Extreme value statistics of weak lensing shear peak counts

Reischke, Robert; Maturi, M.; Bartelmann, Matthias

doi:10.1093/mnras/stv2677

Cited by 18 publications

(15 citation statements)

References 42 publications

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“…Extreme value statistics allow us to assess the probability of finding unusual objects in the Universe (e.g. Davis et al 2011;Waizmann et al 2011;Yaryura et al 2011;Reischke et al 2016). Since we did not find a halo in the MXXL simulation with a distribution of substructure like that seen in Abell 2744, we can use extreme value theory to estimate the simulation volume that would be needed to find at least one halo with the same substructure.…”

Section: Extreme Value Statisticsmentioning

confidence: 99%

Abell 2744: too much substructure for ΛCDM?

Schwinn

Jauzac

Baugh

et al. 2017

Monthly Notices of the Royal Astronomical Society

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The massive substructures found in Abell 2744 by Jauzac et al. (2016) present a challenge to the cold dark matter paradigm due to their number and proximity to the cluster centre. We use one of the biggest N-body simulations, the Millennium XXL, to investigate the substructure in a large sample of massive dark matter haloes. A range of effects which influence the comparison with the observations is considered, extending the preliminary evaluation carried out by Jauzac et al. (2016). There are many tens of haloes in the simulation with a total mass comparable with or larger than that of Abell 2744. However, we find no haloes with a number and distribution of massive substructures (> 5 × 10 13 M ) that is close to that inferred from the observations of Abell 2744. The application of extreme value statistics suggests that we would need a simulation of at least ten times the volume of the Millennium XXL to find a single dark matter halo with a similar internal structure to Abell 2744. Explaining the distribution of massive substructures in clusters is a new hurdle for hierarchical models to negotiate, which is not weakened by appeals to baryonic physics or uncertainty over the nature of the dark matter particle.

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Section: Extreme Value Statisticsmentioning

confidence: 99%

Abell 2744: too much substructure for ΛCDM?

Schwinn

Jauzac

Baugh

et al. 2017

Monthly Notices of the Royal Astronomical Society

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“…Using a Bayesian approach with flat priors Ω m ∈ [0, 0.7] and σ 8 ∈ [0.4, 1.4] the probability of measuringd meas. if the true parameters are π, is then proportional to 13) where N d is the length of the vectord meas. andΣ −1 is the inverse of our covariance estimate.…”

Section: Likelihood Analysismentioning

confidence: 99%

Weak lensing peak statistics in the era of large scale cosmological surveys

Fluri

Kacprzak

Sgier

et al. 2018

J. Cosmol. Astropart. Phys.

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Weak lensing peak counts are a powerful statistical tool for constraining cosmological parameters. So far, this method has been applied only to surveys with relatively small areas, up to several hundred square degrees. As future surveys will provide weak lensing datasets with size of thousands of square degrees, the demand on the theoretical prediction of the peak statistics will become heightened. In particular, large simulations of increased cosmological volume are required. In this work, we investigate the possibility of using simulations generated with the fast Comoving-Lagrangian acceleration (COLA) method, coupled to the convergence map generator Ufalcon, for predicting the peak counts. We examine the systematics introduced by the COLA method by comparing it with a full TreePM code. We find that for a 2000 deg 2 survey, the systematic error is much smaller than the statistical error. This suggests that the COLA method is able to generate promising theoretical predictions for weak lensing peaks. We also examine the constraining power of various configurations of data vectors, exploring the influence of splitting the sample into tomographic bins and combining different smoothing scales. We find the combination of smoothing scales to have the most constraining power, improving the constraints on the S 8 amplitude parameter by at least 40% compared to a single smoothing scale, with tomography brining only limited increase in measurement precision.

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“…Pires et al (2012) demonstrated that peak counts are the best statistic to break the σ 8 -Ω m degeneracy among the second-order weak lensing statistics. Reischke et al (2016) have suggested that the extreme value statistic of peak counts can tighten even more the constraints on cosmological parameters.…”

Section: Introductionmentioning

confidence: 99%

Weak-lensing peaks in simulated light cones: investigating the coupling between dark matter and dark energy

Giocoli

Moscardini

Baldi

et al. 2018

Monthly Notices of the Royal Astronomical Society

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In this paper, we study the statistical properties of weak lensing peaks in lightcones generated from cosmological simulations. In order to assess the prospects of such observable as a cosmological probe, we consider simulations that include interacting Dark Energy (hereafter DE) models with coupling term between DE and Dark Matter. Cosmological models that produce a larger population of massive clusters have more numerous high signal-to-noise peaks; among models with comparable numbers of clusters those with more concentrated haloes produce more peaks. The most extreme model under investigation shows a difference in peak counts of about 20% with respect to the reference ΛCDM model. We find that peak statistics can be used to distinguish a coupling DE model from a reference one with the same power spectrum normalisation. The differences in the expansion history and the growth rate of structure formation are reflected in their halo counts, non-linear scale features and, through them, in the properties of the lensing peaks. For a source redshift distribution consistent with the expectations of future space-based wide field surveys, we find that typically seventy percent of the cluster population contributes to weak-lensing peaks with signal-to-noise ratios larger than two, and that the fraction of clusters in peaks approaches one-hundred percent for haloes with redshift z ≤ 0.5. Our analysis demonstrates that peak statistics are an important tool for disentangling DE models by accurately tracing the structure formation processes as a function of the cosmic time.

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Extreme value statistics of weak lensing shear peak counts

Cited by 18 publications

References 42 publications

Abell 2744: too much substructure for ΛCDM?

Abell 2744: too much substructure for ΛCDM?

Weak lensing peak statistics in the era of large scale cosmological surveys

Weak-lensing peaks in simulated light cones: investigating the coupling between dark matter and dark energy

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