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Register a new userA Generative Model of Galactic Dust Emission Using Variational Inference
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Emission from the interstellar medium can be a significant contaminant of measurements of the intensity and polarization of the cosmic microwave background (CMB). For planning CMB observations, and for optimizing foreground-cleaning algorithms, a description of the statistical properties of such emission can be helpful. Here we examine a machine learning approach to inferring the statistical properties of dust from either observational data or physics-based simulations. In particular, we apply a type of neural network called a Variational Auto Encoder (VAE) to maps of the intensity of emission from interstellar dust as inferred from Planck sky maps and demonstrate its ability to a) simulate new samples with similar summary statistics as the training set, b) provide fits to emission maps withheld from the training set, and c) produce constrained realizations. We find VAEs are easier to train than another popular architecture: that of Generative Adversarial Networks (GANs), and are better-suited for use in Bayesian inference.
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The upcoming generation of cosmic microwave background (CMB) experiments face a major challenge in detecting the weak cosmic B-mode signature predicted as a product of primordial gravitational waves. To achieve the required sensitivity these experiments must have impressive control of systematic effects and detailed understanding of the foreground emission that will influence the signal. In this paper, we present templates of the intensity and polarisation of emission from one of the main Galactic foregrounds, interstellar dust. These are produced using a model which includes a 3D description of the Galactic magnetic field, examining both large and small scales. We also include in the model the details of the dust density, grain alignment and the intrinsic polarisation of the emission from an individual grain. We present here Stokes parameter template maps at 150GHz and provide an on-line repository (http://www.imperial.ac.uk/people/c.contaldi/fgpol) for these and additional maps at frequencies that will be targeted by upcoming experiments such as EBEX, Spider and SPTpol.
Using the Planck 2015 data release (PR2) temperature maps, we separate Galactic thermal dust emission from cosmic infrared background (CIB) anisotropies. For this purpose, we implement a specifically tailored component-separation method, the so-called generalized needlet internal linear combination (GNILC) method, which uses spatial information (the angular power spectra) to disentangle the Galactic dust emission and CIB anisotropies. We produce significantly improved all-sky maps of Planck thermal dust emission, with reduced CIB contamination, at 353, 545, and 857 GHz. By reducing the CIB contamination of the thermal dust maps, we provide more accurate estimates of the local dust temperature and dust spectral index over the sky with reduced dispersion, especially at high Galactic latitudes above $b = pm 20{deg}$. We find that the dust temperature is $T = (19.4 pm 1.3)$ K and the dust spectral index is $beta = 1.6 pm 0.1$ averaged over the whole sky, while $T = (19.4 pm 1.5)$ K and $beta = 1.6 pm 0.2$ on 21 % of the sky at high latitudes. Moreover, subtracting the new CIB-removed thermal dust maps from the CMB-removed Planck maps gives access to the CIB anisotropies over 60 % of the sky at Galactic latitudes $|b| > 20{deg}$. Because they are a significant improvement over previous Planck products, the GNILC maps are recommended for thermal dust science. The new CIB maps can be regarded as indirect tracers of the dark matter and they are recommended for exploring cross-correlations with lensing and large-scale structure optical surveys. The reconstructed GNILC thermal dust and CIB maps are delivered as Planck products.
We present an improved Global Sky Model (GSM) of diffuse galactic radio emission from 10 MHz to 5 THz, whose uses include foreground modeling for CMB and 21 cm cosmology. Our model improves on past work both algorithmically and by adding new data sets such as the Planck maps and the enhanced Haslam map. Our method generalizes the Principal Component Analysis approach to handle non-overlapping regions, enabling the inclusion of 29 sky maps with no region of the sky common to all. We also perform a blind separation of our GSM into physical components with a method that makes no assumptions about physical emission mechanisms (synchrotron, free-free, dust, etc). Remarkably, this blind method automatically finds five components that have previously only been found by hand, which we identify with synchrotron, free-free, cold dust, warm dust, and the CMB anisotropy, with maps and spectra agreeing with previous work but in many cases with smaller error bars. The improved GSM is available online at github.com/jeffzhen/gsm2016.
We describe our custom processing of the entire Wide-field Infrared Survey Explorer (WISE) 12 micron imaging data set, and present a high-resolution, full-sky map of diffuse Galactic dust emission that is free of compact sources and other contaminating artifacts. The principal distinctions between our resulting co-added images and the WISE Atlas stacks are our removal of compact sources, including their associated electronic and optical artifacts, and our preservation of spatial modes larger than 1.5 degrees. We provide access to the resulting full-sky map via a set of 430 12.5 degree by 12.5 degree mosaics. These stacks have been smoothed to 15 resolution and are accompanied by corresponding coverage maps, artifact images, and bit-masks for point sources, resolved compact sources, and other defects. When combined appropriately with other mid-infrared and far-infrared data sets, we expect our WISE 12 micron co-adds to form the basis for a full-sky dust extinction map with angular resolution several times better than Schlegel et al. (1998).
We investigate the relationship between the linewidths of broad Mg II lambda2800 and Hbeta in active galactic nuclei (AGNs) to refine them as tools to estimate black hole (BH) masses. We perform a detailed spectral analysis of a large sample of AGNs at intermediate redshifts selected from the Sloan Digital Sky Survey, along with a smaller sample of archival ultraviolet spectra for nearby sources monitored with reverberation mapping. Careful attention is devoted to accurate spectral decomposition, especially in the treatment of narrow-line blending and Fe II contamination. We show that, contrary to popular belief, the velocity width of Mg II tends to be smaller than that of Hbeta, suggesting that the two species are not cospatial in the broad-line region. Using these findings and recently updated BH mass measurements from reverberation mapping, we present a new calibration of the empirical prescriptions for estimating virial BH masses for AGNs using the broad Mg II and Hbeta lines. We show that the BH masses derived from our new formalisms show subtle but important differences compared to some of the mass estimators currently used in the literature.
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