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Register a new userCluster richness-mass calibration with cosmic microwave background lensing
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J. E. Geach
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Identifying galaxy clusters through overdensities of galaxies in photometric surveys is the oldest and arguably the most economic and mass-sensitive detection method, compared to X-ray and Sunyaev-Zeldovich Effect surveys that detect the hot intracluster medium. However, a perennial problem has been the mapping of optical richness measurements on to total cluster mass. Emitted at a conformal distance of 14 Gpc, the cosmic microwave background acts as a backlight to all intervening mass in the Universe, and therefore has been gravitationally lensed. Here we present a calibration of cluster optical richness at the 10 per cent level by measuring the average cosmic microwave background lensing convergence measured by Planck towards the positions of large numbers of optically-selected clusters, detecting the deflection of photons by haloes of total mass of the order 10**14 solar masses. Although mainly aimed at the study of larger-scale structures, the Planck lensing reconstruction can yield nearly unbiased results for stacked clusters on arcminute scales. The lensing convergence only depends on the redshift integral of the fractional overdensity of matter, so this approach offers a clean measure of cluster mass over most of cosmic history, largely independent of baryon physics.
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Next-generation cosmic microwave background (CMB) experiments will have lower noise and therefore increased sensitivity, enabling improved constraints on fundamental physics parameters such as the sum of neutrino masses and the tensor-to-scalar ratio r. Achieving competitive constraints on these parameters requires high signal-to-noise extraction of the projected gravitational potential from the CMB maps. Standard methods for reconstructing the lensing potential employ the quadratic estimator (QE). However, the QE performs suboptimally at the low noise levels expected in upcoming experiments. Other methods, like maximum likelihood estimators (MLE), are under active development. In this work, we demonstrate reconstruction of the CMB lensing potential with deep convolutional neural networks (CNN) - ie, a ResUNet. The network is trained and tested on simulated data, and otherwise has no physical parametrization related to the physical processes of the CMB and gravitational lensing. We show that, over a wide range of angular scales, ResUNets recover the input gravitational potential with a higher signal-to-noise ratio than the QE method, reaching levels comparable to analytic approximations of MLE methods. We demonstrate that the network outputs quantifiably different lensing maps when given input CMB maps generated with different cosmologies. We also show we can use the reconstructed lensing map for cosmological parameter estimation. This application of CNN provides a few innovations at the intersection of cosmology and machine learning. First, while training and regressing on images, we predict a continuous-variable field rather than discrete classes. Second, we are able to establish uncertainty measures for the network output that are analogous to standard methods. We expect this approach to excel in capturing hard-to-model non-Gaussian astrophysical foreground and noise contributions.
We reconstruct the gravitational lensing convergence signal from Cosmic Microwave Background (CMB) polarization data taken by the POLARBEAR experiment and cross-correlate it with Cosmic Infrared Background (CIB) maps from the Herschel satellite. From the cross-spectra, we obtain evidence for gravitational lensing of the CMB polarization at a statistical significance of 4.0$sigma$ and evidence for the presence of a lensing $B$-mode signal at a significance of 2.3$sigma$. We demonstrate that our results are not biased by instrumental and astrophysical systematic errors by performing null-tests, checks with simulated and real data, and analytical calculations. This measurement of polarization lensing, made via the robust cross-correlation channel, not only reinforces POLARBEAR auto-correlation measurements, but also represents one of the early steps towards establishing CMB polarization lensing as a powerful new probe of cosmology and astrophysics.
We use galaxy dynamical information to calibrate the richness-mass scaling relation of a sample of 428 galaxy clusters that are members of the CODEX sample with redshifts up to z~0.7. These clusters were X-ray selected using the ROSAT All-Sky Survey (RASS), cross-matched to associated systems in the redMaPPer catalog from the Sloan Digital Sky Survey. The spectroscopic sample we analyze was obtained in the SPIDERS program and contains ~7800 red member galaxies. Adopting NFW mass and galaxy density profiles and a broad range of orbital anisotropy profiles, we use the Jeans equation to calculate halo masses. Modeling the scaling relation as $lambda propto text{A}_{lambda} {M_{text{200c}}}^{text{B}_{lambda}} ({1+z})^{gamma_{lambda}}$, we find the parameter constraints $text{A}_{lambda}=38.6^{+3.1}_{-4.1}pm3.9$, $text{B}_{lambda}=0.99^{+0.06}_{-0.07}pm0.04$, and $gamma_{lambda}=-1.13^{+0.32}_{-0.34}pm0.49$. We find good agreement with previously published mass trends with the exception of those from stacked weak lensing analyses. We note that although the lensing analyses failed to account for the Eddington bias, this is not enough to explain the differences. We suggest that differences in the levels of contamination between pure redMaPPer and RASS+redMaPPer samples could well contribute to these differences. The redshift trend we measure is more negative than but statistically consistent with previous results. We suggest that our measured redshift trend reflects a change in the cluster galaxy red sequence fraction with redshift, noting that the trend we measure is consistent with but somewhat stronger than an independently measured redshift trend in the red sequence fraction. We also examine the impact of a plausible model of correlated scatter in X-ray luminosity and optical richness, showing it has negligible impact on our results.
We aim to present a tutorial on the detection, parameter estimation and statistical analysis of compact sources (far galaxies, galaxy clusters and Galactic dense emission regions) in cosmic microwave background observations. The topic is of great relevance for current and future cosmic microwave background missions because the presence of compact sources in the data introduces very significant biases in the determination of the cosmological parameters that determine the energy contain, origin and evolution of the universe and because compact sources themselves provide us with important information about the large scale structure of the universe.
Gravitational lensing due to the large-scale distribution of matter in the cosmos distorts the primordial Cosmic Microwave Background (CMB) and thereby induces new, small-scale $B$-mode polarization. This signal carries detailed information about the distribution of all the gravitating matter between the observer and CMB last scattering surface. We report the first direct evidence for polarization lensing based on purely CMB information, from using the four-point correlations of even- and odd-parity $E$- and $B$-mode polarization mapped over $sim30$ square degrees of the sky measured by the POLARBEAR experiment. These data were analyzed using a blind analysis framework and checked for spurious systematic contamination using null tests and simulations. Evidence for the signal of polarization lensing and lensing $B$-modes is found at 4.2$sigma$ (stat.+sys.) significance. The amplitude of matter fluctuations is measured with a precision of $27%$, and is found to be consistent with the Lambda Cold Dark Matter ($Lambda$CDM) cosmological model. This measurement demonstrates a new technique, capable of mapping all gravitating matter in the Universe, sensitive to the sum of neutrino masses, and essential for cleaning the lensing $B$-mode signal in searches for primordial gravitational waves.
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