We examine cosmological constraints from high precision weak lensing surveys including super-sample covariance (SSC) due to the finite survey volume. Specifically, we focus on the contribution of {\it beat coupling} in the intrinsic alignments as a part of full cosmic shear signal under flat sky approximation. The SSC-effect grows by going to lower redshift bin and indicates considerable footprint on the intermediate and high multipoles for cumulative signal to noise ratio (SNR). The SNR is reduced by $\approx 10\%$ as a consequence of including the intrinsic alignments super-sample covariance, for the full cosmic shear signal, depending on the amplitude of intrinsic alignments, the ellipticity dispersion and the survey redshift ranges, while the contribution of photometric redshift error can be ignored in the cumulative signal to noise ratio. Using the Fisher-matrix formalism, we find that the impact of large modes beyond the volume of the surveys on the small modes alters the intrinsic alignments. However, corresponding impact on the cosmological parameters estimation is marginal compared to that of for gravitational weak lensing, particularly, when all available redshift bins are considered. Our results also demonstrate that, including SSC-effect on the intrinsic alignments in the analytical covariance matrix of full cosmic shear leads to increase marginally the confidence interval for $σ_8$ by $\approx 10\%$ for a sample with almost high intrinsic alignments amplitude.
In this paper we show how intrinsic alignments can be incorporated consistently in the formalism of 3d weak lensing. We use two different descriptions of the intrinsic galaxy ellipticities, the so-called linear and quadratic model, respectively. For both models we derive the covariance matrix of the intrinsic alignment signal (II-alignments) and GI-alignments (the cross correlation of intrinsic and lensing induced ellipticities). Evaluating the covariance matrices for the linear model numerically and comparing the results to the cosmic shear signal we find that for a low redshift survey the to…
The thermal Sunyaev-Zel'dovich (tSZ) effect signal is widely recognized as a robust mass proxy of galaxy clusters with small intrinsic scatter. However, recent observational calibration of the tSZ scaling relation using weak lensing (WL) mass exhibits considerably larger scatter than the intrinsic scatter predicted from numerical simulations. This raises a question as to whether we can realize the full statistical power of ongoing and upcoming tSZ-WL observations of galaxy clusters. In this work, we investigate the origin of observed scatter in the tSZ-WL scaling relation, using mock maps of g…
We introduce an intrinsic Lyα emission line profile reconstruction method for high-$z$ quasars (QSOs). This approach utilises a covariance matrix of emission line properties obtained from a large, moderate-$z$ ($2 \leq z \leq 2.5$), high signal to noise (S/N > 15) sample of BOSS QSOs. For each QSO, we complete a Monte Carlo Markov Chain fitting of the continuum and emission line properties and perform a visual quality assessment to construct a large database of robustly fit spectra. With this dataset, we construct a covariance matrix to describe the correlations between the high ionisation emi…
Modes with wavelengths larger than the survey window can have significant impact on the covariance within the survey window. The supersample covariance has been recognized as an important source of covariance for the power spectrum on small scales, and it can potentially be important for the bispectrum covariance as well. In this paper, using the response function formalism, we model the supersample covariance contributions to the bispectrum covariance and the cross covariance between the power spectrum and the bispectrum. The supersample covariances due to the long wavelength density and tida…
The observable universe contains density perturbations on scales larger than any finite volume survey. Perturbations on scales larger than a survey can measure degrade its power to constrain cosmological parameters. The dependence of survey observables such as the weak lensing power spectrum on these long-wavelength modes results in super-sample covariance. Accurately forecasting parameter constraints for future surveys requires accurately accounting for the super-sample effects. If super-sample covariance is in fact a major component of the survey error budget, it may be necessary to investig…
We give an analytical interpretation of how subsample-based internal covariance estimators lead to biased estimates of the covariance, due to underestimating the super-sample covariance (SSC). This includes the jackknife and bootstrap methods as estimators for the full survey area, and subsampling as an estimator of the covariance of subsamples. The limitations of the jackknife covariance have been previously presented in the literature because it is effectively a rescaling of the covariance of the subsample area. However we point out that subsampling is also biased, but for a different reason…
