We present C ii observations of 20 strongly lensed dusty star-forming galaxies at 2.1 < z < 5.7 using Atacama Pathfinder EXperiment and Herschel. The sources were selected on their 1.4 mm flux (S
1.4 ...mm > 20 mJy) from the South Pole Telescope (SPT) survey, with far-infrared (FIR) luminosities determined from extensive photometric data. The C ii line is robustly detected in 17 sources, all but one being spectrally resolved. 11 out of 20 sources observed in C ii also have low-J CO detections from Australia Telescope Compact Array. A comparison with mid- and high-J CO lines from Atacama Large Millimeter/submillimeter Array reveals consistent C ii and CO velocity profiles, suggesting that there is little differential lensing between these species. The C ii, low-J CO and FIR data allow us to constrain the properties of the interstellar medium. We find C ii to CO(1–0) luminosity ratios in the SPT sample of 5200 ± 1800, with significantly less scatter than in other samples. This line ratio can be best described by a medium of C ii and CO emitting gas with a higher C ii than CO excitation temperature, high CO optical depth τCO(1–0) ≫ 1, and low to moderate C ii optical depth
$\tau _{{\rm C\,\small {II}}}$
≲ 1. The geometric structure of photodissociation regions allows for such conditions.
We present a measurement of the cosmic microwave background (CMB) temperature power spectrum using data from the recently completed South Pole Telescope Sunyaev-Zel'dovich (SPT-SZ) survey. We report ...CMB temperature anisotropy power over the multipole range 650 < l < 3000. We fit the SPT bandpowers, combined with the 7 yr Wilkinson Microwave Anisotropy Probe (WMAP7) data, with a six-parameter ACDM cosmological model and find that the two datasets are consistent and well fit by the model. Adding SPT measurements significantly improves ACDM parameter constraints; in particular, the constraint on theta sub(s) tightens by a factor of 2.7. The impact of gravitational lensing is detected at 8.1sigma, the most significant detection to date. These new constraints on n sub(s) and r have significant implications for our understanding of inflation, which we discuss in the context of selected single-field inflation models.
We present a new application of deep learning to infer the masses of galaxy clusters directly from images of the microwave sky. Effectively, this is a novel approach to determining the scaling ...relation between a cluster's Sunyaev-Zel'dovich (SZ) effect signal and mass. The deep-learning algorithm used is mResUNet, which is a modified feed-forward deep-learning algorithm that broadly combines residual learning, convolution layers with different dilation rates, image regression activation, and a U-Net framework. We train and test the deep-learning model using simulated images of the microwave sky that include signals from the cosmic microwave background, dusty and radio galaxies, and instrumental noise as well as the cluster's own SZ signal. The simulated cluster sample covers the mass range 1 × 1014 M < M200c < 8 × 1014 M at z = 0.7. The trained model estimates the cluster masses with a 1 uncertainty ΔM/M ≤ 0.2, consistent with the input scatter on the SZ signal of 20%. We verify that the model works for realistic SZ profiles even when trained on azimuthally symmetric SZ profiles by using the Magneticum hydrodynamical simulations.
ABSTRACT
Empirical estimates of the band power covariance matrix are commonly used in cosmic microwave background (CMB) power spectrum analyses. While this approach easily captures correlations in ...the data, noise in the resulting covariance estimate can systematically bias the parameter fitting. Conditioning the estimated covariance matrix, by applying prior information on the shape of the eigenvectors, can reduce these biases and ensure the recovery of robust parameter constraints. In this work, we use simulations to benchmark the performance of four different conditioning schemes, motivated by contemporary CMB analyses. The simulated surveys measure the TT, TE, and EE power spectra over the angular multipole range 300 ≤ ℓ ≤ 3500 in Δℓ = 50 wide bins, for temperature map-noise levels of 10, 6.4, and $2\, \mu$K arcmin. We divide the survey data into Nreal = 30, 50, or 100 uniform subsets. We show the results of different conditioning schemes on the errors in the covariance estimate, and how these uncertainties on the covariance matrix propagate to the best-fitting parameters and parameter uncertainties. The most significant effect we find is an additional scatter in the best-fitting point, beyond what is expected from the data likelihood. For a minimal conditioning strategy, Nreal = 30, and a temperature map-noise level of 10$\, \mu$K arcmin, we find the uncertainty on the recovered best-fitting parameter to be ×1.3 larger than the apparent posterior width from the likelihood (×1.2 larger than the uncertainty when the true covariance is used). Stronger priors on the covariance matrix reduce the misestimation of parameter uncertainties to $\lt 1{{\ \rm per\ cent}}$. As expected, empirical estimates perform better with higher Nreal, ameliorating the adverse effects on parameter constraints.
