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Published May 2022 | Accepted Version
Journal Article Open

The Atacama Cosmology Telescope: measurement and analysis of 1D beams for DR4

Abstract

We describe the measurement and treatment of the telescope beams for the Atacama Cosmology Telescope's fourth data release, DR4. Observations of Uranus are used to measure the central portion (<12') of the beams to roughly -40 dB of the peak. Such planet maps in intensity are used to construct azimuthally averaged beam profiles, which are fit with a physically motivated model before being transformed into Fourier space. We investigate and quantify a number of percent-level corrections to the beams, all of which are important for precision cosmology. Uranus maps in polarization are used to measure the temperature-to-polarization leakage in the main part of the beams, which is ≲ 1% (2.5%) at 150 GHz (98 GHz). The beams also have polarized sidelobes, which are measured with observations of Saturn and deprojected from the ACT time-ordered data. Notable changes relative to past ACT beam analyses include an improved subtraction of the atmospheric effects from Uranus calibration maps, incorporation of a scattering term in the beam profile model, and refinements to the beam model uncertainties and the main temperature-to-polarization leakage terms in the ACT power spectrum analysis.

Additional Information

© 2022 IOP Publishing Ltd and Sissa Medialab. Received 26 December 2021; Accepted 17 March 2022; Published 26 May 2022. Support for ACT was through the U.S. National Science Foundation through awards AST-0408698, AST-0965625, and AST-1440226 for the ACT project, as well as awards PHY-0355328, PHY-0855887 and PHY-1214379. Funding was also provided by Princeton University, the University of Pennsylvania, and a Canada Foundation for Innovation (CFI) award to UBC. ACT operates in the Parque Astronomico Atacama in northern Chile under the auspices of the Agencia Nacional de Investigacion y Desarrollo (ANID). The development of multichroic detectors and lenses was supported by NASA grants NNX13AE56G and NNX14AB58G. Detector research at NIST was supported by the NIST Innovations in Measurement Science program. Computations were performed on Tiger and Della as part of Princeton Research Computing resources at Princeton University, on Feynman at Princeton University, and on the Niagara supercomputer at the SciNet HPC Consortium. SciNet is funded by the CFI under the auspices of Compute Canada, the Government of Ontario, the Ontario Research Fund-Research Excellence, and the University of Toronto. Research at Perimeter Institute is supported in part by the Government of Canada through the Department of Innovation, Science and Industry Canada and by the Province of Ontario through the Ministry of Colleges and Universities. ML was supported by a Dicke Fellowship. ES and JD are supported through NSF grant AST-1814971 and AST-2108126. EC acknowledges support from the STFC Ernest Rutherford Fellowship ST/M004856/2, STFC Consolidated Grant ST/S00033X/ and from the Horizon 2020 ERC Starting Grant (Grant agreement No 849169). SKC acknowledges support from NSF award AST-2001866. JCH acknowledges support from NSF grant AST-2108536. ADH acknowledges support from the Sutton Family Chair in Science, Christianity and Cultures and from the Faculty of Arts and Science, University of Toronto. KM acknowledges support from the National Research Foundation of South Africa. LP gratefully acknowledges support from the Mishrahi and Wilkinson funds. ZX is supported by the Gordon and Betty Moore Foundation through grant GBMF5215 to the Massachusetts Institute of Technology. We gratefully acknowledge the publicly available software packages that were used for parts of this analysis. They include healpy (Zonca et al. 2019), HEALPix (Goorski et al. 2005b), libsharp (Reinecke & Seljebotn 2013), and pixell34. This research made use of Astropy35, a community-developed core Python package for Astronomy (Astropy Collaboration et al. 2013; Price-Whelan et al. 2018). We also acknowledge use of the matplotlib (Hunter 2007) package and the Python Image Library for producing plots in this paper.

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Additional details

Created:
August 22, 2023
Modified:
October 24, 2023