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The XFaster Power Spectrum and Likelihood Estimator for the Analysis of Cosmic Microwave Background Maps

Gambrel, A. E. and Rahlin, A. S. and Song, X. and Contaldi, C. R. and Ade, P. A. R. and Amiri, M. and Benton, S. J. and Bergman, A. S. and Bihary, R. and Bock, J. J. and Bond, J. R. and Bonetti, J. A. and Bryan, S. A. and Chiang, H. C. and Duivenvoorden, A. J. and Eriksen, H. K. and Farhang, M. and Filippini, J. P. and Fraisse, A. A. and Freese, K. and Galloway, M. and Gandilo, N. N. and Gualtieri, R. and Gudmundsson, J. E. and Halpern, M. and Hartley, J. and Hasselfield, M. and Hilton, G. and Holmes, W. A. and Hristov, V. V. and Huang, Z. and Irwin, K. D. and Jones, W. C. and Karakci, A. and Kuo, C. L. and Kermish, Z. D. and Leung, J. S. -Y. and Li, S. and Mak, D. S. Y. and Mason, P. V. and Megerian, K. and Moncelsi, L. and Morford, T. A. and Nagy, J. M. and Netterfield, C. B. and Nolta, M. and O'Brient, R. and Osherson, B. and Padilla, I. L. and Racine, B. and Reintsema, C. and Ruhl, J. E. and Ruud, T. M. and Shariff, J. A. and Shaw, E. C. and Shiu, C. and Soler, J. D. and Trangsrud, A. and Tucker, C. and Tucker, R. S. and Turner, A. D. and List, J. F. van der and Weber, A. C. and Wehus, I. K. and Wen, S. and Wiebe, D. V. and Young, E. Y. (2021) The XFaster Power Spectrum and Likelihood Estimator for the Analysis of Cosmic Microwave Background Maps. . (Unpublished)

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We present the XFaster analysis package. XFaster is a fast, iterative angular power spectrum estimator based on a diagonal approximation to the quadratic Fisher matrix estimator. XFaster uses Monte Carlo simulations to compute noise biases and filter transfer functions and is thus a hybrid of both Monte Carlo and quadratic estimator methods. In contrast to conventional pseudo-C_ℓ based methods, the algorithm described here requires a minimal number of simulations, and does not require them to be precisely representative of the data to estimate accurate covariance matrices for the bandpowers. The formalism works with polarization-sensitive observations and also data sets with identical, partially overlapping, or independent survey regions. The method was first implemented for the analysis of BOOMERanG data, and also used as part of the Planck analysis. Here, we describe the full, publicly available analysis package, written in Python, as developed for the analysis of data from the 2015 flight of the SPIDER instrument. The package includes extensions for self-consistently estimating null spectra and for estimating fits for Galactic foreground contributions. We show results from the extensive validation of XFaster using simulations, and its application to the SPIDER data set.

Item Type:Report or Paper (Discussion Paper)
Related URLs:
URLURL TypeDescription Paper
Bock, J. J.0000-0002-5710-5212
Mason, P. V.0000-0002-7963-7420
Moncelsi, L.0000-0002-4242-3015
Additional Information:We acknowledge the contribution to the development of the XFaster pipelines by all members of the BOOMERanG, Planck, and SPIDER collaborations. SPIDER is supported in the U.S. by the National Aeronautics and Space Administration under grants NNX07AL64G, NNX12AE95G, and NNX17AC55G issued through the Science Mission Directorate and by the National Science Foundation through PLR-1043515. Logistical support for the Antarctic deployment and operations is provided by the NSF through the U.S. Antarctic Program. Support in Canada is provided by the Natural Sciences and Engineering Research Council and the Canadian Space Agency. Support in Norway is provided by the Research Council of Norway. Support in Sweden is provided by the Swedish Research Council through the Oskar Klein Centre (Contract No. 638-2013-8993) as well as a grant from the Swedish Research Council (dnr. 2019-93959) and a grant from the Swedish Space Agency (dnr. 139/17). The Dunlap Institute is funded through an endowment established by the David Dunlap family and the University of Toronto. The multiplexing readout electronics were developed with support from the Canada Foundation for Innovation and the British Columbia Knowledge Development Fund. AEG is supported by the Kavli Institute for Cosmological Physics at the University of Chicago through an endowment from the Kavli Foundation and its founder Fred Kavli. CRC was supported by UKRI Consolidated Grants, ST/P000762/1, ST/N000838/1, and ST/T000791/1. KF holds the Jeff & Gail Kodosky Endowed Chair at UT Austin and is grateful for that support. WCJ acknowledges Foundation, which has been crucial to the success of the project. Some of the results in this paper have been derived using the HEALPix package (Gorski et al. 2005). The computations described in this paper were performed on four computing clusters: Hippo at the University of KwaZulu-Natal, Feynman at Princeton University, and the GPC and Niagara supercomputers at the SciNet HPC Consortium (Loken et al. 2010; Ponce et al. 2019). SciNet is funded by the Canada Foundation for Innovation under the auspices of Compute Canada, the Government of Ontario, Ontario Research Fund - Research Excellence, and the University of Toronto. The collaboration is grateful to the British Antarctic Survey, particularly Sam Burrell, and to the Alfred Wegener Institute and the crew of R.V. Polarstern for invaluable assistance with the recovery of the data and payload after the 2015 flight. Brendan Crill and Tom Montroy made significant contributions to SPIDER’s development. This project, like so many others that he founded and supported, owes much to the vision and leadership of the late Professor Andrew E. Lange.
Group:Astronomy Department
Funding AgencyGrant Number
Natural Sciences and Engineering Research Council of Canada (NSERC)UNSPECIFIED
Canadian Space Agency (CSA)UNSPECIFIED
Research Council of NorwayUNSPECIFIED
Swedish Research Council638-2013-8993
Swedish Research Council2019-93959
Swedish Research Council139/17
David Dunlap FamilyUNSPECIFIED
University of TorontoUNSPECIFIED
Canada Foundation for InnovationUNSPECIFIED
British Columbia Knowledge Development FundUNSPECIFIED
Kavli Institute for Cosmological PhysicsUNSPECIFIED
Kavli FoundationUNSPECIFIED
Science and Technology Facilities Council (STFC)ST/P000762/1
Science and Technology Facilities Council (STFC)ST/N000838/1
Science and Technology Facilities Council (STFC)ST/T000791/1
University of Texas at AustinUNSPECIFIED
Ontario Research Fund-Research ExcellenceUNSPECIFIED
Record Number:CaltechAUTHORS:20210409-140459958
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Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:108678
Deposited By: Tony Diaz
Deposited On:12 Apr 2021 01:23
Last Modified:12 Apr 2021 01:23

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