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| Format: | Preprint |
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2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2411.10529 |
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| _version_ | 1866910732467044352 |
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| author | Chen, Kai-Feng Wilensky, Michael J. Liu, Adrian Dillon, Joshua S. Hewitt, Jacqueline N. Adams, Tyrone Aguirre, James E. Baartman, Rushelle Beardsley, Adam P. Berkhout, Lindsay M. Bernardi, Gianni Billings, Tashalee S. Bowman, Judd D. Bull, Philip Burba, Jacob Byrne, Ruby Carey, Steven Choudhuri, Samir Cox, Tyler DeBoer, David R. Dexter, Matt Eksteen, Nico Ely, John Ewall-Wice, Aaron Furlanetto, Steven R. Gale-Sides, Kingsley Garsden, Hugh Gehlot, Bharat Kumar Gorce, Adélie Gorthi, Deepthi Halday, Ziyaad Hazelton, Bryna J. Hickish, Jack Jacobs, Daniel C. Josaitis, Alec Kern, Nicholas S. Kerrigan, Joshua Kittiwisit, Piyanat Kolopanis, Matthew La Plante, Paul Lanman, Adam Ma, Yin-Zhe MacMahon, David H. E. Malan, Lourence Malgas, Cresshim Malgas, Keith Marero, Bradley Martinot, Zachary E. McBride, Lisa Mesinger, Andrei Mohamed-Hinds, Nicel Molewa, Mathakane Morales, Miguel F. Murray, Steven G. Nuwegeld, Hans Parsons, Aaron R. Pascua, Robert Qin, Yuxiang Rath, Eleanor Razavi-Ghods, Nima Robnett, James Santos, Mario G. Sims, Peter Singh, Saurabh Storer, Dara Swarts, Hilton Tan, Jianrong van Wyngaarden, Pieter Zheng, Haoxuan |
| author_facet | Chen, Kai-Feng Wilensky, Michael J. Liu, Adrian Dillon, Joshua S. Hewitt, Jacqueline N. Adams, Tyrone Aguirre, James E. Baartman, Rushelle Beardsley, Adam P. Berkhout, Lindsay M. Bernardi, Gianni Billings, Tashalee S. Bowman, Judd D. Bull, Philip Burba, Jacob Byrne, Ruby Carey, Steven Choudhuri, Samir Cox, Tyler DeBoer, David R. Dexter, Matt Eksteen, Nico Ely, John Ewall-Wice, Aaron Furlanetto, Steven R. Gale-Sides, Kingsley Garsden, Hugh Gehlot, Bharat Kumar Gorce, Adélie Gorthi, Deepthi Halday, Ziyaad Hazelton, Bryna J. Hickish, Jack Jacobs, Daniel C. Josaitis, Alec Kern, Nicholas S. Kerrigan, Joshua Kittiwisit, Piyanat Kolopanis, Matthew La Plante, Paul Lanman, Adam Ma, Yin-Zhe MacMahon, David H. E. Malan, Lourence Malgas, Cresshim Malgas, Keith Marero, Bradley Martinot, Zachary E. McBride, Lisa Mesinger, Andrei Mohamed-Hinds, Nicel Molewa, Mathakane Morales, Miguel F. Murray, Steven G. Nuwegeld, Hans Parsons, Aaron R. Pascua, Robert Qin, Yuxiang Rath, Eleanor Razavi-Ghods, Nima Robnett, James Santos, Mario G. Sims, Peter Singh, Saurabh Storer, Dara Swarts, Hilton Tan, Jianrong van Wyngaarden, Pieter Zheng, Haoxuan |
| contents | The precise characterization and mitigation of systematic effects is one of the biggest roadblocks impeding the detection of the fluctuations of cosmological 21cm signals. Missing data in radio cosmological experiments, often due to radio frequency interference (RFI), poses a particular challenge to power spectrum analysis as it could lead to the ringing of bright foreground modes in Fourier space, heavily contaminating the cosmological signals. Here we show that the problem of missing data becomes even more arduous in the presence of systematic effects. Using a realistic numerical simulation, we demonstrate that partially flagged data combined with systematic effects can introduce significant foreground ringing. We show that such an effect can be mitigated through inpainting the missing data. We present a rigorous statistical framework that incorporates the process of inpainting missing data into a quadratic estimator of the 21cm power spectrum. Under this framework, the uncertainties associated with our inpainting method and its impact on power spectrum statistics can be understood. These results are applied to the latest Phase II observations taken by the Hydrogen Epoch of Reionization Array, forming a crucial component in power spectrum analyses as we move toward detecting 21cm signals in the ever more noisy RFI environment. