Intrinsic size correlations in weak lensing

Ciarlariello, Sandro; Crittenden, Robert; Pace, Francesco

doi:10.1093/mnras/stv447

Cited by 6 publications

(10 citation statements)

References 71 publications

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“…In addition, the halo density profile is one of the main ingredients for the halo model (Scherrer & Bertschinger 1991;Seljak 2000;Cooray & Sheth 2002;Sheth & Jain 2003); halo model applications for lensing include calculating the lensing power spectrum (Cooray et al 2000;Takada & Hamana 2003;Kainulainen & Marra 2011), the influence of substructures (Giocoli et al 2008(Giocoli et al , 2010, and the modelling of the intrinsic alignments (Schneider & Bridle 2010) and their effects on the lensing power spectrum (Ciarlariello et al 2014). Conversely, lensing can be used to constrain elements of the halo model (Cacciato et al 2012;Velander et al 2014).…”

Section: Introductionmentioning

confidence: 99%

The importance of the cosmic web and halo substructure for power spectra

Pace

Manera

Bacon

et al. 2015

Mon. Not. R. Astron. Soc.

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In this work we study the relevance of the cosmic web and substructures on the matter and lensing power spectra measured from halo mock catalogues extracted from the N-body simulations. Since N-body simulations are computationally expensive, it is common to use faster methods that approximate the dark matter field as a set of halos. In this approximation, we replace mass concentrations in N-body simulations by a spherically symmetric Navarro-FrenkWhite halo density profile. We also consider the full mass field as the sum of two distinct fields: dark matter halos (M > 9 × 10 12 M ⊙ /h) and particles not included into halos. Mock halos reproduce well the matter power spectrum, but underestimate the lensing power spectrum on large and small scales. For sources at z s = 1 the lensing power spectrum is underestimated by up to 40% at ℓ ≈ 10 4 with respect to the simulated halos. The large scale effect can be alleviated by combining the mock catalogue with the dark matter distribution outside the halos. In addition, to evaluate the contribution of substructures we have smeared out the intra-halo substructures in a N-body simulation while keeping the halo density profiles unchanged. For the matter power spectrum the effect of this smoothing is only of the order of 5%, but for lensing substructures are much more important: for ℓ ≈ 10 4 the internal structures contribute 30% of the total spectrum. These findings have important implications in the way mock catalogues have to be created, suggesting that some approximate methods currently used for galaxy surveys will be inadequate for future weak lensing surveys.

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Section: Introductionmentioning

confidence: 99%

The importance of the cosmic web and halo substructure for power spectra

Pace

Manera

Bacon

et al. 2015

Mon. Not. R. Astron. Soc.

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“…Overall, we find these improvements in the modelling have not affected the main conclusion of Ciarlariello et al (2015), that intrinsic correlations in the galaxy properties used to trace magnification are an important systematic to measurements of the convergence power spectrum; if ignored, they can significantly bias the cosmological interpretation of the convergence measurements.…”

Section: Discussionmentioning

confidence: 85%

“…In our previous paper (Ciarlariello et al 2015), we examined the issue of intrinsic size correlations in a halo model, where the sizes of galaxies were assumed to be a simple function of the sub-halo mass. Here, we have extended this analysis by examining the correlations in galaxy brightness, and by introducing intrinsic scatter in the mass-size and mass brightness relations.…”

Section: Discussionmentioning

confidence: 99%

“…The magnitude biases are also generally higher than the size biases, due to the steepness of the Vale-Ostriker mass-luminosity relation. As a result, we expect the intrinsic correlations to be more of a contaminant for convergence estimation than was the case for sizes (Ciarlariello et al 2015). …”

Section: Two-halo Termsmentioning

confidence: 99%

“…This analysis has been extended in Alsing et al (2015) which provided an estimate of the convergence dispersion expected from size measurements and, analogously to intrinsic alignments for cosmic shear, they study the possible impact of marginalising over intrinsic size correlations on constraints of cosmological parameters such as the dark energy equation of state parameters. In Ciarlariello et al (2015) (hereafter CCP15), we investigated a theoretical model in which intrinsic size correlations arise in a simple halo model, assuming larger and more massive galaxies reside in more massive haloes and linking observed galaxy sizes to halo and subhalo masses through the relation found by Kravtsov (2013). Haloes are populated with subhaloes by means of a subhalo mass function which accounts for the fact the size of the largest subhaloes is limited by the total halo mass.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Modelling the impact of intrinsic size and luminosity correlations on magnification estimation

Ciarlariello

Crittenden²

2016

Mon. Not. R. Astron. Soc.

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Spatial correlations of the observed sizes and luminosities of galaxies can be used to estimate the magnification that arises through weak gravitational lensing. However, the intrinsic properties of galaxies can be similarly correlated through local physical effects, and these present a possible contamination to the weak lensing estimation. In an earlier paper (Ciarlariello et al. 2015) we modelled the intrinsic size correlations using the halo model, assuming the galaxy sizes reflect the mass in the associated halo. Here we extend this work to consider galaxy magnitudes and show that these may be even more affected by intrinsic correlations than galaxy sizes, making this a bigger systematic for measurements of the weak lensing signal. We also quantify how these intrinsic correlations are affected by sample selection criteria based on sizes and magnitudes.

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An EFT description of galaxy intrinsic alignments

Vlah

Chisari

Schmidt

2020

J. Cosmol. Astropart. Phys.

146

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We present a general perturbative effective field theory (EFT) description of galaxy shape correlations, which are commonly known as intrinsic alignments. This rigorous approach extends current analytical modelling strategies in that it only relies on the equivalence principle. We present our results in terms of three-dimensional statistics for two-and three-point functions of both galaxy shapes and number counts. In case of the two-point function, we recover the well-known linear alignment result at leading order, but also present the full next-to-leading order expressions. In case of the three-point function we present leading order results for all the auto-and cross-correlations of galaxy shapes and densities. We use a spherical tensor basis to decompose the tensor perturbations in different helicity modes, which allows us to make use of isotropy and parity properties in the correlators. Combined with the results on projection presented in a forthcoming companion paper, our framework is directly applicable to accounting for intrinsic alignment contamination in weak lensing surveys, and to extracting cosmological information from intrinsic alignments. 42A.1 Two-point functions 44 A.2 Three-point functions 47 B Fields in Fourier space 50 B.1 Bias expansion and renormalisation of the one-loop power spectrum 55 B.2 Degeneracy of the bias operators 62 B.3 Bias expansion of the tree-level bispectrum 63 C Bias renormalisation for tensor fields 65 1 Explicitly, we writewhere the Dirac delta function ensures the total momentum conservation, and is a consequence of the statistical translation invariance.

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Intrinsic size correlations in weak lensing

Cited by 6 publications

References 71 publications

The importance of the cosmic web and halo substructure for power spectra

The importance of the cosmic web and halo substructure for power spectra

Modelling the impact of intrinsic size and luminosity correlations on magnification estimation

An EFT description of galaxy intrinsic alignments

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