4.7 Article

COMAP Early Science. IV. Power Spectrum Methodology and Results

期刊

ASTROPHYSICAL JOURNAL
卷 933, 期 2, 页码 -

出版社

IOP Publishing Ltd
DOI: 10.3847/1538-4357/ac63c5

关键词

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资金

  1. National Science Foundation [1517108, 1517288, 1517598, 1518282, 1910999]
  2. Keck Institute for Space Studies
  3. National Aeronautics and Space Administration
  4. internal Research and Technology Development program
  5. CITA/Dunlap Institute postdoctoral fellowship
  6. David Dunlap family
  7. University of Toronto
  8. STFC Consolidated Grant [ST/P000649/1]
  9. Research Council of Norway [251328, 274990]
  10. European Research Council (ERC) [819478]
  11. University of Miami
  12. Caltech
  13. Swiss National Science Foundation [PZ00P2_179934]
  14. James Arthur Postdoctoral Fellowship
  15. European Research Council (ERC) [819478] Funding Source: European Research Council (ERC)
  16. Swiss National Science Foundation (SNF) [PZ00P2_179934] Funding Source: Swiss National Science Foundation (SNF)
  17. Direct For Mathematical & Physical Scien
  18. Division Of Astronomical Sciences [1517288, 1518282, 1517598] Funding Source: National Science Foundation
  19. Division Of Astronomical Sciences
  20. Direct For Mathematical & Physical Scien [1910999, 1517108] Funding Source: National Science Foundation

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This article presents the power spectrum methodology used in the first-season COMAP analysis and evaluates the quality of the current data set. Using the Feed-Feed Pseudo-Cross-Spectrum (FPXS) method, the main results are derived, and both noise modeling errors and experimental systematics are taken into account. By applying effective transfer functions, the effects of instrumental beam smoothing and various filter operations are considered. The power spectra obtained in this way help identify a systematic error related to one of the scanning strategies and demonstrate that uncertainties integrate as expected. The FPXS method allows for the estimation of the clustering component of the CO(1-0) power spectrum.
We present the power spectrum methodology used for the first-season COMAP analysis, and assess the quality of the current data set. The main results are derived through the Feed-Feed Pseudo-Cross-Spectrum (FPXS) method, which is a robust estimator with respect to both noise modeling errors and experimental systematics. We use effective transfer functions to take into account the effects of instrumental beam smoothing and various filter operations applied during the low-level data processing. The power spectra estimated in this way have allowed us to identify a systematic error associated with one of our two scanning strategies, believed to be due to residual ground or atmospheric contamination. We omit these data from our analysis and no longer use this scanning technique for observations. We present the power spectra from our first season of observing, and demonstrate that the uncertainties are integrating as expected for uncorrelated noise, with any residual systematics suppressed to a level below the noise. Using the FPXS method, and combining data on scales k = 0.051-0.62 Mpc(-1), we estimate P (CO)(k) = -2. 7 +/- 1.7 x 10(4) mu K-2 Mpc(3), the first direct 3D constraint on the clustering component of the CO(1-0) power spectrum in the literature.

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