On the Conditional Distribution of a Multivariate Normal given a Transformation - the Linear Case

We show that the orthogonal projection operator onto the range of the adjoint of a linear operator $T$ can be represented as $UT,$ where $U$ is an invertible linear operator. Using this representation we obtain a decomposition of a Normal random vector $Y$ as the sum of a linear transformation of $Y$ that is independent of $TY$ and an affine transformation of $TY$. We then use this decomposition to prove that the conditional distribution of a Normal random vector $Y$ given a linear transformation $\mathcal{T}Y$ is again a multivariate Normal distribution. This result is equivalent to the well-known result that given a $k$-dimensional component of a $n$-dimensional Normal random vector, where $k<n$, the conditional distribution of the remaining $\left(n-k\right)$-dimensional component is a $\left(n-k\right)$-dimensional multivariate Normal distribution, and sets the stage for approximating the conditional distribution of $Y$ given $g\left(Y\right)$, where $g$ is a continuously differentiable vector field.Comment: 2/6/18: Updated the proof of Theorem 4 & added a corollary. arXiv admin note: text overlap with arXiv:1612.0121

Statistics of the epoch of reionization (EoR) 21-cm signal -- II. The evolution of the power spectrum error-covariance

The EoR 21-cm signal is expected to become highly non-Gaussian as reionization progresses. This severely affects the error-covariance of the EoR 21-cm power spectrum which is important for predicting the prospects of a detection with ongoing and future experiments. Most earlier works have assumed that the EoR 21-cm signal is a Gaussian random field where (1) the error variance depends only on the power spectrum and the number of Fourier modes in the particular $k$ bin, and (2) the errors in the different $k$ bins are uncorrelated. Here we use an ensemble of simulated 21-cm maps to analyze the error-covariance at various stages of reionization. We find that even at the very early stages of reionization ($\bar{x}_{\rm HI} \sim 0.9$) the error variance significantly exceeds the Gaussian predictions at small length-scales ($k > 0.5 \,{\rm Mpc}^{-1}$) while they are consistent at larger scales. The errors in most $k$ bins (both large and small scales), are however found to be correlated. Considering the later stages ($\bar{x}_{\rm HI} = 0.15$), the error variance shows an excess in all $k$ bins within $k \ge 0.1 \, {\rm Mpc}^{-1}$, and it is around $200$ times larger than the Gaussian prediction at $k \sim 1 \, {\rm Mpc}^{-1}$. The errors in the different $k$ bins are all also highly correlated, barring the two smallest $k$ bins which are anti-correlated with the other bins. Our results imply that the predictions for different 21-cm experiments based on the Gaussian assumption underestimate the errors, and it is necessary to incorporate the non-Gaussianity for more realistic predictions.Comment: Published in Monthly Notices of the Royal Astronomical Society (MNRAS). Available at "this URL http://dx.doi.org/10.1093/mnras/stw2599

The effect of peculiar velocities on the epoch of reionization (EoR) 21-cm signal

We have used semi-numerical simulations of reionization to study the behaviour of the power spectrum of the EoR 21-cm signal in redshift space. We have considered two models of reionization, one which has homogeneous recombination (HR) and the other incorporating inhomogeneous recombination (IR). We have estimated the observable quantities --- quadrupole and monopole moments of HI power spectrum at redshift space from our simulated data. We find that the magnitude and nature of the ratio between the quadrupole and monopole moments of the power spectrum ($P^s_2 /P^s_0$) can be a possible probe for the epoch of reionization. We observe that this ratio becomes negative at large scales for $x_{HI} \leq 0.7$ irrespective of the reionization model, which is a direct signature of an inside-out reionization at large scales. It is possible to qualitatively interpret the results of the simulations in terms of the fluctuations in the matter distribution and the fluctuations in the neutral fraction which have power spectra and cross-correlation $P_{\Delta \Delta}(k)$, $P_{xx}(k)$ and $P_{\Delta x}(k)$ respectively. We find that at large scales the fluctuations in matter density and neutral fraction is exactly anti-correlated through all stages of reionization. This provides a simple picture where we are able to qualitatively interpret the behaviour of the redshift space power spectra at large scales with varying $x_{HI}$ entirely in terms of a just two quantities, namely $x_{HI}$ and the ratio $P_{xx}/P_{\Delta \Delta}$. The nature of $P_{\Delta x}$ becomes different for HR and IR scenarios at intermediate and small scales. We further find that it is possible to distinguish between an inside-out and an outside-in reionization scenario from the nature of the ratio $P^s_2 /P^s_0$ at intermediate length scales.Comment: 11 pages, 6 figures. Accepted for publication in MNRAS. Replaced to match the accepted version. Added one appendix to quantify the possible uncertainties in the estimation of the multipole moments of redshift space power spectru

The effect of non-Gaussianity on error predictions for the Epoch of Reionization (EoR) 21-cm power spectrum

