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Suman Majumdar

Publications and source records attributed to Suman Majumdar.

At least 73 records · Page 4Linked to original sources
arXiv2017

A fast estimator for the bispectrum and beyond - A practical method for measuring non-Gaussianity in 21-cm maps

In this paper we establish the accuracy and robustness of a fast estimator for the bispectrum - the "FFT bispectrum estimator". The implementation of the estimator presented here offers speed and simplicity benefits over a direct sampling approach. We also generalise the derivation so it may be easily be applied to any order polyspectra, such as the trispectrum, with the cost of only a handful of FFTs. All lower order statistics can also be calculated simultaneously for little extra cost. To test the estimator we make use of a non-linear density field, and for a more strongly non-Gaussian test case we use a toy-model of reionization in which ionized bubbles at a given redshift are all of equal size and are randomly distributed. Our tests find that the FFT estimator remains accurate over a wide range of k, and so should be extremely useful for analysis of 21-cm observations. The speed of the FFT bispectrum estimator makes it suitable for sampling applications, such as Bayesian inference. The algorithm we describe should prove valuable in the analysis of simulations and observations, and whilst we apply it within the field of cosmology, this estimator is useful in any field that deals with non-Gaussian data.

astro-ph.CO↗
arXiv2017

On the regular conditional distribution of a multivariate Normal given a linear transformation

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 multivariate Normal random variable 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 regular conditional distribution of a multivariate Normal random variable Y given a linear transformation TY 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 multivariate Normal random variable, where k < n, the regular conditional distribution of the remaining (n - k)-dimensional component is a (n - k)-dimensional multivariate Normal distribution.

math.ST↗
arXiv2017

Necessary and Sufficient Condition for Asymptotic Standard Normality of the Two Sample Pivot

The asymptotic solution to the problem of comparing the means of two heteroscedastic populations, based on two random samples from the populations, hinges on the pivot underpinning the construction of the confidence interval and the test statistic being asymptotically standard Normal. The pivot is known to converge to the standard Normal distribution if the two samples are independent and the ratio of the sample sizes converges to a finite positive number. We show, without any restriction on the asymptotic behavior of the ratio of the sample sizes, that Cesaro convergence of the sequence of cross sample correlation coefficients to 0 is necessary and sufficient for the aforesaid pivotal convergence. We also obtain, without any assumption on the cross sample dependence structure, that both iterated limits of the pivot are standard Normal and if the joint distribution of the standardized sample means converges to a spherically symmetric distribution, then that distribution must be bivariate standard Normal.

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arXiv2017

Prediction of the 21-cm signal from reionization: comparison between 3D and 1D radiative transfer schemes

Three-dimensional radiative transfer simulations of the epoch of reionization can produce realistic results, but are computationally expensive. On the other hand, simulations relying on one-dimensional radiative transfer solutions are faster but limited in accuracy due to their more approximate nature. Here, we compare the performance of the reionization simulation codes grizzly and C2-ray which use 1D and 3D radiative transfer schemes respectively. The comparison is performed using the same cosmological density fields, halo catalogues and source properties. We find that the ionization maps, as well as the 21-cm signal maps from these two simulations are very similar even for complex scenarios which include thermal feedback on low mass halos. The comparison between the schemes in terms of the statistical quantities such as the power spectrum of the brightness temperature fluctuation agree with each other within 10% error throughout the entire reionization history. grizzly seems to perform slightly better than the semi-numerical approaches considered in Majumdar et al. (2014) which are based on the excursion set principle. We argue that grizzly can be efficiently used for exploring parameter space, establishing observations strategies and estimating parameters from 21-cm observations.

astro-ph.CO↗
arXiv2017

On Asymptotic Standard Normality of the Two Sample Pivot

The asymptotic solution to the problem of comparing the means of two heteroscedastic populations, based on two random samples from the populations, hinges on the pivot underpinning the construction of the confidence interval and the test statistic being asymptotically standard Normal, which is known to happen if the two samples are independent and the ratio of the sample sizes converges to a finite positive number. This restriction on the asymptotic behavior of the ratio of the sample sizes carries the risk of rendering the asymptotic justification of the finite sample approximation invalid. It turns out that neither the restriction on the asymptotic behavior of the ratio of the sample sizes nor the assumption of cross sample independence is necessary for the pivotal convergence in question to take place. If the joint distribution of the standardized sample means converges to a spherically symmetric distribution, then that distribution must be bivariate standard Normal (which can happen without the assumption of cross sample independence), and the aforesaid pivotal convergence holds.

