No Arabic abstract
Measuring cosmic shear in wide-field imaging surveys requires accurate knowledge of the redshift distribution of all sources. The clustering-redshift technique exploits the angular cross-correlation of a target galaxy sample with unknown redshifts and a reference sample with known redshifts, and is an attractive alternative to colour-based methods of redshift calibration. We test the performance of such clustering redshift measurements using mock catalogues that resemble the Kilo-Degree Survey (KiDS). These mocks are created from the MICE simulation and closely mimic the properties of the KiDS source sample and the overlapping spectroscopic reference samples. We quantify the performance of the clustering redshifts by comparing the cross-correlation results with the true redshift distributions in each of the five KiDS photometric redshift bins. Such a comparison to an informative model is necessary due to the incompleteness of the reference samples at high redshifts. Clustering mean redshifts are unbiased at $|Delta z|<0.006$ under these conditions. The redshift evolution of the galaxy bias can be reliably mitigated at this level of precision using auto-correlation measurements and self-consistency relations, and will not become a dominant source of systematic error until the arrival of Stage-IV cosmic shear surveys. Using redshift distributions from a direct colour-based estimate instead of the true redshift distributions as a model for comparison with the clustering redshifts increases the biases in the mean to up to $|Delta z|sim0.04$. This indicates that the interpretation of clustering redshifts in real-world applications will require more sophisticated (parameterised) models of the redshift distribution in the future. If such better models are available, the clustering-redshift technique promises to be a highly complementary alternative to other methods of redshift calibration.
We present the tomographic cross-correlation between galaxy lensing measured in the Kilo Degree Survey (KiDS-450) with overlapping lensing measurements of the cosmic microwave background (CMB), as detected by Planck 2015. We compare our joint probe measurement to the theoretical expectation for a flat $Lambda$CDM cosmology, assuming the best-fitting cosmological parameters from the KiDS-450 cosmic shear and Planck CMB analyses. We find that our results are consistent within $1sigma$ with the KiDS-450 cosmology, with an amplitude re-scaling parameter $A_{rm KiDS} = 0.86 pm 0.19$. Adopting a Planck cosmology, we find our results are consistent within $2sigma$, with $A_{it Planck} = 0.68 pm 0.15$. We show that the agreement is improved in both cases when the contamination to the signal by intrinsic galaxy alignments is accounted for, increasing $A$ by $sim 0.1$. This is the first tomographic analysis of the galaxy lensing -- CMB lensing cross-correlation signal, and is based on five photometric redshift bins. We use this measurement as an independent validation of the multiplicative shear calibration and of the calibrated source redshift distribution at high redshifts. We find that constraints on these two quantities are strongly correlated when obtained from this technique, which should therefore not be considered as a stand-alone competitive calibration tool.
Analyzes of next-generation galaxy data require accurate treatment of systematic effects such as the bias between observed galaxies and the underlying matter density field. However, proposed models of the phenomenon are either numerically expensive or too inaccurate to achieve unbiased inferences of cosmological parameters even at mildly-nonlinear scales of the data. As an alternative to constructing accurate galaxy bias models, requiring understanding galaxy formation, we propose to construct likelihood distributions for Bayesian forward modeling approaches that are insensitive to linear, scale-dependent bias and provide robustness against model misspecification. We use maximum entropy arguments to construct likelihood distributions designed to account only for correlations between data and inferred quantities. By design these correlations are insensitive to linear galaxy biasing relations, providing the desired robustness. The method is implemented and tested within a Markov Chain Monte Carlo approach. The method is assessed using a halo mock catalog based on standard full, cosmological, N-body simulations. We obtain unbiased and tight constraints on cosmological parameters exploiting only linear cross-correlation rates for $kle 0.10$ Mpc/h. Tests for halos of masses ~10$^{12}$ M$_odot$ to ~10$^{13}$ M$_odot$ indicate that it is possible to ignore all details of the linear, scale dependent, bias function while obtaining robust constraints on cosmology. Our results provide a promising path forward to analyzes of galaxy surveys without the requirement of having to accurately model the details of galaxy biasing but by designing robust likelihoods for the inference.
