We present maps of the Large and Small Magellanic Clouds from combined South Pole Telescope (SPT) and Planck data. The Planck satellite observes in nine bands, while the SPT data used in this work were taken with the three-band SPT-SZ camera, The SPT-SZ bands correspond closely to three of the nine Planck bands, namely those centered at 1.4, 2.1, and 3.0 mm. The angular resolution of the Planck data ranges from 5 to 10 arcmin, while the SPT resolution ranges from 1.0 to 1.7 arcmin. The combined maps take advantage of the high resolution of the SPT data and the long-timescale stability of the space-based Planck observations to deliver robust brightness measurements on scales from the size of the maps down to similar to 1 arcmin. In each band, we first calibrate and color-correct the SPT data to match the Planck data, then we use noise estimates from each instrument and knowledge of each instrument's beam to make the inverse-variance-weighted combination of the two instruments' data as a function of angular scale. We create maps assuming a range of underlying emission spectra and at a range of final resolutions. We perform several consistency tests on the combined maps and estimate the expected noise in measurements of features in them. We compare maps from this work to those from the Herschel HERITAGE survey, finding general consistency between the data sets. All data products described in this paper are available for download from the NASA Legacy Archive for Microwave Background Data Analysis server.

We study the consistency of 150 GHz data from the South Pole Telescope (SPT) and 143 GHz data from the Planck satellite over the patch of sky covered by the SPT-SZ survey. We first visually compare the maps and find that the residuals appear consistent with noise after accounting for differences in angular resolution and filtering. We then calculate (1) the cross-spectrum between two independent halves of SPT data, (2) the cross-spectrum between two independent halves of Planck data, and (3) the cross-spectrum between SPT and Planck data. We find that the three cross-spectra are well fit (PTE = 0.30) by the null hypothesis in which both experiments have measured the same sky map up to a single free calibration parameter-i.e., we find no evidence for systematic errors in either data set. As a by-product, we improve the precision of the SPT calibration by nearly an order of magnitude, from 2.6% to 0.3% in power. Finally, we compare all three cross-spectra to the full-sky Planck power spectrum and find marginal evidence for differences between the power spectra from the SPT-SZ footprint and the full sky. We model these differences as a power law in spherical harmonic multipole number. The best-fit value of this tilt is consistent among the three cross-spectra in the SPT-SZ footprint, implying that the source of this tilt is a sample variance fluctuation in the SPT-SZ region relative to the full sky. The consistency of cosmological parameters derived from these data sets is discussed in a companion paper.

In this work we introduce a fast Bayesian algorithm designed for detecting compact objects immersed in a diffuse background. A general methodology is presented in terms of formal correctness and optimal use of all the available information in a consistent unified framework, where no distinction is made between point sources (unresolved objects), SZ clusters, single or multi-channel detection. An emphasis is placed on the necessity of a multi-frequency, multi-model detection algorithm in order to achieve optimality. We have chosen to use the Bayes/Laplace probability theory as it grants a fully consistent extension of formal deductive logic to a more general inferential system with optimal inclusion of all ancillary information [Jaynes, 2004]. Nonetheless, probability theory only informs us about the plausibility, a ‘degree-of-belief ’, of a proposition given the data, the model that describes it and all ancillary (prior) information. However, detection or classification is mostly about making educated choices and a wrong decision always carries a cost/loss. Only resorting to ‘Decision Theory’, supported by probability theory, one can take the best decisions in terms of maximum yield at minimal cost. Despite the rigorous and formal approach employed, practical efficiency and applicability have always been kept as primary design goals. We have attempted to select and employ the relevant tools to explore a likelihood form and its manifold symmetries to achieve the very high computational performance required not only by our ‘decision machine’ but mostly to tackle large realistic contemporary cosmological data sets. As an illustration, we successfully applied the methodology to ESA’s (European Space Agency) Planck satellite data [Planck Collaboration et al., 2011d]. This data set is large, complex and typical of the contemporary precision observational cosmology state-of-the-art. Two catalogue products are already released: (i) A point sources catalogue [Planck Collaboration et al., 2011e], (ii) A catalogue of galaxy clusters [Planck Collaboration et al., 2011f]. Many other contributions, in science products, as an estimation device, have recently been issued [Planck et al., 2012; Planck Collaboration et al., 2011g,i, 2012a,b,c]. This new method is called ‘PowellSnakes’ (PwS).