Abstract
We present a new application of deep learning to reconstruct the cosmic microwave background (CMB) temperature maps from images of the microwave sky and to use these reconstructed maps to ...estimate the masses of galaxy clusters. We use a feed-forward deep-learning network, mResUNet, for both steps of the analysis. The first deep-learning model, mResUNet-I, is trained to reconstruct foreground and noise-suppressed CMB maps from a set of simulated images of the microwave sky that include signals from the CMB, astrophysical foregrounds like dusty and radio galaxies, instrumental noise as well as the cluster’s own thermal Sunyaev–Zel’dovich signal. The second deep-learning model, mResUNet-II, is trained to estimate cluster masses from the gravitational-lensing signature in the reconstructed foreground and noise-suppressed CMB maps. For SPTpol-like noise levels, the trained mResUNet-II model recovers the mass for 10
4
galaxy cluster samples with a 1
σ
uncertainty
Δ
M
200
c
est
/
M
200
c
est
=
0.108 and 0.016 for input cluster mass
M
200
c
true
=
10
14
M
⊙
and 8 × 10
14
M
⊙
, respectively. We also test for potential bias on recovered masses, finding that for a set of 10
5
clusters the estimator recovers
M
200
c
est
=
2.02
×
10
14
M
⊙
, consistent with the input at 1% level. The 2
σ
upper limit on potential bias is at 3.5% level.
We study the stellar, brightest cluster galaxy (BCG) and intracluster medium (ICM) masses of 14 South Pole Telescope (SPT) selected galaxy clusters with median redshift z = 0.9 and mass M
...500 = 6 × 1014 M⊙. We estimate stellar masses for each cluster and BCG using six photometric bands, the ICM mass using X-ray observations and the virial masses using the SPT Sunyaev–Zel'dovich effect signature. At z = 0.9, the BCG mass
$M_{\star }^{\mathrm{BCG}}$
constitutes 0.12 ± 0.01 per cent of the halo mass for a 6 × 1014 M⊙ cluster, and this fraction falls as
$M_{500}^{-0.58\pm 0.07}$
. The cluster stellar mass function has a characteristic mass M
0 = 1011.0 ± 0.1 M⊙, and the number of galaxies per unit mass in clusters is larger than in the field by a factor of 1.65 ± 0.20. We combine our SPT sample with previously published samples at low redshift and correct to a common initial mass function and for systematic virial mass differences. We then explore mass and redshift trends in the stellar fraction f
⋆, the ICM fraction f
ICM, the collapsed baryon fraction f
c and the baryon fraction f
b. At a pivot mass of 6 × 1014 M⊙ and redshift z = 0.9, the characteristic values are f
⋆ = 1.1 ± 0.1 per cent, f
ICM = 9.6 ± 0.5 per cent, f
c = 10.7 ± 1.1 per cent and f
b = 10.7 ± 0.6 per cent. These fractions all vary with cluster mass at high significance, with higher mass clusters having lower f
⋆ and f
c and higher f
ICM and f
b. When accounting for a 15 per cent systematic virial mass uncertainty, there is no statistically significant redshift trend at fixed mass. Our results support the scenario where clusters grow through accretion from subclusters (higher f
⋆, lower f
ICM) and the field (lower f
⋆, higher f
ICM), balancing to keep f
⋆ and f
ICM approximately constant since z ∼ 0.9.
We present component-separated maps of the primary cosmic microwave background/kinematic Sunyaev–Zel’dovich (SZ) amplitude and the thermal SZ Compton-y parameter, created using data from the South ...Pole Telescope (SPT) and the Planck satellite. These maps, which cover the ∼2500 deg2 of the southern sky imaged by the SPT-SZ survey, represent a significant improvement over previous such products available in this region by virtue of their higher angular resolution (1.′25 for our highest-resolution Compton-y maps) and lower noise at small angular scales. In this work we detail the construction of these maps using linear combination techniques, including our method for limiting the correlation of our lowest-noise Compton-y map products with the cosmic infrared background. We perform a range of validation tests on these data products to test our sky modeling and combination algorithms, and we find good performance in all of these tests. Recognizing the potential utility of these data products for a wide range of astrophysical and cosmological analyses, including studies of the gas properties of galaxies, groups, and clusters, we make these products publicly available at http://pole.uchicago.edu/public/data/sptsz_ymap and on the NASA/LAMBDA website.