The Epoch of Reionization (EoR) 21-cm signal is expected to become increasingly non-Gaussian as reionization proceeds. We have used semi-numerical simulations to study how this affects the error predictions for the EoR 21-cm power spectrum. We expect $SNR=\sqrt{N_k}$ for a Gaussian random field where $N_k$ is the number of Fourier modes in each $k$ bin. We find that non-Gaussianity is important at high $SNR$ where it imposes an upper limit $[SNR]_l$. For a fixed volume $V$, it is not possible to achieve $SNR > [SNR]_l$ even if $N_k$ is increased. The value of $[SNR]_l$ falls as reionization proceeds, dropping from $\sim 500$ at $\bar{x}_{HI} = 0.8-0.9$ to $\sim 10$ at $\bar{x}_{HI} = 0.15$ for a $[150.08\, {\rm Mpc}]^3$ simulation. We show that it is possible to interpret $[SNR]_l$ in terms of the trispectrum, and we expect $[SNR]_l \propto \sqrt{V}$ if the volume is increased. For $SNR \ll [SNR]_l$ we find $SNR = \sqrt{N_k}/A$ with $A \sim 0.95 - 1.75$, roughly consistent with the Gaussian prediction. We present a fitting formula for the $SNR$ as a function of $N_k$, with two parameters $A$ and $[SNR]_l$ that have to be determined using simulations. Our results are relevant for predicting the sensitivity of different instruments to measure the EoR 21-cm power spectrum, which till date have been largely based on the Gaussian assumption.Comment: Accepted for publication in MNRAS Letters. The definitive version is available at http://mnrasl.oxfordjournals.org/content/449/1/L4

HI tomographic imaging of the Cosmic Dawn and Epoch of Reionization with SKA

We provide an overview of 21cm tomography of the Cosmic Dawn and Epoch of Reionization as possible with SKA-Low. We show why tomography is essential for studying CD/EoR and present the scales which can be imaged at different frequencies for the different phases of SKA- Low. Next we discuss the different ways in which tomographic data can be analyzed. We end with an overview of science questions which can only be answered by tomography, ranging from the characterization of individual objects to understanding the global processes shaping the Universe during the CD/EoRComment: 14 pages, 3 figures. Accepted for publication in the SKA Science Book 'Advancing Astrophysics with the Square Kilometre Array', to appear in 2015. PoS(AASKA14)01

Position-dependent power spectra of the 21-cm signal from the epoch of reionization

The 21-cm signal from the epoch of reionization is non-Gaussian. Current radio telescopes are focused on detecting the 21-cm power spectrum, but in the future the Square Kilometre Array is anticipated to provide a first measurement of the bispectrum. Previous studies have shown that the position-dependent power spectrum is a simple and efficient way to probe the squeezed-limit bispectrum. In this approach, the survey is divided into subvolumes and the correlation between the local power spectrum and the corresponding mean density of the subvolume is computed. This correlation is equivalent to an integral of the bispectrum in the squeezed limit, but is much simpler to implement than the usual bispectrum estimators. It also has a clear physical interpretation: it describes how the small-scale power spectrum of tracers such as galaxies and the 21-cm signal respond to a large-scale environment. Reionization naturally couples large and small scales as ionizing radiation produced by galactic sources can travel up to tens of Megaparsecs through the intergalactic medium during this process. Here we apply the position-dependent power spectrum approach to fluctuations in the 21-cm background from reionization. We show that this statistic has a distinctive evolution in time that can be understood with a simple analytic model. We also show that the statistic can easily distinguish between simple "inside-out" and "outside-in" models of reionization. The position-dependent power spectrum is thus a promising method to validate the reionization signal and to extract higher-order information on this process.Comment: 24 pages, 10 figures, accepted in JCA

Quantifying the non-Gaussianity in the EoR 21-cm signal through bispectrum

The epoch of reionization (EoR) 21-cm signal is expected to be highly non-Gaussian in nature and this non-Gaussianity is also expected to evolve with the progressing state of reionization. Therefore the signal will be correlated between different Fourier modes ($k$). The power spectrum will not be able capture this correlation in the signal. We use a higher-order estimator -- the bispectrum -- to quantify this evolving non-Gaussianity. We study the bispectrum using an ensemble of simulated 21-cm signal and with a large variety of $k$ triangles. We observe two competing sources driving the non-Gaussianity in the signal: fluctuations in the neutral fraction ($x_{\rm HI}$) field and fluctuations in the matter density field. We find that the non-Gaussian contribution from these two sources vary, depending on the stage of reionization and on which $k$ modes are being studied. We show that the sign of the bispectrum works as a unique marker to identify which among these two components is driving the non-Gaussianity. We propose that the sign change in the bispectrum, when plotted as a function of triangle configuration $\cos{\theta}$ and at a certain stage of the EoR can be used as a confirmative test for the detection of the 21-cm signal. We also propose a new consolidated way to visualize the signal evolution (with evolving $\overline{x}_{\rm HI}$ or redshift), through the trajectories of the signal in a power spectrum and equilateral bispectrum i.e. $P(k)-B(k, k, k)$ space.Comment: 18 pages, 11 figures. Accepted for publication in MNRAS. Replaced to match the accepted versio