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Register a new userThe 21cm bispectrum during reionization: a tracer of the ionization topology
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We compute the bispectra of the 21cm signal during the Epoch of Reionization for three different reionization scenarios that are based on a dark matter N-body simulation combined with a self-consistent, semi-numerical model of galaxy evolution and reionization. Our reionization scenarios differ in their trends of ionizing escape fractions ($f_mathrm{esc}$) with the underlying galaxy properties and cover the physically plausible range, i.e. $f_mathrm{esc}$ effectively decreasing, being constant, or increasing with halo mass. We find the 21cm bispectrum to be sensitive to the resulting ionization topologies that significantly differ in their size distribution of ionized and neutral regions throughout reionization. From squeezed to stretched triangles, the 21cm bispectra features a change of sign from negative to positive values, with ionized and neutral regions representing below-average and above-average concentrations contributing negatively and positively, respectively. The position of the change of sign provides a tracer of the size distribution of the ionized and neutral regions, and allows us to identify three major regimes that the 21cm bispectrum undergoes during reionization. In particular the regime during the early stages of reionization, where the 21cm bispectrum tracks the peak of the size distribution of the ionized regions, provides exciting prospects for pinning down reionization with the forthcoming Square Kilometre Array.
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The high-redshift 21 cm signal from the Epoch of Reionization (EoR) is a promising observational probe of the early universe. Current- and next-generation radio interferometers such as the Hydrogen Epoch of Reionization Array (HERA) and Square Kilometre Array (SKA) are projected to measure the 21 cm auto power spectrum from the EoR. Another observational signal of this era is the kinetic Sunyaev-Zeldovich (kSZ) signal in the cosmic microwave background (CMB), which will be observed by the upcoming Simons Observatory (SO) and CMB-S4 experiments. The 21 cm signal and the contribution to the kSZ from the EoR are expected to be anti-correlated, the former coming from regions of neutral gas in the intergalactic medium and the latter coming from ionized regions. However, the naive cross-correlation between the kSZ and 21 cm maps suffers from a cancellation that occurs because ionized regions are equally likely to be moving toward or away from the observer and so there is no net correlation with the 21 cm signal. We present here an investigation of the 21 cm-kSZ-kSZ bispectrum, which should not suffer the same cancellation as the simple two-point cross-correlation. We show that there is a significant and non-vanishing signal that is sensitive to the reionization history, suggesting the statistic may be used to confirm or infer the ionization fraction as a function of redshift. In the absence of foreground contamination, we forecast that this signal is detectable at high statistical significance with HERA and SO. The bispectrum we study suffers from the fact that the kSZ signal is sensitive only to Fourier modes with long-wavelength line-of-sight components, which are generally lost in the 21 cm data sets owing to foreground contamination. We discuss possible strategies for alleviating this contamination, including an alternative four-point statistic that may help circumvent this issue.
The cross-correlation between fluctuations in the electron scattering optical depth $tau_{rm es}$ as probed by future Cosmic Microwave Background (CMB) experiments, and fluctuations in the 21cm differential brightness temperature $Delta T_{rm 21cm}$ as probed by ground-based radio interferometers, will trace the reionization history of the Universe. In particular, the $tau_{rm es}-$21cm cross-correlation should yield a determination of the characteristic bubble size distribution and ionization fraction as a function of redshift. When assuming that the cross-correlation signal is limited by instrumental noise rather than by foregrounds, we estimate its potential detectability by upcoming experiments. Specifically, the combination of HERA and Simons Observatory, CMB-S4 and PICO should yield a signal-to-noise ratio around 3 - 6, while and the exploitation of the SKA should increase it to 10-20. Finally, we have discussed how such levels of detectability can be affected when (simply modeled) 21cm foregrounds are present. For the most promising PICO$times$SKA configuration, an efficiency of foreground removal to a level of $7times 10^{-4}$ is needed to achieve a $5sigma$ detection of the cross-correlation signal; in addition, safe avoidance of foreground contamination in the line-of-sight Fourier modes above $0.03 ,h,rm Mpc^{-1}$ would guarantee a detection significance around $3sigma$.
Increasing evidence suggests that cosmological sheets, filaments, and voids may be substantially magnetized today. The origin of magnetic fields in the intergalactic medium (IGM) is, however, currently uncertain. It seems well known that non-standard extensions to the physics of the standard model can provide mechanisms susceptible of magnetizing the universe at large. Perhaps less well known is the fact that standard, classical physics of matter--radiation interactions actually possesses the same potential. We discuss a magnetogenesis mechanism based on the exchange of momentum between hard photons and electrons in an inhomogeneous IGM. Operating in the neighborhood of ionizing sources during the epoch of reionization, this mechanism is capable of generating magnetic seeds of relevant strengths over scales comparable to the distance between ionizing sources. In addition, summing up the contributions of all ionizing sources and taking into account the distribution of gas inhomogeneities, we show that this mechanism leaves the IGM, at the end of reionization, with a level of magnetization that might account, when amplification mechanisms take over, for the magnetic fields strengths in the current cosmic web.
Detection of the redshifted 21cm-line signal from neutral hydrogen in the intergalactic medium (IGM) during the Epoch of Reionization (EoR) is complicated by intense foregrounds such as galactic synchrotron and extragalactic radio galaxies. The 21cm-Lyman-$alpha$ emitter(LAE) cross-correlation is one of the tools available to reduce the foreground effects because the foreground emission from such radio sources is statistically independent of LAE distribution. LAE surveys during the EoR at redshifts $z=6.6$ and $7.3$ are ongoing by the Subaru Hyper Suprime-Cam (HSC). Additionally, Prime Focus Spectrograph (PFS) will provide precise redshift information of the LAEs discovered by the HSC survey. In this paper, we investigate the detectability of the 21cm signal with the 21cm-LAE cross-correlation by using our improved reionization simulations. We also focus on the error budget and evaluate it quantitatively in order to consider a strategy to improve the signal-to-noise ratio. In addition, we explore an expansion of the LAE survey to suggest optimal survey parameters and show a potential to measure a characteristic size of ionized bubbles via the turnover scale of the cross-power spectrum. As a result, we find that the Murchison Widefield Array (MWA) has ability to detect the cross-power spectrum signal on large scales by combining LAE Deep field survey of HSC. We also show that the sensitivity is improved dramatically at small scales by adding redshift information from the PFS measurements. The Square Kilometre Array (SKA) has a potential to measure the turnover scale with an accuracy of $6times10^{-3}~{rm Mpc^{-1}}$.
We propose a deep learning analyzing technique with convolutional neural network (CNN) to predict the evolutionary track of the Epoch of Reionization (EoR) from the 21-cm differential brightness temperature tomography images. We use 21cmFAST, a fast semi-numerical cosmological 21-cm signal simulator, to produce mock 21-cm maps between $z=6 sim 13$. We then apply two observational effects into those 21-cm maps, such as instrumental noise and limit of (spatial and depth) resolution somewhat suitable for realistic choices of the Square Kilometre Array (SKA). We design our deep learning model with CNN to predict the sliced-averaged neutral hydrogen fraction from the given 21-cm map. The estimated neutral fraction from our CNN model has a great agreement with its true value even after coarsely smoothing with broad beamsize and frequency bandwidth, and also heavily covered by noise with narrow. Our results have shown that deep learning analyzing method has a large potential to efficiently reconstruct the EoR history from the 21-cm tomography surveys in future.
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