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

• Published in: The Astrophysical Journal
• Main Authors: Gambrel, A. E., Rahlin, A. S., Song, X., Contaldi, C. R., Ade, P. A. R., Amiri, M., Benton, S. J., Bergman, A. S., Bihary, R., Bock, J. J., Bond, J. R., Bonetti, J. A., Bryan, S. A., Chiang, H. C., Duivenvoorden, A. J., Eriksen, H. K., Farhang, M., Filippini, J. P., Fraisse, A. A., Freese, K., Galloway, M. M., Gandilo, N. N., Gualtieri, R., Gudmundsson, J. E., Halpern, M., Hartley, J., Hasselfield, M., Hilton, G., Holmes, W., Hristov, V. V., Huang, Z., Irwin, K. D., Jones, W. C., Karakci, A., Kuo, C. L., Kermish, Z. D., Leung, J. S.-Y., Li, S., Mak, D. S. Y., Mason, P. V., Megerian, K., Moncelsi, L., Morford, T. A., Nagy, J. M., Netterfield, C. B., Nolta, M., O'Brient, R., Osherson, B., Padilla, I. L., Racine, B., Reintsema, C., Ruhl, J. E., Ruud, T. M., Shariff, J. A., Shaw, E. C., Shiu, C., Soler, J. D., Trangsrud, A., Tucker, C., Tucker, R. S., Turner, A. D., van der List, J. F., Weber, A. C., Wehus, I. K., Wen, S., Wiebe, D. V., Young, E. Y.
• Format: Article in Journal/Newspaper
• Language: unknown
• Published: American Astronomical Society 2021
• Subjects: Cosmic microwave background radiation; Maximum likelihood estimation; Observational cosmology; Antarctic; Canada; The Antarctic; Antarc*
• Online Access: https://doi.org/10.3847/1538-4357/ac230b

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-Cℓ–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. © 2021. The American Astronomical Society. Received 2021 May 21; revised 2021 August 24; accepted 2021 August 24; published 2021 November 25. We acknowledge the contribution to the development of the XFaster pipeline 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. ...