Browsing by Author "Burba, Jacob"

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    Statistical estimation of full-sky radio maps from 21 cm array visibility data using gaussian constrained realizations
    (Oxford University Press, 2024) Glasscock, Katrine A.; Bull, Philip; Burba, Jacob
    An important application of next-generation wide-field radio interferometers is making high dynamic range maps of radio emission. Traditional deconvolution methods like CLEAN can give poor recovery of diffuse structure, prompting the development of wide-field alternatives like Direct Optimal Mapping and m-mode analysis. In this paper, we propose an alternative Bayesian method to infer the coefficients of a full-sky spherical harmonic basis for a drift-scan telescope with potentially thousands of baselines that can precisely encode the uncertainties and correlations between the parameters used to build the recovered image. We use Gaussian constrained realizations (GCR) to efficiently draw samples of the spherical harmonic coefficients, despite the very large parameter space and extensive sky-regions of missing data. Each GCR solution provides a complete, statistically consistent gap-free realization of a full-sky map conditioned on the available data, even when the interferometer’s field of view is small. Many realizations can be generated and used for further analysis and robust propagation of statistical uncertainties. In this paper, we present the mathematical formalism of the spherical harmonic GCR method for radio interferometers. We focus on the recovery of diffuse emission as a use case, along with validation of the method against simulations with a known diffuse emission component.
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    Statistical recovery of 21 cm visibilities and their power spectra with gaussian-constrained realizations and gibbs sampling
    (The Astrophysical Journal Supplement Series, 2023) Bull, Philip; Kennedy, Fraser; Wilensky, Michael J; Burba, Jacob; Choudhuri, Samir
    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.