K17_Fig1b

Weak-lensing projections

Authors: M. Kilbinger, C. Heymans et al.
Journal: submitted to MNRAS
Year: 2017
Download: ADS | arXiv


Abstract

We compute the spherical-sky weak-lensing power spectrum of the shear and convergence. We discuss various approximations, such as flat-sky, and first- and second- order Limber equations for the projection. We find that the impact of adopting these approximations are negligible when constraining cosmological parameters from current weak lensing surveys. This is demonstrated using data from the Canada-France-Hawaii Lensing Survey (CFHTLenS). We find that the reported tension with Planck Cosmic Microwave Background (CMB) temperature anisotropy results cannot be alleviated, in contrast to the recent claim made by Kitching et al. (2016, version 1). For future large-scale surveys with unprecedented precision, we show that the spherical second-order Limber approximation will provide sufficient accuracy. In this case, the cosmic-shear power spectrum is shown to be in agreement with the full projection at the sub-percent level for l > 3, with the corresponding errors an order of magnitude below cosmic variance for all l. When computing the two-point shear correlation function, we show that the flat-sky fast Hankel transformation results in errors below two percent compared to the full spherical transformation. In the spirit of reproducible research, our numerical implementation of all approximations and the full projection are publicly available within the package nicaea at http://www.cosmostat.org/software/nicaea.


Summary

We discuss various methods to calculate projections for weak gravitational lensing: Since lenses galaxies pick up matter inhomogeneities of the cosmic web along the line of sight while photons from the galaxies propagate through the Universe to the observer, these inhomogeneities have to be projected to a 2D observable, the cumulative shear or convergence. The full projection involves three-dimensional integrals over highly oscillating Bessel functions, and can be time-consuming to compute numerically to high accuracy. Most previous work have therefore used approximations such as the Limber approximation, that reduce the integrals to 1D, and thereby neglecting modes along the line of sight.

The authors show that these projections are more than adequate for present surveys. Sub-percent accuracy is reached for l>20, for example as shown by the pink curve, which is the ratio of the case 'ExtL1Hyb' to the full projection. The abbreviation means 'extended', corresponding to the improved approximation introduced by LoVerde & Afshordi (2008), first-order Limber, and hybrid, since this is a hybrid between flat-sky and spherical coordinates. This case has been used in most of the recent publications (e.g. for KiDS), whereas the cast 'L1Fl' (first-order Limber flat-sky) was popular for most publications since 2014.

These approximations are sufficient for the small areas of current observations coming from CFHTLenS, KiDS, and DES, and well below cosmic variance of even future surveys (the figure shows Euclid - 15,000 deg2 and Kids -1,500 deg2).

K17_Fig1b

The paper then discusses the second-order Limber approximation, introduced in a general framework by LoVerde & Afshordi (2008), and applied to weak lensing in the current paper. The best 2nd-order case 'ExtL2Sph' reaches sub-percent accuracy down to l=3, sufficient for all future surveys.

The paper also computes the shear correlation function in real space, and shows that those approximations have a very minor influence.

We then go on to re-compute the cosmological constraints obtained in Kilbinger et al. (2013), and find virtually no change when choosing different approximations. Only the depreciated case 'ExtL1Fl' makes a noticeable difference, which is however still well within the statistical error bars. This case shows a particular slow convergence to the full projection.

Similar results have been derived in two other recent publications, Kitching et al. (2017), and Lemos, Challinor & Efstathiou (2017).
Note however that Kitching et al. (2017) conclude that errors from projection approximations of the types we discussed here (Limber, flat sky) could make up to 11% of the error budget of future surveys. This is however assuming the worst-case scenario including the deprecated cast 'ExtL1Fl', and we do not share their conclusion, but think that for example the projection 'ExtL2Sph' is sufficient for future surveys such as LSST and Euclid.

Lieu-MT

The XXL Survey

First round of papers published

 

The XXL Survey is a deep X-ray survey observed with the XMM satellite, covering two fields of 25 deg2 each. Observations in many other wavelength, from radio to IR and optical, in both imaging and spectroscopy, complement the survey. The main science case is cosmology with X-ray selected galaxy clusters, but other fields such as galaxy evolution, AGNs, cluster physics, and the large-scale structure are being studied.