We demonstrate that observations lacking reliable redshift information, such as photometric and radio continuum surveys, can produce robust measurements of cosmological parameters when empowered by clustering-based redshift estimation. This method infers the redshift distribution based on the spatial clustering of sources, using cross-correlation with a reference dataset with known redshifts. Applying this method to the existing SDSS photometric galaxies, and projecting to future radio continuum surveys, we show that sources can be efficiently divided into several redshift bins, increasing their ability to constrain cosmological parameters. We forecast constraints on the dark-energy equation-of-state and on local non-gaussianity parameters. We explore several pertinent issues, including the tradeoff between including more sources versus minimizing the overlap between bins, the shot-noise limitations on binning, and the predicted performance of the method at high redshifts. Remarkably, we find that, once this technique is implemented, constraints on dynamical dark energy from the SDSS imaging catalog can be competitive with, or better than, those from the spectroscopic BOSS survey and even future planned experiments. Further, constraints on primordial non-Gaussianity from future large-sky radio-continuum surveys can outperform those from the Planck CMB experiment, and rival those from future spectroscopic galaxy surveys. The application of this method thus holds tremendous promise for cosmology.
We use the cosmo-OWLS suite of cosmological hydrodynamical simulations, which includes different galactic feedback models, to predict the cross-correlation signal between weak gravitational lensing and the thermal Sunyaev-Zeldovich (tSZ) $y$-parameter. The predictions are compared to the recent detection reported by van Waerbeke and collaborators. The simulations reproduce the weak lensing-tSZ cross-correlation, $xi_{ykappa}(theta)$, well. The uncertainty arising from different possible feedback models appears to be important on small scales only ($theta lesssim 10$ arcmin), while the amplitude of the correlation on all scales is sensitive to cosmological parameters that control the growth rate of structure (such as $sigma_8$, $Omega_m$ and $Omega_b$). This study confirms our previous claim (in Ma et al.) that a significant proportion of the signal originates from the diffuse gas component in low-mass ($M_{rm{halo}} lesssim 10^{14} M_{odot}$) clusters as well as from the region beyond the virial radius. We estimate that approximately 20$%$ of the detected signal comes from low-mass clusters, which corresponds to about 30$%$ of the baryon density of the Universe. The simulations also suggest that more than half of the baryons in the Universe are in the form of diffuse gas outside halos ($gtrsim 5$ times the virial radius) which is not hot or dense enough to produce a significant tSZ signal or be observed by X-ray experiments. Finally, we show that future high-resolution tSZ-lensing cross-correlation observations will serve as a powerful tool for discriminating between different galactic feedback models.
In this paper, we investigate the cosmic anisotropy from the SN-Q sample, consisting of the Pantheon sample and quasars, by employing the hemisphere comparison (HC) method and the dipole fitting (DF) method. Compared to the Pantheon sample, the new sample has a larger redshift range, a more homogeneous distribution, and a larger sample size. For the HC method, we find that the maximum anisotropy level is $AL_{max}=0.142pm0.026$ in the direction ($l$, $b$) = $({316.08^{circ}}^{+27.41}_{-129.48}$, ${4.53^{circ}}^{+26.29}_{-64.06})$. The magnitude of anisotropy is $A$ = ($-$8.46 $^{+4.34}_{-5.51}$)$times$$10^{-4}$ and the corresponding preferred direction points toward $(l$, $b)$ = ($29.31^{circ}$$^{+30.59}_{-30.54}$, $71.40^{circ}$$^{+9.79}_{-9.72}$) for the quasar sample from the DF method. The combined SN and quasar sample is consistent with the isotropy hypothesis. The distribution of the dataset might impact the preferred direction from the dipole results. The result is weakly dependent on the redshift from the redshift tomography analysis. There is no evidence of cosmic anisotropy in the SN-Q sample. Though some results obtained from the quasar sample are not consistent with the standard cosmological model, we still do not find any distinct evidence of cosmic anisotropy in the SN-Q sample.