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Register a new userGridded and direct Epoch of Reionisation bispectrum estimates using the Murchison Widefield Array
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We apply two methods to estimate the 21~cm bispectrum from data taken within the Epoch of Reionisation (EoR) project of the Murchison Widefield Array (MWA). Using data acquired with the Phase II compact array allows a direct bispectrum estimate to be undertaken on the multiple redundantly-spaced triangles of antenna tiles, as well as an estimate based on data gridded to the $uv$-plane. The direct and gridded bispectrum estimators are applied to 21 hours of high-band (167--197~MHz; $z$=6.2--7.5) data from the 2016 and 2017 observing seasons. Analytic predictions for the bispectrum bias and variance for point source foregrounds are derived. We compare the output of these approaches, the foreground contribution to the signal, and future prospects for measuring the bispectra with redundant and non-redundant arrays. We find that some triangle configurations yield bispectrum estimates that are consistent with the expected noise level after 10 hours, while equilateral configurations are strongly foreground-dominated. Careful choice of triangle configurations may be made to reduce foreground bias that hinders power spectrum estimators, and the 21~cm bispectrum may be accessible in less time than the 21~cm power spectrum for some wave modes, with detections in hundreds of hours.
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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 $k= 0.07-3.0~h$Mpc$^{-1}$ 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$times$10$^3$ mK$^2$ at $k$=0.14~$h$Mpc$^{-1}$ and $z=6.5$ (2$sigma$ 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 two-dimensional 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.
Structure imprinted in foreground extragalactic point sources by ionospheric refraction has the potential to contaminate Epoch of Reionisation (EoR) power spectra of the 21~cm emission line of neutral hydrogen. The alteration of the spatial and spectral structure of foreground measurements due to total electron content (TEC) gradients in the ionosphere create a departure from the expected sky signal. We present a general framework for understanding the signatures of ionospheric behaviour in the two-dimensional (2D) neutral hydrogen power spectrum measured by a low-frequency radio interferometer. Two primary classes of ionospheric behaviour are considered, corresponding to dominant modes observed in Murchison Widefield Array (MWA) EoR data; namely, anisotropic structured wave behaviour, and isotropic turbulence. Analytic predictions for power spectrum bias due to this contamination are computed, and compared with simulations. We then apply the ionospheric metric described in Jordan et al. (2017) to study the impact of ionospheric structure on MWA data, by dividing MWA EoR datasets into classes with good and poor ionospheric conditions, using sets of matched 30-minute observations from 2014 September. The results are compared with the analytic and simulated predictions, demonstrating the observed bias in the power spectrum when the ionosphere is active (displays coherent structures or isotropic turbulence). The analysis demonstrates that unless ionospheric activity can be quantified and corrected, active data should not be included in EoR analysis in order to avoid systematic biases in cosmological power spectra. When data are corrected with a model formed from the calibration information, bias reduces below the expected 21~cm signal level. Data are considered `quiet when the median measured source position offsets are less than 10-15~arcseconds.
In this paper we build upon recent work in the radio astronomy community to experimentally demonstrate the viability of passive radar for Space Situational Awareness. Furthermore, we show that the six state parameters of objects in orbit may be measured and used to perform orbit characterisation/estimation.
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