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2411_10529 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Impacts and Statistical Mitigation of Missing Data on the 21cm Power Spectrum: A Case Study with the Hydrogen Epoch of Reionization Array Chen, Kai-Feng Wilensky, Michael J. Liu, Adrian Dillon, Joshua S. Hewitt, Jacqueline N. Adams, Tyrone Aguirre, James E. Baartman, Rushelle Beardsley, Adam P. Berkhout, Lindsay M. Bernardi, Gianni Billings, Tashalee S. Bowman, Judd D. Bull, Philip Burba, Jacob Byrne, Ruby Carey, Steven Choudhuri, Samir Cox, Tyler DeBoer, David R. Dexter, Matt Eksteen, Nico Ely, John Ewall-Wice, Aaron Furlanetto, Steven R. Gale-Sides, Kingsley Garsden, Hugh Gehlot, Bharat Kumar Gorce, Adélie Gorthi, Deepthi Halday, Ziyaad Hazelton, Bryna J. Hickish, Jack Jacobs, Daniel C. Josaitis, Alec Kern, Nicholas S. Kerrigan, Joshua Kittiwisit, Piyanat Kolopanis, Matthew La Plante, Paul Lanman, Adam Ma, Yin-Zhe MacMahon, David H. E. Malan, Lourence Malgas, Cresshim Malgas, Keith Marero, Bradley Martinot, Zachary E. McBride, Lisa Mesinger, Andrei Mohamed-Hinds, Nicel Molewa, Mathakane Morales, Miguel F. Murray, Steven G. Nuwegeld, Hans Parsons, Aaron R. Pascua, Robert Qin, Yuxiang Rath, Eleanor Razavi-Ghods, Nima Robnett, James Santos, Mario G. Sims, Peter Singh, Saurabh Storer, Dara Swarts, Hilton Tan, Jianrong van Wyngaarden, Pieter Zheng, Haoxuan Cosmology and Nongalactic Astrophysics The precise characterization and mitigation of systematic effects is one of the biggest roadblocks impeding the detection of the fluctuations of cosmological 21cm signals. Missing data in radio cosmological experiments, often due to radio frequency interference (RFI), poses a particular challenge to power spectrum analysis as it could lead to the ringing of bright foreground modes in Fourier space, heavily contaminating the cosmological signals. Here we show that the problem of missing data becomes even more arduous in the presence of systematic effects. Using a realistic numerical simulation, we demonstrate that partially flagged data combined with systematic effects can introduce significant foreground ringing. We show that such an effect can be mitigated through inpainting the missing data. We present a rigorous statistical framework that incorporates the process of inpainting missing data into a quadratic estimator of the 21cm power spectrum. Under this framework, the uncertainties associated with our inpainting method and its impact on power spectrum statistics can be understood. These results are applied to the latest Phase II observations taken by the Hydrogen Epoch of Reionization Array, forming a crucial component in power spectrum analyses as we move toward detecting 21cm signals in the ever more noisy RFI environment. |
| title | Impacts and Statistical Mitigation of Missing Data on the 21cm Power Spectrum: A Case Study with the Hydrogen Epoch of Reionization Array |
| topic | Cosmology and Nongalactic Astrophysics |
| url | https://arxiv.org/abs/2411.10529 |