We present a detailed study of the colours of late-type galaxy discs for ten of the EDisCS galaxy clusters with 0.5 less than or similar to z less than or similar to 0.8. Our cluster sample contains 172 spiral galaxies, and our control sample is composed of 96 field disc galaxies. We deconvolved their ground-based V and I images obtained with FORS2 at the VLT with initial spatial resolutions between 0.4 and 0.8 arcsec to achieve a final resolution of 0.1 arcsec with 0.05 arcsec pixels, which is close to the resolution of the ACS at the HST. After removing the central region of each galaxy to avoid pollution by the bulges, we measured the V - I colours of the discs. We find that 50% of cluster spiral galaxies have disc V - I colours redder by more than 1 sigma of the mean colours of their field counterparts. This is well above the 16% expected for a normal distribution centred on the field disc properties. The prominence of galaxies with red discs depends neither on the mass of their parent cluster nor on the distance of the galaxies to the cluster cores. Passive spiral galaxies constitute 20% of our sample. These systems are not abnormally dusty. They are are made of old stars and are located on the cluster red sequences. Another 24% of our sample is composed of galaxies that are still active and star forming, but less so than galaxies with similar morphologies in the field. These galaxies are naturally located in the blue sequence of their parent cluster colour-magnitude diagrams. The reddest of the discs in clusters must have stopped forming stars more than similar to 5 Gyr ago. Some of them are found among infalling galaxies, suggesting preprocessing. Our results confirm that galaxies are able to continue forming stars for some significant period of time after being accreted into clusters, and suggest that star formation can decline on seemingly long (1 to 5 Gyr) timescales.

We measure the cross-correlation between weak lensing of galaxy images and of the cosmic microwave background (CMB). The effects of gravitational lensing on different sources will be correlated if the lensing is caused by the same mass fluctuations. We use galaxy shape measurements from 139 deg(2) of the Dark Energy Survey (DES) Science Verification data and overlapping CMB lensing from the South Pole Telescope (SPT) and Planck. The DES source galaxies have a median redshift of z(med) similar to 0.7, while the CMB lensing kernel is broad and peaks at z similar to 2. The resulting cross-correlation is maximally sensitive to mass fluctuations at z similar to 0.44. Assuming the Planck 2015 best-fitting cosmology, the amplitude of the DESxSPT cross-power is found to be A(SPT) = 0.88 +/- 0.30 and that from DESxPlanck to be A(Planck) = 0.86 +/- 0.39, where A = 1 corresponds to the theoretical prediction. These are consistent with the expected signal and correspond to significances of 2.9 sigma and 2.2 sigma, respectively. We demonstrate that our results are robust to a number of important systematic effects including the shear measurement method, estimator choice, photo-z uncertainty and CMB lensing systematics. We calculate a value of A = 1.08 +/- 0.36 for DESxSPT when we correct the observations with a simple intrinsic alignment model. With three measurements of this cross-correlation now existing in the literature, there is not yet reliable evidence for any deviation from the expected LCDM level of cross-correlation. We provide forecasts for the expected signal-to-noise ratio of the combination of the five-year DES survey and SPT-3G.

Matter near a gravitational lens galaxy or projected along the line of sight (LOS) can affect strong lensing observables by more than contemporary measurement errors. We simulate lens fields with realistic threedimensional mass configurations (self-consistently including voids), and then fit mock lensing observables with increasingly complex lens models to quantify biases and uncertainties associated with different ways of treating the lens environment (ENV) and LOS. We identify the combination of mass, projected offset, and redshift that determines the importance of a perturbing galaxy for lensing. Foreground structures have a stronger effect on the lens potential than background structures, due to nonlinear effects in the foreground and downweighting in the background. There is dramatic variation in the net strength of ENV/LOS effects across different lens fields; modeling fields individually yields stronger priors for H-0 than ray tracing through N-body simulations. Models that ignore mass outside the lens yield poor fits and biased results. Adding external shear can account for tidal stretching from galaxies at redshifts z >= z(lens), but it requires corrections for external convergence and cannot reproduce nonlinear effects from foreground galaxies. Using the tidal approximation is reasonable for most perturbers as long as nonlinear redshift effects are included. Even then, the scatter in H0 is limited by the lens profile degeneracy. Asymmetric image configurations produced by highly elliptical lens galaxies are less sensitive to the lens profile degeneracy, so they offer appealing targets for precision lensing analyses in future surveys like LSST and Euclid.

