The fore ground transfer function for H I intensity mapping signal reconstruction: MeerKLASS and precision cosmology applications
dc.contributor.author | Cunnington, Steven | |
dc.contributor.author | Wolz, Laura | |
dc.contributor.author | Bull, Philip | |
dc.date.accessioned | 2023-07-04T07:58:49Z | |
dc.date.available | 2023-07-04T07:58:49Z | |
dc.date.issued | 2023 | |
dc.description.abstract | Blind cleaning methods are currently the preferred strategy for handling foreground contamination in single-dish H I intensity mapping surv e ys. Despite the increasing sophistication of blind techniques, some signal loss will be inevitable across all scales. Constructing a corrective transfer function using mock signal injection into the contaminated data has been a practice relied on for H I intensity mapping experiments. Ho we ver, assessing whether this approach is viable for future intensity mapping surv e ys, where precision cosmology is the aim, remains unexplored. In this work, using simulations, we validate for the first time the use of a foreground transfer function to reconstruct power spectra of foreground-cleaned low-redshift intensity maps and look to e xpose an y limitations. We rev eal that ev en when aggressiv e fore ground cleaning is required, which causes > 50 per cent ne gativ e bias on the largest scales, the power spectrum can be reconstructed using a transfer function to within sub-per cent accuracy. We specifically outline the recipe for constructing an unbiased transfer function, highlighting the pitfalls if one deviates from this recipe, and also correctly identify how a transfer function should be applied in an autocorrelation power spectrum. We validate a method that utilizes the transfer function variance for error estimation in foreground-cleaned power spectra. Finally, we demonstrate how incorrect fiducial parameter assumptions (up to ±100 per cent bias) in the generation of mocks, used in the construction of the transfer function, do not significantly bias signal reconstruction or parameter inference (inducing < 5 per cent bias in reco v ered values). | en_US |
dc.identifier.citation | Cunnington, S. et al. (2023). The fore ground transfer function for H I intensity mapping signal reconstruction: MeerKLASS and precision cosmology applications. Monthly Notices of the Royal Astronomical Society, Monthly Notices of the Royal Astronomical Society, 523(2), 2453-2477. https://doi.org/10.1093/mnras/stad1567 | en_US |
dc.identifier.issn | 1365-2966 | |
dc.identifier.issn | https://doi.org/10.1093/mnras/stad1567 | |
dc.identifier.uri | http://hdl.handle.net/10566/9186 | |
dc.language.iso | en | en_US |
dc.publisher | Oxford University Press | en_US |
dc.subject | Astronomy | en_US |
dc.subject | Physics | en_US |
dc.subject | Statistics studies | en_US |
dc.subject | Cosmology | en_US |
dc.subject | Data analysis | en_US |
dc.title | The fore ground transfer function for H I intensity mapping signal reconstruction: MeerKLASS and precision cosmology applications | en_US |
dc.type | Article | en_US |
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