations, dubbed “null correlations”, which are usually ignored in 3× 2 analyses. Despite contributing only ∼ 10% of the total signal-to-noise, these null correlations improve the constraints on photo-z parameters by up to an order of magnitude. Using the same galaxy sample as sources and lenses dramatically improves the photo-z uncertainties too. Together, these methods add robustness to any claim of detected new Physics, and reduce the statistical errors on cosmology by 15% and 10% respectively. Finally, including CMB lensing from an experiment like Simons Observatory or CMB-S4 improves the cosmological and photo-z posterior constraints by about 10%, and further improves the robustness to systematics. To give intuition on the Fisher forecasts, we examine in detail several toy models that explain the origin of the photo-z self-calibration. Our Fisher code LaSSI (Large-Scale Structure Information), which includes the effect of Gaussian and outlier photo-z, shear multiplicative bias, linear galaxy bias, and extensions to LCDM, is publicly available at \href{https://github.com/EmmanuelSchaan/LaSSI}{https://github.com/EmmanuelSchaan/LaSSI}.

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Optimizing galaxy samples for clustering measurements in photometric surveys

Cited by 10 publications

References 54 publications

Euclidpreparation

Euclidpreparation

Dark Energy Survey Year 3 Results: Optimizing the Lens Sample in Combined Galaxy Clustering and Galaxy-Galaxy Lensing Analysis

Photo-z outlier self-calibration in weak lensing surveys

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