A 2500 deg(2) CMB Lensing Map from Combined South Pole Telescope and Planck Data

Grants

Funding Acknowledgements

We thank Hao-Yi Wu and Olivier Dore for the theoretical prediction for the cross-correlation between CIB and CMB lensing. The South Pole Telescope program is supported by the National Science Foundation through grant PLR-1248097. Partial support is also provided by the NSF Physics Frontier Center grant PHY-0114422 to the Kavli Institute of Cosmological Physics at the University of Chicago, the Kavli Foundation, and the Gordon and Betty Moore Foundation through Grant GBMF #947 to the University of Chicago. The McGill authors acknowledge funding from the Natural Sciences and Engineering Research Council of Canada, Canadian Institute for Advanced Research, and Canada Research Chairs program. C.R. acknowledges support from a Australian Research Council Future Fellowship (FT150100074). B.B. is supported by the Fermi Research Alliance, LLC under Contract No. De-AC02-07CH11359 with the United States Department of Energy. This publication makes use of data products from the Wide-field Infrared Survey Explorer, which is a joint project of the University of California, Los Angeles, and the Jet Propulsion Laboratory/California. Institute of Technology, funded by the National Aeronautics and Space Administration. Argonne National Laboratorys work was supported under U.S. Department of Energy contract DE-AC02-06CH11357. Computations were made on the supercomputer Guillimin from McGill University, managed by Calcul Quebec and Compute Canada. The operation of this supercomputer is funded by the Canada Foundation for Innovation (CFI), the ministere de l'Economie, de la science et de l'innovation du Quebec (MESI) and the Fonds de recherche du Quebec-Natureet technologies (FRQ-NT). This research is part of the Blue Waters sustained-petascale computing project, which is supported by the National Science Foundation (awards OCI-0725070 and ACI-1238993) and the state of Illinois. Blue Waters is a joint effort of the University of Illinois at Urbana Champaign and its National Center for Supercomputing Applications. This work used resources made available on the Jupiter cluster, a joint data-intensive computing project between the High Energy Physics Division and the Computing, Environment, and Life Sciences (CELS) Directorate at Argonne National Laboratory. The results in this paper have been derived using the following packages: ASTROPY, a community-developed core Python package for Astronomy (Astropy Collaboration et al. 2013), CAMB (Lewis et al. 2000; Howlett et al. 2012), CMOCEAN,<SUP>49</SUP> HEALPIX (Gorski et al. 2005), IPYTHON (Perez & Granger 2007), LENsPix (Lewis 2005), MATPLOTLIB (Hunter 2007), NUMPY and SoPY (van der Walt et al. 2011), POLSPICE (Chon et al. 2004), and QUICKLENS (see footnote 39).