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Register a new userStudying the morphology of reionisation with the triangle correlation function of phases
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We present a new statistical tool, called the triangle correlation function (TCF), inspired by the earlier work of Obreschkow et al. It is derived from the three-point correlation function and aims to probe the characteristic scale of ionized regions during the epoch of reionization from 21cm interferometric observations. Unlike most works, which focus on power spectrum, i.e. amplitude information, our statistic is based on the information we can extract from the phases of the Fourier transform of the ionization field. In this perspective, it may benefit from the well-known interferometric concept of closure phases. We find that this statistical estimator performs very well on simple ionization fields. For example, with well-defined fully ionized discs, there is a peaking scale, which we can relate to the radius of the ionized bubbles. We explore the robustness of the TCF when observational effects such as angular resolution and noise are considered. We also get interesting results on fields generated by more elaborate simulations such as 21CMFAST. Although the variety of sources and ionized morphologies in the early stages of the process make its interpretation more challenging, the nature of the signal can tell us about the stage of reionization. Finally, and in contrast to other bubble size distribution algorithms, we show that the TCF can resolve two different characteristic scales in a given map.
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We explore methods for robust estimation of the 21 cm signal from the Epoch of Reionisation (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 hours of Murchison Widefield Array (MWA) 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 < 0.3hMpc^{-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.
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The (re)ionisation of hydrogen in the early universe has a profound effect on the formation of the first galaxies: by raising the gas temperature and pressure, it prevents gas from cooling into small haloes thus affecting the abundance of present-day small galaxies. Using the Galform semi-analytic model of galaxy formation, we show that two key aspects of the reionisation process -- when reionisation takes place and the characteristic scale below which it suppresses galaxy formation -- are imprinted in the luminosity function of dwarf galaxies. We focus on the luminosity function of satellites of galaxies like the Milky Way and the LMC, which is easier to measure than the luminosity function of the dwarf population as a whole. Our results show that the details of these two characteristic properties of reionisation determine the shape of the luminosity distribution of satellites in a unique way, and is largely independent of the other details of the galaxy formation model. Our models generically predict a bimodality in the distribution of satellites as a function of luminosity: a population of faint satellites and population of bright satellites separated by a valley forged by reionisation. We show that this bimodal distribution is present at high statistical significance in the combined satellite luminosity function of the Milky Way and M31. We make predictions for the expected number of satellites around LMC-mass dwarfs where the bimodality may also be measurable in future observational programmes. Our preferred model predicts a total of $26 pm 10$ (68 per cent confidence) satellites brighter than ${rm M}_V=0$ in LMC-mass systems.
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