We provide a simple, unified approach to describing the impact of super-sample covariance, or beat coupling, on power spectrum estimation in a finite-volume survey. For a wide range of survey volumes, the sample variance that arises from modes that are larger than the survey dominates the covariance of power spectrum estimators for modes much smaller than the survey. The deeply nonlinear version of this effect is known as halo sample variance. We show that all variants are unified by the matter trispectrum of squeezed configurations and that such configurations obey a consistency relation whic…
We present correction terms that allow delete-one Jackknife and Bootstrap methods to be used to recover unbiased estimates of the data covariance matrix of the two-point correlation function $ξ\left(\mathbf{r}\right)$. We demonstrate the accuracy and precision of this new method using a large set of 1000 QUIJOTE simulations that each cover a comoving volume of $1\rm{\left[h^{-1}Gpc\right]^3}$. The corrected resampling techniques recover the correct amplitude and structure of the data covariance matrix as represented by its principal components to within $\sim10$\%, the level of error achievabl…
Recent studies have shown that the observed colour distributions of Type Ia SNe (SNIa) are well-described by a combination of distributions from dust and intrinsic colour. Here we present a new forward-modeling fitting method (Dust2Dust) to measure the parent dust and colour distributions, including their dependence on host-galaxy mass. At each fit step, the SNIa selection efficiency is determined from a large simulated sample that is re-weighted to reflect the proposed distributions. We use five separate metrics to constrain the Dust2Dust parameters: distribution of fitted light-curve colour …
The thermal Sunyaev-Zel'dovich (tSZ) effect is a powerful probe of cosmology. The statistical errors in the tSZ power spectrum measurements are dominated by the presence of massive clusters in a survey volume that are easy to identify on individual cluster basis. First, we study the impact of super sample covariance (SSC) on the tSZ power spectrum measurements, and find that the sample variance is dominated by the connected non-Gaussian (cNG) covariance arising mainly from Poisson number fluctuations of massive clusters in the survey volume. Second, we find that removing such individually-dete…
We derive the complete super-sample covariance (SSC) of the matter and weak lensing convergence power spectra using the power spectrum response formalism to accurately describe the coupling of super- to sub-survey modes. The SSC term is completely characterized by the survey window function, the nonlinear matter power spectrum and the full first-order nonlinear power spectrum response function, which describes the response to super-survey density and tidal field perturbations. Generalized separate universe simulations can efficiently measure these responses in the nonlinear regime of structure…
Super-sample covariance (SSC) is an important effect for cosmological analyses that use the deep structure of the cosmic web; it may, however, be nontrivial to include it practically in a pipeline. We solve this difficulty by presenting a formula for the precision (inverse covariance) matrix and show applications to update likelihood or Fisher forecast pipelines. The formula has several advantages in terms of speed, reliability, stability, and ease of implementation. We present an analytical application to show the formal equivalence between three approaches to SSC: (i) at the usual covariance…
Using separate universe simulations, we accurately quantify super-sample covariance (SSC), the typically dominant sampling error for matter power spectrum estimators in a finite volume, which arises from the presence of super survey modes. By quantifying the power spectrum response to a background mode, this approach automatically captures the separate effects of beat coupling in the quasilinear regime, halo sample variance in the nonlinear regime and a new dilation effect which changes scales in the power spectrum coherently across the survey volume, including the baryon acoustic oscillation …
Super-sample covariance (SSC) is the dominant source of statistical error on large scale structure (LSS) observables for both current and future galaxy surveys. In this work, we concentrate on the SSC of cluster counts, also known as sample variance, which is particularly useful for the self-calibration of the cluster observable-mass relation; our approach can similarly be applied to other observables, such as galaxy clustering and lensing shear. We first examined the accuracy of two analytical approximations proposed in the literature for the flat sky limit, finding that they are accurate at …