We present reduced data and data products from the 3D-HST survey, a 248-orbit HST Treasury program. The survey obtained WFC3 G141 grism spectroscopy in four of the five CANDELS fields: AEGIS, COSMOS, GOODS-S, and UDS, along with WFC3 H-140 imaging, parallel ACS G800L spectroscopy, and parallel I-814 imaging. In a previous paper, we presented photometric catalogs in these four fields and in GOODS-N, the fifth CANDELS field. Here we describe and present the WFC3 G141 spectroscopic data, again augmented with data from GO-1600 in GOODS-N (PI: B. Weiner). We developed software to automatically and optimally extract interlaced two-dimensional (2D) and one-dimensional (1D) spectra for all objects in the Skelton et al. (2014) photometric catalogs. The 2D spectra and the multi-band photometry were fit simultaneously to determine redshifts and emission line strengths, taking the morphology of the galaxies explicitly into account. The resulting catalog has redshifts and line strengths (where available) for 22,548 unique objects down to JH(IR) <= 24 (79,609 unique objects down to JH(IR) <= 26). Of these, 5459 galaxies are at z > 1.5 and 9621 are at 0.7 < z < 1.5, where Ha falls in the G141 wavelength coverage. The typical redshift error for JH(IR) <= 24 galaxies is sigma(z) approximate to 0.003 x (1 + z), i.e., one native WFC3 pixel. The 3 sigma limit for emission line fluxes of point sources is 2.1 x 10(-17) erg s(-1) cm(-2). All 2D and 1D spectra, as well as redshifts, line fluxes, and other derived parameters, are publicly available.(18)

We present the initial results from a program aimed at establishing a network of hot DA white dwarfs to serve as spectrophotometric standards for present and future wide-field surveys. These stars span the equatorial zone and are faint enough to be conveniently observed throughout the year with large-aperture telescopes. The spectra of these white dwarfs are analyzed in order to generate a non-local-thermodynamic-equilibrium model atmosphere normalized to Hubble Space Telescope colors, including adjustments for wavelength-dependent interstellar extinction. Once established, this standard star network will serve ground-based observatories in both hemispheres as well as space-based instrumentation from the UV to the near IR. We demonstrate the effectiveness of this concept and show how two different approaches to the problem using somewhat different assumptions produce equivalent results. We discuss the lessons learned and the resulting corrective actions applied to our program.

Asymmetric beams can create significant bias in estimates of the power spectra from cosmic microwave background (CMB) experiments. With the temperature power spectrum many orders of magnitude stronger than the B-mode power spectrum any systematic error that couples the two must be carefully controlled and/or removed. In this thesis, I derive unbiased estimators for the CMB temperature and polarisation power spectra taking into account general beams and scan strategies. I test my correction algorithm on simulations of two temperature-only experiments and demonstrate that it is unbiased. I also develop a map-making algorithm that removes beam asymmetry bias at the map level. I demonstrate its implementation using simulations. I present two new map-making algorithms that create polarisation maps clean of temperature-to-polarisation leakage systematics due to differential gain and pointing between a detector pair. Where a half wave plate is used, I show that the spin-2 systematic due to differential ellipticity can also be removed using my algorithms. The first algorithm is designed to work with scan strategies that have a good range of crossing angles for each map pixel and the second for scan strategies that have a limited range of crossing angles. I demonstrate both algorithms by using simulations of time ordered data with realistic scan strategies and instrumental noise. I investigate the role that a scan strategy can have in mitigating certain common systematics by averaging systematic errors down with many crossing angles. I present approximate analytic forms for the error on the recovered B-mode power spectrum that would result from these systematic errors. I use these analytic predictions to search the parameter space of common satellite scan strategies to identify the features of a scan strategy that have most impact in mitigating systematic effects.

In the last decade, over a million stars were monitored to detect transiting planets. Manual interpretation of potential exoplanet candidates is labour intensive and subject to human error, the results of which are difficult to quantify. Here we present a new method of detecting exoplanet candidates in large planetary search projects that, unlike current methods, uses a neural network. Neural networks, also called 'deep learning' or 'deep nets', are designed to give a computer perception into a specific problem by training it to recognize patterns. Unlike past transit detection algorithms, deep nets learn to recognize planet features instead of relying on hand-coded metrics that humans perceive as the most representative. Our convolutional neural network is capable of detecting Earth-like exoplanets in noisy time series data with a greater accuracy than a least-squares method. Deep nets are highly generalizable allowing data to be evaluated from different time series after interpolation without compromising performance. As validated by our deep net analysis of Kepler light curves, we detect periodic transits consistent with the true period without any model fitting. Our study indicates that machine learning will facilitate the characterization of exoplanets in future analysis of large astronomy data sets.