%0 Generic %1 greig2022detecting %A Greig, Bradley %A Ting, Yuan-Sen %A Kaurov, Alexander A. %D 2022 %K library %T Detecting the non-Gaussianity of the 21-cm signal during reionisation with the Wavelet Scattering Transform %U http://arxiv.org/abs/2207.09082 %X Detecting the 21-cm hyperfine transition from neutral hydrogen in the intergalactic medium is our best probe for understanding the astrophysical processes driving the Epoch of Reionisation (EoR). The primary means for a detection of this 21-cm signal is through a statistical measurement of the spatial fluctuations using the 21-cm power spectrum (PS). However, the 21-cm signal is non-Gaussian meaning the PS, which only measures the Gaussian fluctuations, is sub-optimal for characterising all of the available information. The upcoming Square Kilometre Array (SKA) will perform a deep, 1000 hr observation over 100 deg$.^2$ specifically designed to recover direct images of the 21-cm signal. In this work, we use the Wavelet Scattering Transform (WST) to extract the non-Gaussian information directly from these two-dimensional images of the 21-cm signal. The key advantage of the WST is its stability with respect to statistical noise for measuring non-Gaussian information, unlike the bispectrum whose statistical noise diverges. We introduce a novel method to isolate this non-Gaussian information from mock 21-cm images and demonstrate its detection at 150 (177)~MHz ($z\sim8.5$ and $\sim7$) for a fiducial model with signal-to-noise of $\sim$5~(8) assuming perfect foreground removal and $\sim2$~(3) assuming foreground wedge avoidance.

@misc{greig2022detecting, abstract = {Detecting the 21-cm hyperfine transition from neutral hydrogen in the intergalactic medium is our best probe for understanding the astrophysical processes driving the Epoch of Reionisation (EoR). The primary means for a detection of this 21-cm signal is through a statistical measurement of the spatial fluctuations using the 21-cm power spectrum (PS). However, the 21-cm signal is non-Gaussian meaning the PS, which only measures the Gaussian fluctuations, is sub-optimal for characterising all of the available information. The upcoming Square Kilometre Array (SKA) will perform a deep, 1000 hr observation over 100 deg$.^{2}$ specifically designed to recover direct images of the 21-cm signal. In this work, we use the Wavelet Scattering Transform (WST) to extract the non-Gaussian information directly from these two-dimensional images of the 21-cm signal. The key advantage of the WST is its stability with respect to statistical noise for measuring non-Gaussian information, unlike the bispectrum whose statistical noise diverges. We introduce a novel method to isolate this non-Gaussian information from mock 21-cm images and demonstrate its detection at 150 (177)~MHz ($z\sim8.5$ and $\sim7$) for a fiducial model with signal-to-noise of $\sim$5~(8) assuming perfect foreground removal and $\sim2$~(3) assuming foreground wedge avoidance.}, added-at = {2022-07-20T09:28:15.000+0200}, author = {Greig, Bradley and Ting, Yuan-Sen and Kaurov, Alexander A.}, biburl = {https://www.bibsonomy.org/bibtex/2522dfeefa629ac565bb9a404c0ba683e/gpkulkarni}, description = {Detecting the non-Gaussianity of the 21-cm signal during reionisation with the Wavelet Scattering Transform}, interhash = {5fc5a0a621ac213af8d045109a8065db}, intrahash = {522dfeefa629ac565bb9a404c0ba683e}, keywords = {library}, note = {cite arxiv:2207.09082Comment: 17 pages, 10 figures and 1 table. Submitted to MNRAS, comments welcome}, timestamp = {2022-07-20T09:28:15.000+0200}, title = {Detecting the non-Gaussianity of the 21-cm signal during reionisation with the Wavelet Scattering Transform}, url = {http://arxiv.org/abs/2207.09082}, year = 2022 }