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Register a new userImpact of baryons in cosmic shear analyses with tomographic aperture mass statistics
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NonGaussian cosmic shear statistics based on weak-lensing aperture mass ($M_{rm ap}$) maps can outperform the classical shear two-point correlation function ($gamma$-2PCF) in terms of cosmological constraining power. However, reaching the full potential of these new estimators requires accurate modeling of the physics of baryons as the extra nonGaussian information mostly resides at small scales. We present one such modeling based on the Magneticum hydrodynamical simulation for the KiDS-450 and DES-Y1 surveys and a Euclid-like survey. We compute the bias due to baryons on the lensing PDF and the distribution of peaks and voids in $M_{rm ap}$ maps and propagate it to the cosmological forecasts on the structure growth parameter $S_8$, the matter density parameter $Omega_{rm m}$, and the dark energy equation of state $w_0$ using the SLICS and cosmo-SLICS sets of dark-matter-only simulations. We report a negative bias of a few percent on $S_8$ and $Omega_{rm m}$ and also measure a positive bias of the same level on $w_0$ when including a tomographic decomposition. These biases reach $sim 5$% when combining $M_{rm ap}$ statistics with the $gamma$-2PCF as these estimators show similar dependency on the AGN feedback. We verify that these biases constitute a less than $1sigma$ shift on the probed cosmological parameters for current cosmic shear surveys. However, baryons need to be accounted for at the percentage level for future Stage IV surveys and we propose to include the uncertainty on the AGN feedback amplitude by marginalizing over this parameter using multiple simulations such as those presented in this paper. Finally, we explore the possibility of mitigating the impact of baryons by filtering the $M_{rm ap}$ map but find that this process would require to suppress the small-scale information to a point where the constraints would no longer be competitive.
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We forecast and optimize the cosmological power of various weak-lensing aperture mass ($M_{rm ap}$) map statistics for future cosmic shear surveys, including peaks, voids, and the full distribution of pixels (1D $M_{rm ap}$). These alternative methods probe the non-Gaussian regime of the matter distribution, adding complementary cosmological information to the classical two-point estimators. Based on the SLICS and cosmo-SLICS $N$-body simulations, we build Euclid-like mocks to explore the $S_8 - Omega_{rm m} - w_0$ parameter space. We develop a new tomographic formalism which exploits the cross-information between redshift slices (cross-$M_{rm ap}$) in addition to the information from individual slices (auto-$M_{rm ap}$) probed in the standard approach. Our auto-$M_{rm ap}$ forecast precision is in good agreement with the recent literature on weak-lensing peak statistics, and is improved by $sim 50$% when including cross-$M_{rm ap}$. It is further boosted by the use of 1D $M_{rm ap}$ that outperforms all other estimators, including the shear two-point correlation function ($gamma$-2PCF). When considering all tomographic terms, our uncertainty range on the structure growth parameter $S_8$ is enhanced by $sim 45$% (almost twice better) when combining 1D $M_{rm ap}$ and the $gamma$-2PCF compared to the $gamma$-2PCF alone. We additionally measure the first combined forecasts on the dark energy equation of state $w_0$, finding a factor of three reduction of the statistical error compared to the $gamma$-2PCF alone. This demonstrates that the complementary cosmological information explored by non-Gaussian $M_{rm ap}$ map statistics not only offers the potential to improve the constraints on the recent $sigma_8$ - $Omega_{rm m}$ tension, but also constitutes an avenue to understand the accelerated expansion of our Universe.
We show that it is possible to build effective matter density power spectra in tomographic cosmic shear observations that exhibit the Baryonic Acoustic Oscillations (BAO) features once a nulling transformation has been applied to the data. The precision with which the amplitude and position of these features can be reconstructed is quantified in terms of sky coverage, intrinsic shape noise, median source redshift and number density of sources. BAO detection in Euclid or LSST like wide surveys will be possible with a modest signal-to-noise ratio. It would improve dramatically for slightly deeper surveys.