The main paper (Paper I) describing the survey and giving an overview of the science is arXiv:1512.04317 (Pierre et al. 2015). Paper IV (arxiv.org:1512.03857, Lieu et al. 2015) presents weak-lensing mass measurements of the brightest clusters in the Northern field, using CFHTLenS shapes and photometric redshifts.

 

The mass-temperature relation for XXL and other surveys (CCCP, COSMOS), Lieu et al (2015).
Sigma_tab_0715

Review: Cosmology from cosmic shear observations

Martin Kilbinger, CEA Saclay, Service d'Astrophysique (SAp), France

Find on this page general information and updates for my recent review article (arXiv:1411.0155) on cosmic shear, Reports on Progress in Physics 78 (2015) 086901 (ads link for two-column format).

Sigma 06/16
Fig. 7 of the review article: The quantity \Sigma = \sigma_8 \left( \Omega_{\rm m}/0.3 \right)^\alpha as function of publication year.
Get the data in table format as pdf.
 
 
 
Updated figure!
02/2015: Added Stripe-82 and CFHTLenS peak counts
07/2015: Added DES-SV.
06/2016: Added DLS, two more CFHTLenS analyses, DES-SV peak counts, and KiDS-450.
08/2017: Added DES-Y1, and another KiDS-450 result.
 
 
 
 

In the video abstract of the article I talk about cosmic shear and the review for a broader audience.
 
 
 
 
Additional references, new papers
General papers, new reviews.
 
    • Another weak-lensing review has been published by my colleagues Liping Fu and Zu-Hui Fan (behind a pay wall, not available on the arXiv).
    • Rachel Mandelbaum's short, pedagogical review to instrumental systematics and WL

 Sect. 2: Cosmological background

 Sect. 5: Measuring weak lensing

    • News on ensemble shape measurement methods:
      An implementation of the Bernstein & Armstrong (2014) Bayesian shape method has been published at arXiv:1403.7669. The team that participated at the great3 challenge with the Bayesian inference method "MBI" published their pipeline and results paper, see arXiv:1411.2608.
    • Okura & Futamase (arXiv:1405.1539) came up with an estimator of ellipticity that uses 0th instead of 2nd-order moments!
    • arXiv:1409.6273 discusses atmospheric chromatic effects for LSST.
    • Dust in spiral galaxies  as source of shape bias, but also astrophysical probe: arXiv:1411.6724.

Scripts

Fig. 3 (b), derivatives of the convergence power spectrum with respect to various cosmological parameters.
cs_review_scripts.tgz.


Comments and suggestions are welcome! Please write to me at martin.kilbinger@cea.fr.

Last updated 22 July 2015.

K17_Fig1b

A new model to predict weak-lensing peak counts I. Comparison with N-body Simulations

Authors: C.-A. Lin, M. Kilbinger.
Journal: A&A 576, A24
Year: 2015
Download: ADS | arXiv

 


Abstract

Weak-lensing peak counts has been shown to be a powerful tool for cosmology. It provides non-Gaussian information of large scale structures, complementary to second order statistics. We propose a new flexible method to predict weak lensing peak counts, which can be adapted to realistic scenarios, such as a real source distribution, intrinsic galaxy alignment, mask effects, photo-z errors from surveys, etc. The new model is also suitable for applying the tomography technique and non-linear filters. A probabilistic approach to model peak counts is presented. First, we sample halos from a mass function. Second, we assign them NFW profiles. Third, we place those halos randomly on the field of view. The creation of these "fast simulations" requires much less computing time compared to N-body runs. Then, we perform ray-tracing through these fast simulation boxes and select peaks from weak-lensing maps to predict peak number counts. The computation is achieved by our \textsc{Camelus} algorithm, which we make available at this http URL. We compare our results to N-body simulations to validate our model. We find that our approach is in good agreement with full N-body runs. We show that the lensing signal dominates shape noise and Poisson noise for peaks with SNR between 4 and 6. Also, counts from the same SNR range are sensitive to Ωm and σ8. We show how our model can discriminate between various combinations of those two parameters. In summary, we offer a powerful tool to study weak lensing peaks. The potential of our forward model is its high flexibility, making the use of peak counts under realistic survey conditions feasible.