math.ST↗
arXiv2017

Recovering the HII region size statistics from 21-cm tomography

We introduce a novel technique, called "granulometry", to characterize and recover the mean size and the size distribution of HII regions from 21-cm tomography. The technique is easy to implement, but places the previously not very well defined concept of morphology on a firm mathematical foundation. The size distribution of the cold spots in 21-cm tomography can be used as a direct tracer of the underlying probability distribution of HII region sizes. We explore the capability of the method using large-scale reionization simulations and mock observational data cubes while considering capabilities of SKA1-low and a future extension to SKA2. We show that the technique allows the recovery of the HII region size distribution with a moderate signal-to-noise ratio from wide-field imaging ($\rm SNR\lesssim3$), for which the statistical uncertainty is sample variance dominated. We address the observational requirements on the angular resolution, the field-of-view, and the thermal noise limit for a successful measurement. To achieve a full scientific return from 21-cm tomography and to exploit a synergy with 21-cm power spectra, we suggest an observing strategy using wide-field imaging (several tens of square degrees) by an interferometric mosaicking/multi-beam observation with additional intermediate baselines (~2-4 km).

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arXiv2016

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.

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arXiv2016

Line of sight anisotropies in the Cosmic Dawn and EoR 21-cm power spectrum

The line of sight direction in the redshifted 21-cm signal coming from the cosmic dawn and the epoch of reionization is quite unique in many ways compared to any other cosmological signal. Different unique effects, such as the evolution history of the signal, non-linear peculiar velocities of the matter etc will imprint their signature along the line of sight axis of the observed signal. One of the major goals of the future SKA-LOW radio interferometer is to observe the cosmic dawn and the epoch of reionization through this 21-cm signal. It is thus important to understand how these various effects affect the signal for it's actual detection and proper interpretation. For more than one and half decades, various groups in India have been actively trying to understand and quantify the different line of sight effects that are present in this signal through analytical models and simulations. In many ways the importance of this sub-field under 21-cm cosmology have been identified, highlighted and pushed forward by the Indian community. In this article we briefly describe their contribution and implication of these effects in the context of the future surveys of the cosmic dawn and the epoch of reionization that will be conducted by the SKA-LOW.

astro-ph.CO↗
arXiv2016

Modelling the 21 cm Signal From the Epoch of Reionization and Cosmic Dawn

Studying the cosmic dawn and the epoch of reionization through the redshifted 21 cm line are among the major science goals of the SKA1. Their significance lies in the fact that they are closely related to the very first stars in the universe. Interpreting the upcoming data would require detailed modelling of the relevant physical processes. In this article, we focus on the theoretical models of reionization that have been worked out by various groups working in India with the upcoming SKA in mind. These models include purely analytical and semi-numerical calculations as well as fully numerical radiative transfer simulations. The predictions of the 21 cm signal from these models would be useful in constraining the properties of the early galaxies using the SKA data.

astro-ph.CO↗
arXiv2016

Probing individual sources during reionization and cosmic dawn using SKA HI 21-cm observations

Detection of individual luminous sources during the reionization epoch and cosmic dawn through their signatures in the HI 21-cm signal is one of the direct approaches to probe the epoch. Here, we summarize our previous works on this and present preliminary results on the prospects of detecting such sources using the SKA1-low experiment. We first discuss the expected HI 21-cm signal around luminous sources at different stages of reionization and cosmic dawn. We then introduce two visibility based estimators for detecting such signal: one based on the matched filtering technique and the other relies on simply combing the visibility signal from different baselines and frequency channels. We find that that the SKA1-low should be able to detect ionized bubbles of radius $R_b \gtrsim 10$ Mpc with $\sim 100$ hr of observations at redshift $z \sim 8$ provided that the mean outside neutral Hydrogen fraction $ x_{\rm HI} \gtrsim 0.5$. We also investigate the possibility of detecting HII regions around known bright QSOs such as around ULASJ1120+0641 discovered by Mortlock et al. 2011. We find that a $5 σ$ detection is possible with $600$ hr of SKA1-low observations if the QSO age and the outside $ x_{\rm HI} $ are at least $\sim 2 \times 10^7$ Myr and $\sim 0.2$ respectively. Finally, we investigate the possibility of detecting the very first X-ray and Ly-$α$ sources during the cosmic dawn. We consider mini-QSOs like sources which emits in X-ray frequency band. We find that with a total $\sim 1000$ hr of observations, SKA1-low should be able to detect those sources individually with a $\sim 9 σ$ significance at redshift $z=15$. We summarize how the SNR changes with various parameters related to the source properties.