Weak gravitational lensing analyses are fundamentally limited by the intrinsic, non-Gaussian distribution of galaxy shapes. We explore alternative statistics for samples of ellipticity measurements that are unbiased, efficient, and robust. We take the non-linear mapping of gravitational shear and the effect of noise into account. We then discuss how the distribution of individual galaxy shapes in the observed field of view can be modeled by fitting Fourier modes to the shear pattern directly. We simulated samples of galaxy ellipticities, using both theoretical distributions and real data for ellipticities and noise. We determined the possible bias $Delta e$, the efficiency $eta$ and the robustness of the least absolute deviations, the biweight, and the convex hull peeling estimators, compared to the canonical weighted mean. Using these statistics for regression, we have shown the applicability of direct Fourier mode fitting. These estimators can be unbiased in the absence of noise, and decrease noise bias by more than $sim 30%$. The convex hull peeling estimator distribution is centered around the underlying shear, and its bias least affected by noise. The least absolute deviations estimator to be the most efficient estimator in almost all cases, except in the Gaussian case, where its still competitive ($0.83<eta <5.1$) and therefore robust. These results hold when fitting Fourier modes, where amplitudes of variation in ellipticity are determined to the order of $10^{-3}$. The peak of the ellipticity distribution is a direct tracer of the underlying shear and unaffected by noise, and we have shown that estimators that are sensitive to a central cusp perform more efficiently, potentially reducing uncertainties by more than $50%$ and significantly decreasing noise bias.
Recent cosmic shear studies have reported discrepancies of up to $1sigma$ on the parameter ${S_{8}=sigma_{8}sqrt{Omega_{rm m}/0.3}}$ between the analysis of shear power spectra and two-point correlation functions, derived from the same shear catalogs. It is not a priori clear whether the measured discrepancies are consistent with statistical fluctuations. In this paper, we investigate this issue in the context of the forthcoming analyses from the third year data of the Dark Energy Survey (DES-Y3). We analyze DES-Y3 mock catalogs from Gaussian simulations with a fast and accurate importance sampling pipeline. We show that the methodology for determining matching scale cuts in harmonic and real space is the key factor that contributes to the scatter between constraints derived from the two statistics. We compare the published scales cuts of the KiDS, Subaru-HSC and DES surveys, and find that the correlation coefficients of posterior means range from over 80% for our proposed cuts, down to 10% for cuts used in the literature. We then study the interaction between scale cuts and systematic uncertainties arising from multiple sources: non-linear power spectrum, baryonic feedback, intrinsic alignments, uncertainties in the point-spread function, and redshift distributions. We find that, given DES-Y3 characteristics and proposed cuts, these uncertainties affect the two statistics similarly; the differential biases are below a third of the statistical uncertainty, with the largest biases arising from intrinsic alignment and baryonic feedback. While this work is aimed at DES-Y3, the tools developed can be applied to Stage-IV surveys where statistical errors will be much smaller.
One of the most pernicious theoretical systematics facing upcoming gravitational lensing surveys is the uncertainty introduced by the effects of baryons on the power spectrum of the convergence field. One method that has been proposed to account for these effects is to allow several additional parameters (that characterize dark matter halos) to vary and to fit lensing data to these halo parameters concurrently with the standard set of cosmological parameters. We test this method. In particular, we use this technique to model convergence power spectrum predictions from a set of cosmological simulations. We estimate biases in dark energy equation of state parameters that would be incurred if one were to fit the spectra predicted by the simulations either with no model for baryons, or with the proposed method. We show that neglecting baryonic effect leads to biases in dark energy parameters that are several times the statistical errors for a survey like the Dark Energy Survey. The proposed method to correct for baryonic effects renders the residual biases in dark energy equation of state parameters smaller than the statistical errors. These results suggest that this mitigation method may be applied to analyze convergence spectra from a survey like the Dark Energy Survey. For significantly larger surveys, such as will be carried out by the Large Synoptic Survey Telescope, the biases introduced by baryonic effects are much more significant. We show that this mitigation technique significantly reduces the biases for such larger surveys, but that a more effective mitigation strategy will need to be developed in order ensure that the residual biases in these surveys fall below the statistical errors.
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