TY - JOUR
T1 - Understanding the diversity of 21 cm cosmology analyses
AU - Morales, Miguel F.
AU - Beardsley, Adam
AU - Pober, Jonathan
AU - Barry, Nichole
AU - Hazelton, Bryna
AU - Jacobs, Daniel
AU - Sullivan, Ian
N1 - Funding Information:
This work was directly supported by National Science Foundation (NSF) grants #1613855, #1613040, #1506024, and #1636646 and National Aeronautivcal and Space Administration grant 80NSSC18K0389. AB is supported by an NSF Astronomy and Astrophysics Postdoctoral Fellowship under #1701440. We’d also like to thank the anonymous referee, Adrian Liu, Cathryn Trott, and Michael Eastwood for their helpful comments in improving this paper.
Publisher Copyright:
©2018 The Author(s).
PY - 2019/2/21
Y1 - 2019/2/21
N2 - 21 cm power spectrum observations have the potential to revolutionize our understanding of the epoch of reionization and dark energy, but require extraordinarily precise data analysis methods to separate the cosmological signal from the astrophysical and instrumental contaminants. This analysis challenge has led to a diversity of proposed analyses, including delay spectra, imaging power spectra,m-mode analysis, and numerous others. This diversity of approach is a strength, but has also led to a confusion within the community about whether insights gleaned by one group are applicable to teams working in different analysis frameworks. In this paper, we show that all existing analysis proposals can be classified into two distinct families based on whether they estimate the power spectrum of the measured or reconstructed sky. This subtle difference in the statistical question posed largely determines the susceptibility of the analyses to foreground emission and calibration errors, and ultimately the science different analyses can pursue. In this paper, we detail the origin of the two analysis families, categorize the analyses being actively developed, and explore their relative sensitivities to foreground contamination and calibration errors.
AB - 21 cm power spectrum observations have the potential to revolutionize our understanding of the epoch of reionization and dark energy, but require extraordinarily precise data analysis methods to separate the cosmological signal from the astrophysical and instrumental contaminants. This analysis challenge has led to a diversity of proposed analyses, including delay spectra, imaging power spectra,m-mode analysis, and numerous others. This diversity of approach is a strength, but has also led to a confusion within the community about whether insights gleaned by one group are applicable to teams working in different analysis frameworks. In this paper, we show that all existing analysis proposals can be classified into two distinct families based on whether they estimate the power spectrum of the measured or reconstructed sky. This subtle difference in the statistical question posed largely determines the susceptibility of the analyses to foreground emission and calibration errors, and ultimately the science different analyses can pursue. In this paper, we detail the origin of the two analysis families, categorize the analyses being actively developed, and explore their relative sensitivities to foreground contamination and calibration errors.
KW - First stars - cosmology: observations
KW - Methods: data analysis - dark ages
KW - Reionization
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U2 - 10.1093/mnras/sty2844
DO - 10.1093/mnras/sty2844
M3 - Article
AN - SCOPUS:85067198750
SN - 0035-8711
VL - 483
SP - 2207
EP - 2216
JO - Monthly Notices of the Royal Astronomical Society
JF - Monthly Notices of the Royal Astronomical Society
IS - 2
ER -