We present the first three-frequency South Pole Telescope (SPT) cosmic microwave background (CMB) power spectra. The band powers presented here cover angular scales 2000 < l < 9400 in frequency bands ...centered at 95, 150, and 220 GHz. At these frequencies and angular scales, a combination of the primary CMB anisotropy, thermal and kinetic Sunyaev-Zel'dovich (SZ) effects, radio galaxies, and cosmic infrared background (CIB) contributes to the signal. We combine Planck/HFI and SPT data at 220 GHz to constrain the amplitude and shape of the CIB power spectrum and find strong evidence for nonlinear clustering. We explore the SZ results using a variety of cosmological models for the CMB and CIB anisotropies and find them to be robust with one exception: allowing for spatial correlations between the thermal SZ effect and CIB significantly degrades the SZ constraints. Neglecting this potential correlation, we find the thermal SZ power at 150 GHz and l = 3000 to be 3.65 + or - 0.69 mu K super(2), and set an upper limit on the kinetic SZ power to be less than 2.8 mu K super(2) at 95% confidence. When a correlation between the thermal SZ and CIB is allowed, we constrain a linear combination of thermal and kinetic SZ power: D super(tSZ) sub(3000) + 0.5D sub(3000) super(kSZ) = 4.60 + or - 0.63 mu K super(2), consistent with earlier measurements. We use the measured thermal SZ power and an analytic, thermal SZ model calibrated with simulations to determine sigma sub(8) = 0.807 + or - 0.016. Modeling uncertainties involving the astrophysics of the intracluster medium rather than the statistical uncertainty in the measured band powers are the dominant source of uncertainty on sigma sub(8). We also place an upper limit on the kinetic SZ power produced by patchy reionization; a companion paper uses these limits to constrain the reionization history of the universe.
Abstract
We present an HST/Advanced Camera for Surveys (ACS) weak gravitational lensing analysis of 13 massive high-redshift (zmedian = 0.88) galaxy clusters discovered in the South Pole Telescope ...(SPT) Sunyaev–Zel'dovich Survey. This study is part of a larger campaign that aims to robustly calibrate mass–observable scaling relations over a wide range in redshift to enable improved cosmological constraints from the SPT cluster sample. We introduce new strategies to ensure that systematics in the lensing analysis do not degrade constraints on cluster scaling relations significantly. First, we efficiently remove cluster members from the source sample by selecting very blue galaxies in V − I colour. Our estimate of the source redshift distribution is based on Cosmic Assembly Near-infrared Deep Extragalactic Legacy Survey (CANDELS) data, where we carefully mimic the source selection criteria of the cluster fields. We apply a statistical correction for systematic photometric redshift errors as derived from Hubble Ultra Deep Field data and verified through spatial cross-correlations. We account for the impact of lensing magnification on the source redshift distribution, finding that this is particularly relevant for shallower surveys. Finally, we account for biases in the mass modelling caused by miscentring and uncertainties in the concentration–mass relation using simulations. In combination with temperature estimates from Chandra
we constrain the normalization of the mass–temperature scaling relation ln (E(z)M500c/1014 M⊙) = A + 1.5ln (kT/7.2 keV) to $A=1.81^{+0.24}_{-0.14}(\mathrm{stat.})\,{\pm }\,0.09(\mathrm{sys.})$, consistent with self-similar redshift evolution when compared to lower redshift samples. Additionally, the lensing data constrain the average concentration of the clusters to $c_\mathrm{200c}=5.6^{+3.7}_{-1.8}$.
Uncertainty in the mass-observable scaling relations is currently the limiting factor for galaxy cluster based cosmology. Weak gravitational lensing can provide a direct mass calibration and reduce ...the mass uncertainty. We present new ground-based weak lensing observations of 19 South Pole Telescope (SPT) selected clusters and combine them with previously reported space-based observations of 13 galaxy clusters to constrain the cluster mass scaling relations with the Sunyaev-Zel'dovich effect (SZE), the cluster gas mass $M_\mathrm{gas}$, and $Y_\mathrm{X}$, the product of $M_\mathrm{gas}$ and X-ray temperature. We extend a previously used framework for the analysis of scaling relations and cosmological constraints obtained from SPT-selected clusters to make use of weak lensing information. Here, we introduce a new approach to estimate the effective average redshift distribution of background galaxies and quantify a number of systematic errors affecting the weak lensing modelling. These errors include a calibration of the bias incurred by fitting a Navarro-Frenk-White profile to the reduced shear using $N$-body simulations. We blind the analysis to avoid confirmation bias. We are able to limit the systematic uncertainties to 6.4% in cluster mass (68% confidence). Our constraints on the mass-X-ray observable scaling relations parameters are consistent with those obtained by earlier studies, and our constraints for the mass-SZE scaling relation are consistent with the the simulation-based prior used in the most recent SPT-SZ cosmology analysis. We can now replace the external mass calibration priors used in previous SPT-SZ cosmology studies with a direct, internal calibration obtained on the same clusters.
![The nature of the [C ii] em...](http://api.summon.serialssolutions.com/2.0.0/image/issn/XR4PS5YY4K/0035-8711_1365-8711_1365-2966/small "The nature of the [C ii] emission in dusty star-forming galaxies from the SPT survey")
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