Statistical Recovery of 21 cm Visibilities and Their Power Spectra with Gaussian-constrained Realizations and Gibbs Sampling
Radio interferometers designed to probe the 21 cm signal from Cosmic Dawn and the Epoch of Reionization must contend with systematic effects that make it difficult to achieve sufficient dynamic range to separate the 21 cm signal from foreground emission and other effects. For instance, the instrumen...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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IOP Publishing
2023-01-01
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| Series: | The Astrophysical Journal Supplement Series |
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| Online Access: | https://doi.org/10.3847/1538-4365/acc324 |
| _version_ | 1797696200983445504 |
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| author | Fraser Kennedy Philip Bull Michael J. Wilensky Jacob Burba Samir Choudhuri |
| author_facet | Fraser Kennedy Philip Bull Michael J. Wilensky Jacob Burba Samir Choudhuri |
| author_sort | Fraser Kennedy |
| collection | DOAJ |
| description | Radio interferometers designed to probe the 21 cm signal from Cosmic Dawn and the Epoch of Reionization must contend with systematic effects that make it difficult to achieve sufficient dynamic range to separate the 21 cm signal from foreground emission and other effects. For instance, the instrument’s chromatic response modulates the otherwise spectrally smooth foregrounds, making them difficult to model, while a significant fraction of the data must be excised due to the presence of radio-frequency interference, leaving gaps in the data. Errors in modeling the (modulated and gappy) foregrounds can easily generate spurious contamination of what should otherwise be 21 cm signal-dominated modes. Various approaches have been developed to mitigate these issues by, for example, using nonparametric reconstruction of the foregrounds, in-painting the gaps, and weighting the data to reduce the level of contamination. We present a Bayesian statistical method that combines these approaches, using the coupled techniques of Gaussian-constrained realizations and Gibbs sampling. This provides a way of drawing samples from the joint posterior distribution of the 21 cm signal modes and their power spectrum in the presence of gappy data and an uncertain foreground model in a computationally scalable manner. The data are weighted by an inverse covariance matrix that is estimated as part of the inference, along with a foreground model that can then be marginalized over. We demonstrate the application of this technique on a simulated Hydrogen Epoch of Reionization Array–like delay spectrum analysis, comparing three different approaches for accounting for the foreground components. |
| first_indexed | 2024-03-12T03:23:04Z |
| format | Article |
| id | doaj.art-6de41f51097e4f1abb36f686663dd278 |
| institution | Directory Open Access Journal |
| issn | 0067-0049 |
| language | English |
| last_indexed | 2024-03-12T03:23:04Z |
| publishDate | 2023-01-01 |
| publisher | IOP Publishing |
| record_format | Article |
| series | The Astrophysical Journal Supplement Series |
| spelling | doaj.art-6de41f51097e4f1abb36f686663dd2782023-09-03T13:48:10ZengIOP PublishingThe Astrophysical Journal Supplement Series0067-00492023-01-0126622310.3847/1538-4365/acc324Statistical Recovery of 21 cm Visibilities and Their Power Spectra with Gaussian-constrained Realizations and Gibbs SamplingFraser Kennedy0https://orcid.org/0000-0002-5883-6543Philip Bull1https://orcid.org/0000-0001-5668-3101Michael J. Wilensky2https://orcid.org/0000-0001-7716-9312Jacob Burba3https://orcid.org/0000-0002-8465-9341Samir Choudhuri4https://orcid.org/0000-0002-2338-935XAstronomy Unit, Queen Mary University of London , Mile End Road, London, E1 4NS, UK ; f.kennedy@qmul.ac.ukJodrell Bank Centre for Astrophysics, University of Manchester , Manchester, M13 9PL, UK; Department of Physics and Astronomy, University of Western Cape , Cape Town, 7535, South AfricaJodrell Bank Centre for Astrophysics, University of Manchester , Manchester, M13 9PL, UKJodrell Bank Centre for Astrophysics, University of Manchester , Manchester, M13 9PL, UKCentre for Strings, Gravitation and Cosmology, Department of Physics, Indian Institute of Technology Madras , Chennai, 600036, IndiaRadio interferometers designed to probe the 21 cm signal from Cosmic Dawn and the Epoch of Reionization must contend with systematic effects that make it difficult to achieve sufficient dynamic range to separate the 21 cm signal from foreground emission and other effects. For instance, the instrument’s chromatic response modulates the otherwise spectrally smooth foregrounds, making them difficult to model, while a significant fraction of the data must be excised due to the presence of radio-frequency interference, leaving gaps in the data. Errors in modeling the (modulated and gappy) foregrounds can easily generate spurious contamination of what should otherwise be 21 cm signal-dominated modes. Various approaches have been developed to mitigate these issues by, for example, using nonparametric reconstruction of the foregrounds, in-painting the gaps, and weighting the data to reduce the level of contamination. We present a Bayesian statistical method that combines these approaches, using the coupled techniques of Gaussian-constrained realizations and Gibbs sampling. This provides a way of drawing samples from the joint posterior distribution of the 21 cm signal modes and their power spectrum in the presence of gappy data and an uncertain foreground model in a computationally scalable manner. The data are weighted by an inverse covariance matrix that is estimated as part of the inference, along with a foreground model that can then be marginalized over. We demonstrate the application of this technique on a simulated Hydrogen Epoch of Reionization Array–like delay spectrum analysis, comparing three different approaches for accounting for the foreground components.https://doi.org/10.3847/1538-4365/acc324Bayesian statisticsReionizationInterferometry |
| spellingShingle | Fraser Kennedy Philip Bull Michael J. Wilensky Jacob Burba Samir Choudhuri Statistical Recovery of 21 cm Visibilities and Their Power Spectra with Gaussian-constrained Realizations and Gibbs Sampling The Astrophysical Journal Supplement Series Bayesian statistics Reionization Interferometry |
| title | Statistical Recovery of 21 cm Visibilities and Their Power Spectra with Gaussian-constrained Realizations and Gibbs Sampling |
| title_full | Statistical Recovery of 21 cm Visibilities and Their Power Spectra with Gaussian-constrained Realizations and Gibbs Sampling |
| title_fullStr | Statistical Recovery of 21 cm Visibilities and Their Power Spectra with Gaussian-constrained Realizations and Gibbs Sampling |
| title_full_unstemmed | Statistical Recovery of 21 cm Visibilities and Their Power Spectra with Gaussian-constrained Realizations and Gibbs Sampling |
| title_short | Statistical Recovery of 21 cm Visibilities and Their Power Spectra with Gaussian-constrained Realizations and Gibbs Sampling |
| title_sort | statistical recovery of 21 cm visibilities and their power spectra with gaussian constrained realizations and gibbs sampling |
| topic | Bayesian statistics Reionization Interferometry |
| url | https://doi.org/10.3847/1538-4365/acc324 |
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