"Author! Author!" : Shakespeare and biography

Original article can be found at: http://www.informaworld.com/smpp/title~content=t714579626~db=all Copyright Informa / Taylor & Francis Group. DOI: 10.1080/17450910902764454Since 1996, not a year has passed without the publication of at least one Shakespeare biography. Yet for many years the place of the author in the practice of understanding literary works has been problematized, and even on occasions eliminated. Criticism reads the “works”, and may or may not refer to an author whose “life” contributed to their meaning. Biography seeks the author in the works, the personality that precedes the works and gives them their characteristic shape and meaning. But the form of literary biography addresses the unusual kind of “life” that puts itself into “works”, and this is particularly challenging where the “works” predominate massively over the salient facts of the “life”. This essay surveys the current terrain of Shakespeare biography, and considers the key questions raised by the medium: can we know anything of Shakespeare's “personality” from the facts of his life and the survival of his works? What is the status of the kind of speculation that inevitably plays a part in biographical reconstruction? Are biographers in the end telling us as much about themselves as they tell us about Shakespeare?Peer reviewe

Robust statistics towards detection of the 21 cm signal from the Epoch of Reionization

© 2019 The Author(s) Published by Oxford University Press on behalf of the Royal Astronomical Society. We explore methods for robust estimation of the 21 cm signal from the Epoch of Reionization (EoR). A Kernel Density Estimator (KDE) is introduced for measuring the spatial temperature fluctuation power spectrum from the EoR. The KDE estimates the underlying probability distribution function of fluctuations as a function of spatial scale, and contains different systematic biases and errors to the typical approach to estimating the fluctuation power spectrum. Extraction of histograms of visibilities allows moments analysis to be used to discriminate foregrounds from 21 cm signal and thermal noise. We use the information available in the histograms, along with the statistical dis-similarity of foregrounds from two independent observing fields, to robustly separate foregrounds from cosmological signal, while making no assumptions about the Gaussianity of the signal. Using two independent observing fields to robustly discriminate signal from foregrounds is crucial for the analysis presented in this paper. We apply the techniques to 13 h of Murchison Widefield Array EoR data over two observing fields. We compare the output to that obtained with a comparative power spectrum estimation method, and demonstrate the reduced foreground contamination using this approach. Using the second moment obtained directly from the KDE distribution functions yields a factor of 2-3 improvement in power for k < 0.3 h Mpc-1 compared with a matched delay space power estimator, while weighting data by additional statistics does not offer significant improvement beyond that available for thermal noise-only weights

The impact of tandem redundant/sky-based calibration in MWA Phase II data analysis

Precise instrumental calibration is of crucial importance to 21-cm cosmology experiments. The Murchison Widefield Array's (MWA) Phase II compact configuration offers us opportunities for both redundant calibration and sky-based calibration algorithms; using the two in tandem is a potential approach to mitigate calibration errors caused by inaccurate sky models. The MWA Epoch of Reionization (EoR) experiment targets three patches of the sky (dubbed EoR0, EoR1, and EoR2) with deep observations. Previous work in Li et al. (2018) and (2019) studied the effect of tandem calibration on the EoR0 field and found that it yielded no significant improvement in the power spectrum (PS) over sky-based calibration alone. In this work, we apply similar techniques to the EoR1 field and find a distinct result: The improvements in the PS from tandem calibration are significant. To understand this result, we analyse both the calibration solutions themselves and the effects on the PS over three nights of EoR1 observations. We conclude that the presence of the bright radio galaxy Fornax A in EoR1 degrades the performance of sky-based calibration, which in turn enables redundant calibration to have a larger impact. These results suggest that redundant calibration can indeed mitigate some level of model incompleteness error

A new MWA limit on the 21 cm power spectrum at redshifts ∼13-17

Observations in the lowest Murchison Widefield Array (MWA) band between 75 and 100 MHz have the potential to constrain the distribution of neutral hydrogen in the intergalactic medium at redshift ∼13-17. Using 15 h of MWA data, we analyse systematics in this band such as radio-frequency interference (RFI), ionospheric and wide field effects. By updating the position of point sources, we mitigate the direction-independent calibration error due to ionospheric offsets. Our calibration strategy is optimized for the lowest frequency bands by reducing the number of direction-dependent calibrators and taking into account radio sources within a wider field of view. We remove data polluted by systematics based on the RFI occupancy and ionospheric conditions, finally selecting 5.5 h of the cleanest data. Using these data, we obtain 2σ upper limits on the 21 cm power spectrum in the range of 0.1 h Mpc-1 ≲ k ≲ 1 h Mpc-1 and at z = 14.2, 15.2, and 16.5, with the lowest limit being 6.3 × 106 mK2 at k=0.14 h Mpc-1 and at z = 15.2 with a possibility of a few per cent of signal loss due to direction-independent calibration

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

We compute the spherically averaged power spectrum from four seasons of data obtained for the Epoch of Reionization (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 h on EoR0 high band (3340 observations), yields a lowest measurement of (43 mK)2 = 1.8 × 103 mK2 at k = 0.14 h Mpc−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-min snapshots (453 h), 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 h). 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 8935 observations (298 h of data) to form integrated power spectra over the different fields, pointings, and redshift ranges