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Published September 1, 2015 | Submitted + Published
Journal Article Open

A Measurement of the Cosmic Microwave Background Gravitational Lensing Potential from 100 Square Degrees of SPTpol Data

Abstract

We present a measurement of the cosmic microwave background (CMB) gravitational lensing potential using data from the first two seasons of observations with SPTpol, the polarization-sensitive receiver currently installed on the South Pole Telescope. The observations used in this work cover 100 deg^2 of sky with arcminute resolution at 150 GHz. Using a quadratic estimator, we make maps of the CMB lensing potential from combinations of CMB temperature and polarization maps. We combine these lensing potential maps to form a minimum-variance (MV) map. The lensing potential is measured with a signal-to-noise ratio of greater than one for angular multipoles between 100 < L < 250. This is the highest signal-to-noise mass map made from the CMB to date and will be powerful in cross-correlation with other tracers of large-scale structure. We calculate the power spectrum of the lensing potential for each estimator, and we report the value of the MV power spectrum between 100 < L < 2000 as our primary result. We constrain the ratio of the spectrum to a fiducial ΛCDM model to be A_(MV) = 0.92 ± 0.14 (Stat.) ± 0.08 (Sys.). Restricting ourselves to polarized data only, we find A_(POL) = 0.92 ± 0.24 (Stat.) ± 0.11 (Sys.). This measurement rejects the hypothesis of no lensing at 5.9σ using polarization data alone, and at 14σ using both temperature and polarization data.

Additional Information

© 2015 The American Astronomical Society. Received 2014 December 15; accepted 2015 June 12; published 2015 August 28. 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. The CU Boulder group acknowledges support from NSF AST-0956135. J. W. H. is supported by the National Science Foundation under Award No. AST-1402161. B. B. is supported by the Fermi Research Alliance, LLC under Contract No. De-AC02-07CH11359 with the U.S. Department of Energy. TdH is supported by a Miller Research Fellowship. This work is also supported by the U.S. Department of Energy. Work at Argonne National Lab is supported by UChicago Argonne, LLC, Operator of Argonne National Laboratory (Argonne). Argonne, a U.S. Department of Energy Office of Science Laboratory, is operated under Contract No. DE-AC02-06CH11357. We also acknowledge support from the Argonne Center for Nanoscale Materials. This research used resources of the Calcul Quebec computing consortium, part of the Compute Canada network, and of the National Energy Research Scientific Computing Center, a DOE Office of Science User Facility supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231. The data analysis pipeline uses the scientific Python stack (Jones et al. 2001; Hunter 2007; van der Walt et al. 2011) and the HDF5 file format (The HDF Group 1997).

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Submitted - 1412.4760v2.pdf

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August 20, 2023
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October 25, 2023