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Detection and extraction of signals from the epoch of reionization using higher order one-point statistics

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arxiv 0809.2428 v2 pith:CCKP4EAH submitted 2008-09-15 astro-ph

Detection and extraction of signals from the epoch of reionization using higher order one-point statistics

classification astro-ph
keywords reionizationforegroundsfrequencyimagesnoisesignaldetectionepoch
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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Detecting redshifted 21cm emission from neutral hydrogen in the early Universe promises to give direct constraints on the epoch of reionization (EoR). It will, though, be very challenging to extract the cosmological signal (CS) from foregrounds and noise which are orders of magnitude larger. Fortunately, the signal has some characteristics which differentiate it from the foregrounds and noise, and we suggest that using the correct statistics may tease out signatures of reionization. We generate mock datacubes simulating the output of the Low Frequency Array (LOFAR) EoR experiment. These cubes combine realistic models for Galactic and extragalactic foregrounds and the noise with three different simulations of the CS. We fit out the foregrounds, which are smooth in the frequency direction, to produce residual images in each frequency band. We denoise these images and study the skewness of the one-point distribution in the images as a function of frequency. We find that, under sufficiently optimistic assumptions, we can recover the main features of the redshift evolution of the skewness in the 21cm signal. We argue that some of these features - such as a dip at the onset of reionization, followed by a rise towards its later stages - may be generic, and give us a promising route to a statistical detection of reionization.

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  1. Probing initial isocurvature perturbation with 21cm one-point statistics

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    A Fisher forecast from 21cmFAST simulations shows 21cm variance can constrain the CDM isocurvature fraction to about 3e-4 with SKA, while skewness is an order of magnitude weaker.