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arXiv · 2205.09960

Generating extremely large-volume reionisation simulations

Bradley Greig·J. Stuart B. Wyithe·Steven G. Murray·Simon J. Mutch·Cathryn M. Trott
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Abstract

Preparing for the first detection of the cosmic 21-cm signal from large-scale interferometer experiments requires rigorous testing of the data analysis and reduction pipelines. To validate that these pipelines do not erroneously remove or add features that can mimic the cosmic signal (e.g. from side-lobes or large-scale power leakage), we require reionisation simulations larger than the experiments primary field of view. For an experiment such as the MWA, with a field of view of $\sim25^{2}$ deg.$^{2}$, this would require a simulation of several Gpcs, which is currently infeasible. To overcome this, we developed a simplified version of the semi-numerical reionisation simulation code 21CMFAST preferencing large volumes over some physical accuracy by assuming linear theory for structure formation. With this, we constructed a 7.5 Gpc comoving volume with voxel resolution of $\sim1.17$ cMpc tailored specifically to the binned spectral resolution of the MWA. This simulation was used for validating the pipelines for the 2020 MWA 21-cm power spectrum (PS) upper limits (Trott et al.). We then use this large-volume simulation to explore: (i) whether smaller volume simulations are biased by the missing large-scale modes, (ii) non-Gaussianity in estimates of the cosmic variance, (iii) biases in the recovered 21-cm PS following foreground wedge removal and (iv) the impact of tiling smaller volume simulations to achieve extremely large volumes. In summary, we find: (i) no biases from missing large-scale power, (ii) significant contribution from non-Gaussianity in the cosmic variance as expected following Mondal et al. (iii) an over-estimate of the 21-cm PS of 10-20 per cent following wedge mode excision for our particular model and (iv) tiling smaller volume simulations under-estimates the large-scale power and also the estimated cosmic variance.

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Bradley Greig, J. Stuart B. Wyithe, Steven G. Murray, Simon J. Mutch, Cathryn M. Trott. 2022-05-20. Generating extremely large-volume reionisation simulations. https://doi.org/10.1093/mnras%2Fstac2506

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