Gravitational lensing information from the two and higher point statistics of the CMB temperature and polarization fields are intrinsically correlated because they are lensed by the same realization of structure between last scattering and observation. Using an analytic model for lens sample covariance, we show that there is one mode, separately measurable in the lensed CMB power spectra and lensing reconstruction, that carries most of this correlation. Once these measurements become lens sample variance dominated, this mode should provide a useful consistency check between the observables tha…
As galaxy surveys become more precise and push to smaller scales, the need for accurate covariances beyond the classical Gaussian formula becomes more acute. Here, I investigate the analytical implementation and impact of non-Gaussian covariance terms that I previously derived for galaxy clustering. Braiding covariance is such a class of terms and it gets contribution both from in-survey and super-survey modes. I present an approximation for braiding covariance which speeds up the numerical computation. I show that including braiding covariance is a necessary condition for including other non-…
We investigate correlations induced by gravitational lensing on simulated cosmic microwave background data of experiments with an incomplete sky coverage and their effect on inferences from the South Pole Telescope data. These correlations agree well with the theoretical expectations, given by the sum of super-sample and intra-sample lensing terms, with only a typically negligible $\sim$ 5% discrepancy in the amplitude of the super-sample lensing effect. Including these effects we find that lensing constraints are in $3.0σ$ or $2.1σ$ tension between the SPT polarization measurements and Planck…
We reconsider cosmological perturbation theory for multi-component scalars, enforcing covariance in field-space, and ensuring that phyical observations are independent of field re-definitions. We use the formalism to clarify some issues in the literature, and use pseudo-supersymmetry to derive exact expressions for terms of interest.
We explore the covariance of redshift-space matter power spectra after a standard density-field reconstruction. We derive perturbative formula of the covariance at the tree-level order and find that the amplitude of the off-diagonal components from the trispectrum decreases by reconstruction. Using a large set of N-body simulations, we also find the similar reduction of the off-diagonal components of the covariance and thereby the signal-to-noise ratio (S/N) of the post-reconstructed (post-rec) power spectra significantly increases compared to the pre-reconstructed spectra. This indicates that…
We use a suite of $N$-body simulations to study intrinsic alignments (IA) of halo shapes with the surrounding large-scale structure in the $Λ$CDM model. For this purpose, we develop a novel method to measure multipole moments of the three-dimensional power spectrum of the $E$-mode field of halo shapes with the matter/halo distribution, $P_{δE}^{(\ell)}(k)$ (or $P^{(\ell)}_{{\rm h}E}$), and those of the auto-power spectrum of the $E$ mode, $P^{(\ell)}_{EE}(k)$, based on the $E$/$B$-mode decomposition. The IA power spectra have non-vanishing amplitudes over the linear to nonlinear scales, and th…
Photometric galaxy surveys probe the late-time Universe where the density field is highly non-Gaussian. A consequence is the emergence of the super-sample covariance (SSC), a non-Gaussian covariance term that is sensitive to fluctuations on scales larger than the survey window. In this work, we study the impact of the survey geometry on the SSC and, subsequently, on cosmological parameter inference. We devise a fast SSC approximation that accounts for the survey geometry and compare its performance to the common approximation of rescaling the results by the fraction of the sky covered by the s…
We compute the covariance of the galaxy power spectrum multipoles in perturbation theory, including the effects of nonlinear evolution, nonlinear and nonlocal bias, radial redshift-space distortions, arbitrary survey window and shot noise. We rewrite the power spectrum FKP estimator in terms of the usual windowed galaxy fluctuations and the fluctuations in the number of galaxies inside the survey volume. We show that this leads to a stronger super-sample covariance than assumed in the literature and causes a substantial leakage of Gaussian information. We decompose the covariance matrix into s…
