The XFaster Power Spectrum and Likelihood Estimator for the Analysis of Cosmic Microwave Background Maps
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Published:2021-11-25
Issue:2
Volume:922
Page:132
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ISSN:0004-637X
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Container-title:The Astrophysical Journal
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language:
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Short-container-title:ApJ
Author:
Gambrel A. E., Rahlin A. S.ORCID, Song X., Contaldi C. R.ORCID, Ade P. A. R., Amiri M., Benton S. J.ORCID, Bergman A. S., Bihary R., Bock J. J., Bond J. R.ORCID, Bonetti J. A., Bryan S. A., Chiang H. C.ORCID, Duivenvoorden A. J.ORCID, Eriksen H. K., Farhang M., Filippini J. P.ORCID, Fraisse A. A., Freese K., Galloway M., Gandilo N. N., Gualtieri R.ORCID, Gudmundsson J. E.ORCID, Halpern M.ORCID, Hartley J., Hasselfield M., Hilton G., Holmes W., Hristov V. V., Huang Z., Irwin K. D., Jones W. C.ORCID, Karakci A., Kuo C. L., Kermish Z. D., Leung J. S.-Y.ORCID, Li S.ORCID, Mak D. S. Y., Mason P. V., Megerian K., Moncelsi L., Morford T. A., Nagy J. M.ORCID, Netterfield C. B., Nolta M., O’Brient R., Osherson B., Padilla I. L.ORCID, Racine B., Reintsema C., Ruhl J. E., Ruud T. M.ORCID, Shariff J. A., Shaw E. C.ORCID, Shiu C., Soler J. D.ORCID, Trangsrud A., Tucker C., Tucker R. S., Turner A. D., List J. F. van der, Weber A. C., Wehus I. K.ORCID, Wen S., Wiebe D. V., Young E. Y.
Abstract
Abstract
We present the XFaster analysis package, a fast, iterative angular power spectrum estimator based on a diagonal approximation to the quadratic Fisher matrix estimator. It 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 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.
Funder
NASA ∣ Science Mission Directorate National Science Foundation Swedish Research Council Swedish Space Agency UK Research and Innovation
Publisher
American Astronomical Society
Subject
Space and Planetary Science,Astronomy and Astrophysics
Cited by
2 articles.
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