The FHD/εppsilon Epoch of Reionisation power spectrum pipeline

Barry, N.; Beardsley, Adam P.; Byrne, R.; Hazelton, B. J.; Morales, M. F.; Pober, Jonathan C.; Sullivan, M.

doi:10.1017/pasa.2019.21

Cited by 57 publications

(129 citation statements)

References 72 publications

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“…It is important to ensure that the normalisation is correct, and that signal is not being lost due to coherence of coherentlygridded data. The former can be ensured via matching of different approaches to calculating the noise, and to internal consistency between independent MWA analysis pipelines ( Barry et al 2019a). The latter can be achieved using a signal simulation; ensuring that the input power spectrum is recovered after passing through the CHIPS pipeline.…”

Section: Simulationsmentioning

confidence: 99%

Deep multiredshift limits on Epoch of Reionization 21 cm power spectra from four seasons of Murchison Widefield Array observations

Trott

Jordan

Midgley³

et al. 2020

Monthly Notices of the Royal Astronomical Society

204

139

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We compute the spherically-averaged power spectrum from four seasons of data obtained for the Epoch of Reionisation (EoR) project observed with the Murchison Widefield Array (MWA). We measure the EoR power spectrum over k = 0.07 − 3.0 hMpc −1 at redshifts z = 6.5 − 8.7. The largest aggregation of 110 hours on EoR0 high-band (3,340 observations), yields a lowest measurement of (43 mK) 2 = 1.8×10 3 mK 2 at k=0.14 hMpc −1 and z = 6.5 (2σ thermal noise plus sample variance). Using the Real-Time System to calibrate and the CHIPS pipeline to estimate power spectra, we select the best observations from the central five pointings within the 2013-2016 observing seasons, observing three independent fields and in two frequency bands. This yields 13,591 2-minute snapshots (453 hours), based on a quality assurance metric that measures ionospheric activity. We perform another cut to remove poorly-calibrated data, based on power in the foreground-dominated and EoR-dominated regions of the twodimensional power spectrum, reducing the set to 12,569 observations (419 hours). These data are processed in groups of 20 observations, to retain the capacity to identify poor data, and used to analyse the evolution and structure of the data over field, frequency, and data quality. We subsequently choose the cleanest 8,935 observations (298 hours of data) to form integrated power spectra over the different fields, pointings and redshift ranges.

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Section: Simulationsmentioning

confidence: 99%

Deep multiredshift limits on Epoch of Reionization 21 cm power spectra from four seasons of Murchison Widefield Array observations

Trott

Jordan

Midgley³

et al. 2020

Monthly Notices of the Royal Astronomical Society

204

139

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“…In our estimation of added contamination due to beam modelling errors, we overestimate the expected errors for the MWA EoR experiment. Both MWA EoR pipelines RTS/CHIPS (Mitchell et al 2008;Trott et al 2016) and FHD/ ppsilon (Sullivan et al 2012;Jacobs et al 2016;Barry et al 2019) incorporate direction dependent calibration. RTS/CHIPS uses information about broken dipoles explicitly to better model individual MWA tile beams.…”

Section: Discussionmentioning

confidence: 99%

Calibration and 21-cm power spectrum estimation in the presence of antenna beam variations

Joseph

Trott

Wayth

et al. 2019

Monthly Notices of the Royal Astronomical Society

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Detecting a signal from the Epoch of Reionisation (EoR) requires an exquisite understanding of galactic and extra-galactic foregrounds, low frequency radio instruments, instrumental calibration, and data analysis pipelines. In this work we build upon existing work that aims to understand the impact of calibration errors on 21-cm power spectrum (PS) measurements. It is well established that calibration errors have the potential to inhibit EoR detections by introducing additional spectral features that mimic the structure of EoR signals. We present a straightforward way to estimate the impact of a wide variety of modelling residuals in EoR PS estimation. We apply this framework to the specific case of broken dipoles in Murchison Widefield Array (MWA) to understand its effect and estimate its impact on PS estimation. Combining an estimate of the percentage of MWA tiles that have at least one broken dipole (15%-40%) with an analytic description of beam errors induced by such dipoles, we compute the residuals of the foregrounds after calibration and source subtraction. We find that that incorrect beam modelling introduces bias in the 2D-PS on the order of ∼ 10 3 mK 2 h −3 Mpc −3 , which is on the order of current lowest limits. Determining the accuracy of both current beam models and direction dependent calibration pipelines is therefore crucial in our search for an EoR signal.

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“…The gains are calibrated on the strongest source, before that source is peeled (subtracted) from the data, and the next strongest source is used to refine the calibration, and so on until it is deemed that enough bright sources have been removed, usually a few hundred to a thousand at most. The other MWA calibration pipeline, Fast Holographic Deconvolution (FHD) [146], uses the MWA extragalactic catalogue GLEAM [61] to calibrate gains, modelling all sources out to 1% beam level in the primary lobe, amounting to approximately 50000 sources [7] and then removing a smaller population of them from the data. Similarly, LOFAR has built up a sky model over several years using the highest resolution LO-FAR images and subtracts the sources in visibility space also [167,166].…”

Section: Bright Source Removalmentioning

confidence: 99%

“…The FHD [146] and εpsilon [7] pipeline builds a sky model of point sources based on a golden set of data, including all sources above a floor limit within the primary beam of the instrument, and those beyond the primary beam if they are above 1% of the maximum primary beam level. This point source model is used in calibration in a similar way to LOFAR, and contains about 7000 sources as of 2016 [9].…”

Section: Foreground Avoidance and Suppressionmentioning

confidence: 99%

Foregrounds and Their Mitigation

Chapman¹,

Jelić²

2019

The Cosmic 21-Cm Revolution

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The low-frequency radio sky is dominated by the diffuse synchrotron emission of our Galaxy and extragalactic radio sources related to Active Galactic Nuclei and star-forming galaxies. This foreground emission is much brighter than the cosmological 21 cm emission from the Cosmic Dawn and Epoch of Reionization. Studying the physical properties of the foregrounds is therefore of fundamental importance for their mitigation in the cosmological 21 cm experiments. This chapter gives a comprehensive overview of the foregrounds and our current state-of-the-art knowledge about their mitigation.

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The FHD/εppsilon Epoch of Reionisation power spectrum pipeline

Cited by 57 publications

References 72 publications

Deep multiredshift limits on Epoch of Reionization 21 cm power spectra from four seasons of Murchison Widefield Array observations

Deep multiredshift limits on Epoch of Reionization 21 cm power spectra from four seasons of Murchison Widefield Array observations

Calibration and 21-cm power spectrum estimation in the presence of antenna beam variations

Foregrounds and Their Mitigation

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