SAMPLE VARIANCE IN<i>N</i>-BODY SIMULATIONS AND IMPACT ON TOMOGRAPHIC SHEAR PREDICTIONS

Casarini, Luciano; Piattella, Oliver F.; Bonometto, S. A.; Mezzetti, M.

doi:10.1088/0004-637x/812/1/16

Cited by 6 publications

(7 citation statements)

References 51 publications

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“…In particular, we find that only a few components (5-10) are necessary to characterize the cosmological information content in single redshift statistics, while more components (30)(31)(32)(33)(34)(35)(36)(37)(38)(39)(40) are necessary when tomography is included. Nevertheless we find that the number of required components N c is significantly smaller than the full summary statistic space dimensionality before performing PCA.…”

Section: Discussionmentioning

confidence: 98%

Cosmology with photometric weak lensing surveys: Constraints with redshift tomography of convergence peaks and moments

2016

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Weak gravitational lensing is becoming a mature technique for constraining cosmological parameters, and future surveys will be able to constrain the dark energy equation of state w. When analyzing galaxy surveys, redshift information has proven to be a valuable addition to angular shear correlations. We forecast parameter constraints on the triplet (Ωm, w, σ8) for an LSST-like photometric galaxy survey, using tomography of the shear-shear power spectrum, convergence peak counts and higher convergence moments. We find that redshift tomography with the power spectrum reduces the area of the 1σ confidence interval in (Ωm, w) space by a factor of 8 with respect to the case of the single highest redshift bin. We also find that adding non-Gaussian information from the peak counts and higher-order moments of the convergence field and its spatial derivatives further reduces the constrained area in (Ωm, w) by a factor of 3 and 4, respectively. When we add cosmic microwave background parameter priors from Planck to our analysis, tomography improves power spectrum constraints by a factor of 3. Adding moments yields an improvement by an additional factor of 2, and adding both moments and peaks improves by almost a factor of 3, over power spectrum tomography alone. We evaluate the effect of uncorrected systematic photometric redshift errors on the parameter constraints. We find that different statistics lead to different bias directions in parameter space, suggesting the possibility of eliminating this bias via self-calibration.PACS numbers: 95.36.+x, 95.30.Sf, 98.62.Sb

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Section: Discussionmentioning

confidence: 98%

Cosmology with photometric weak lensing surveys: Constraints with redshift tomography of convergence peaks and moments

2016

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“…On the other hand, relaxing the required accuracy to 50% of the statistical error, we find N s = 2 to be always sufficient. As pointed out by [42], the box size used for the N -body simulations can also play an important role in the accuracy of the power spectrum ensemble means. Figure 3 shows the variance of convergence power spectrum computed from different ensembles, in units of the Gaussian expectation.…”

Section: Discussionmentioning

confidence: 99%

Sample variance in weak lensing: How many simulations are required?

2016

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Constraining cosmology using weak gravitational lensing consists of comparing a measured feature vector of dimension N b with its simulated counterpart. An accurate estimate of the N b × N b feature covariance matrix C is essential to obtain accurate parameter confidence intervals. When C is measured from a set of simulations, an important question is how large this set should be. To answer this question, we construct different ensembles of Nr realizations of the shear field, using a common randomization procedure that recycles the outputs from a smaller number Ns ≤ Nr of independent ray-tracing N -body simulations. We study parameter confidence intervals as a function of (Ns, Nr) in the range 1 ≤ Ns ≤ 200 and 1 ≤ Nr 10 5 . Previous work [1] has shown that Gaussian noise in the feature vectors (from which the covariance is estimated) lead, at quadratic order, to an O(1/Nr) degradation of the parameter confidence intervals. Using a variety of lensing features measured in our simulations, including shear-shear power spectra and peak counts, we show that cubic and quartic covariance fluctuations lead to additional O(1/N 2 r ) error degradation that is not negligible when Nr is only a factor of few larger than N b . We study the large Nr limit, and find that a single, 240Mpc/h sized 512 3 -particle N -body simulation (Ns = 1) can be repeatedly recycled to produce as many as Nr = few × 10 4 shear maps whose power spectra and high-significance peak counts can be treated as statistically independent. As a result, a small number of simulations (Ns = 1 or 2) is sufficient to forecast parameter confidence intervals at percent accuracy.PACS numbers: 95.36.+x, 95.30.Sf, 98.62.Sb

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“…However, while individual state-of-the-art simulations may have a very high precision, that is, small statistical errors on the parameters that enter the mass function, their accuracy may not necessarily be so high (Knebe et al 2013;Murray et al 2013;Casarini et al 2015). Indeed, many are the possible causes of systematic differences between simulations which could affect cosmological forecasts (Cunha & Evrard 2010;Paranjape 2014;Schneider et al 2015;Bocquet et al 2016).…”

Section: Introductionmentioning

confidence: 99%

Constraining the halo mass function with observations

Castro

Marra

Quartin

2016

Mon. Not. R. Astron. Soc.

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The abundances of dark matter halos in the universe are described by the halo mass function (HMF). It enters most cosmological analyses and parametrizes how the linear growth of primordial perturbations is connected to these abundances. Interestingly, this connection can be made approximately cosmology independent. This made it possible to map in detail its near-universal behavior through large-scale simulations. However, such simulations may suffer from systematic effects, especially if baryonic physics is included. In this paper we ask how well observations can constrain directly the HMF. The observables we consider are galaxy cluster number counts, galaxy cluster power spectrum and lensing of type Ia supernovae. Our results show that DES is capable of putting the first meaningful constraints on the HMF, while both Euclid and J-PAS can give stronger constraints, comparable to the ones from state-of-the-art simulations. We also find that an independent measurement of cluster masses is even more important for measuring the HMF than for constraining the cosmological parameters, and can vastly improve the determination of the halo mass function. Measuring the HMF could thus be used to cross-check simulations and their implementation of baryon physics. It could even, if deviations cannot be accounted for, hint at new physics.

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SAMPLE VARIANCE INN-BODY SIMULATIONS AND IMPACT ON TOMOGRAPHIC SHEAR PREDICTIONS

Cited by 6 publications

References 51 publications

Cosmology with photometric weak lensing surveys: Constraints with redshift tomography of convergence peaks and moments

Cosmology with photometric weak lensing surveys: Constraints with redshift tomography of convergence peaks and moments

Sample variance in weak lensing: How many simulations are required?

Constraining the halo mass function with observations

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