We present a cosmic microwave background (CMB) lensing map produced from a linear combination of South Pole Telescope (SPT) and Planck temperature data. The 150 GHz temperature data from the 2500 deg2 SPT-SZ survey is combined with the Planck 143 GHz data in harmonic space to obtain a temperature map that has a broader ℓ coverage and less noise than either individual map. Using a quadratic estimator technique on this combined temperature map, we produce a map of the gravitational lensing potential projected along the line of sight. We measure the auto-spectrum of the lensing potential CLφφ, and compare it to the theoretical prediction for a ΛCDM cosmology consistent with the Planck 2015 data set, finding a best-fit amplitude of 0.95-0.06+0.06(stat.)0.01+0.01(sys.). The null hypothesis of no lensing is rejected at a significance of 24σ. One important use of such a lensing potential map is in cross-correlations with other dark matter tracers. We demonstrate this cross-correlation in practice by calculating the cross-spectrum, CLφG, between the SPT+Planck lensing map and Wide-field Infrared Survey Explorer (WISE) galaxies. We fit CLφG to a power law of the form PL = a(L/L0)-b with a, L 0, and b fixed, and find ηφG = CLφG/PL = 0.94-0.04+0.04, which is marginally lower, but in good agreement with ηφG = 1.00-0.01+0.02, the best-fit amplitude for the cross-correlation of Planck-2015 CMB lensing and WISE galaxies over ∼67% of the sky. The lensing potential map presented here will be used for cross-correlation studies with the Dark Energy Survey, whose footprint nearly completely covers the SPT 2500 deg2 field.
Bibliographical noteFunding Information:
We thank Hao-Yi Wu and Olivier Doré 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 Québec and Compute Canada. The operation of this supercomputer is funded by the Canada Foundation for Innovation (CFI), the ministère de l’Économie, de la science et de l’innovation du Québec (MESI) and the Fonds de recherche du Québec—Nature et 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,49 HEALPIX (Górski et al. 2005), IPYTHON (Pérez & Granger 2007), LENSPIX (Lewis 2005), MATPLOTLIB (Hunter 2007), NUMPY and SCIPY (van der Walt et al. 2011), POLSPICE (Chon et al. 2004), and QUICKLENS (see footnote 39).
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- cosmic background radiation
- gravitational lensing: weak
- large-scale structure of universe