Summary

A new, probabilistic model for weak-lensing peak counts is being proposed in this first paper of a series of three. The model is based on drawing halos from the mass function and, via ray-tracing, generating weak-lensing maps to count peaks. These simulated maps can directly be compared to observations, making this a forward-modelling approach of the cluster mass function, in contrast to many other traditional methods using cluster probes such as X-ray, optical richness, or SZ observations.

The model prediction is in very good agreement with N-body simulations.

It is very flexible, and can potentially include astrophysical and observational effects, such as intrinsic alignment, halo triaxiality, masking, photo-z errors, etc. Moreover, the pdf of the number of peaks can be output by the model, allowing for a very general likelihood calculation, without e.g. assuming a Gaussian distribution of the observables.

 

review1

Review: Cosmology from cosmic shear observations

Mean and 68% error bars for the parameter  $\sigma_8 (\Omega_{\rm m}/0.3)^\alpha$, for various cosmic shear observations, plotted as function of their publication date (first arXiv submission). Data points are second-order statistics (circles), third-order (diamonds), 3D lensing (pentagons), galaxy-galaxy lensing (+ galaxy clustering; triangle), and CMB (squares).
Mean and 68% error bars for the parameter \sigma_8 (\Omega_{\rm m}/0.3)^\alpha, for various cosmic shear observations, plotted as function of their publication date (first arXiv submission). Data points are second-order statistics (circles), third-order (diamonds), 3D lensing (pentagons), galaxy-galaxy lensing (+ galaxy clustering; triangle), and CMB (squares).

A review on cosmology from cosmic shear observations has been submitted to ROPP, and has the arXiv reference arXiv:1411.0115. Comments are very welcome! Check also the accompanying web page for more information, updates, and errata.

reduced_F3c

Reduced-shear power spectrum

Fitting formulae of the reduced-shear power spectrum for weak lensing

Reference

Martin Kilbinger, 2010, arXiv:1004.3493

Description

We provide fitting formulae for the reduced-shear power-spectrum correction which is third-order in the lensing potential. This correction reaches up to 10% of the total lensing spectrum. Higher-order correction terms are one order of magnitude below the third-order term. The correction involves an integral over the matter bispectrum. We fit this integral with a combination of power-law functions and polynomials. We also fit the derivatives with respect to cosmological parameters. A Taylor-expansion around a fiducial (WMAP7) model provides accurate reduced-shear corrections within a region in parameter space containing the WMAP7 68% error elllipsoid.

Results

Our fits are accurate to 1% for l<104, and to 2% for l<2·105, which reduces the bias by a factor of four compared to the case of no correction. This matches the precision lensing power spectrum predictions of recent N-body simulations.

Ratio of power spectra uncorrected (lower lines) and corrected (upper lines) for reduced-shear.

 

Download, install, and run the code

Download an example code which includes the fitting matrices. Use 'make' to compile the code. To use the code, you have to fill in Fmn(a) (eq. 10 from the paper) which involves the lensing efficiency, comoving distances and the redshift distribution(s).

The reduced-shear corrections are also implemented in the cosmology and lensing package 'nicaea'. This code provides all necessary functions to produce lensing observables (shear power spectrum and real-space second-order functions). The cosmology and redshift distributions are set via parameter files.

Author

Martin Kilbinger (martin.kilbinger@cea.fr)

EBmode2

Optimes E-/B-mode decomposition

A new cosmic shear function:
Optimised E-/B-mode decomposition on a finite interval

Reference

Liping Fu, Martin Kilbinger, 2009, arXiv:0907.0795

Description

We have introduced a new cosmic shear statistic which decomposes the shear correlation into E- and B-modes on a finite angular interval. The new function is calculated by integrating the shear two-point correlation function with a filter function. The filter function fulfills the E-/B-mode decomposition constraints given in Schneider & Kilbinger (2007).

Download, install, and run the code

Download the tar file decomp.tgz. Extract the archive with
tar xzf decomp.tgz

To compile and run the code:
cd Demo
make links
make decomp_eb
decomp_eb

The package fftw3 has to be installed. If it is not in a standard directory, fftw3.h is looked for in $(FFTW)/include and libfftw3.a in $(FFTW)/lib. Change the variable `FFTW' in the Makefile accordingly. You can download fftw3 from http://www.fftw.org.

The program produces two files, Tpm containing the filter functions T+ and T-, and REB containing the shear functions RE and RB.

Authors

Liping Fu, Martin Kilbinger (martin.kilbinger@cea.fr)