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arXiv2015

Statistics of the epoch of reionization 21-cm signal - I. Power spectrum error-covariance

The non-Gaussian nature of the epoch of reionization (EoR) 21-cm signal has a significant impact on the error variance of its power spectrum $P({\bf \textit{k}})$. We have used a large ensemble of semi-numerical simulations and an analytical model to estimate the effect of this non-Gaussianity on the entire error-covariance matrix ${\mathcal{C}}_{ij}$. Our analytical model shows that ${\mathcal{C}}_{ij}$ has contributions from two sources. One is the usual variance for a Gaussian random field which scales inversely of the number of modes that goes into the estimation of $P({\bf \textit{k}})$. The other is the trispectrum of the signal. Using the simulated 21-cm signal ensemble, an ensemble of the randomized signal and ensembles of Gaussian random ensembles we have quantified the effect of the trispectrum on the error variance ${\mathcal{C}}_{ij}$. We find that its relative contribution is comparable to or larger than that of the Gaussian term for the $k$ range $0.3 \leq k \leq 1.0 \,{\rm Mpc}^{-1}$, and can be even $\sim 200$ times larger at $k \sim 5\, {\rm Mpc}^{-1}$. We also establish that the off-diagonal terms of ${\mathcal{C}}_{ij}$ have statistically significant non-zero values which arise purely from the trispectrum. This further signifies that the error in different $k$ modes are not independent. We find a strong correlation between the errors at large $k$ values ($\ge 0.5 \,{\rm Mpc}^{-1}$), and a weak correlation between the smallest and largest $k$ values. There is also a small anti-correlation between the errors in the smallest and intermediate $k$ values. These results are relevant for the $k$ range that will be probed by the current and upcoming EoR 21-cm experiments.

astro-ph.CO↗
arXiv2015

Effects of the sources of reionization on 21-cm redshift-space distortions

The observed 21-cm signal from the epoch of reionization will be distorted along the line-of-sight by the peculiar velocities of matter particles. These redshift-space distortions will affect the contrast in the signal and will also make it anisotropic. This anisotropy contains information about the cross-correlation between the matter density field and the neutral hydrogen field, and could thus potentially be used to extract information about the sources of reionization. In this paper, we study a collection of simulated reionization scenarios assuming different models for the sources of reionization. We show that the 21-cm anisotropy is best measured by the quadrupole moment of the power spectrum. We find that, unless the properties of the reionization sources are extreme in some way, the quadrupole moment evolves very predictably as a function of global neutral fraction. This predictability implies that redshift-space distortions are not a very sensitive tool for distinguishing between reionization sources. However, the quadrupole moment can be used as a model-independent probe for constraining the reionization history. We show that such measurements can be done to some extent by first-generation instruments such as LOFAR, while the SKA should be able to measure the reionization history using the quadrupole moment of the power spectrum to great accuracy.

astro-ph.CO↗
arXiv2015

The wedge bias in reionization 21-cm power spectrum measurements

A proposed method for dealing with foreground emission in upcoming 21-cm observations from the epoch of reionization is to limit observations to an uncontaminated window in Fourier space. Foreground emission can be avoided in this way, since it is limited to a wedge-shaped region in $k_{\parallel}, k_{\perp}$ space. However, the power spectrum is anisotropic owing to redshift-space distortions from peculiar velocities. Consequently, the 21-cm power spectrum measured in the foreground avoidance window---which samples only a limited range of angles close to the line-of-sight direction---differs from the full spherically-averaged power spectrum which requires an average over \emph{all} angles. In this paper, we calculate the magnitude of this "wedge bias" for the first time. We find that the bias is strongest at high redshifts, where measurements using foreground avoidance will over-estimate the power spectrum by around 100 per cent, possibly obscuring the distinctive rise and fall signature that is anticipated for the spherically-averaged 21-cm power spectrum. In the later stages of reionization, the bias becomes negative, and smaller in magnitude ($\lesssim 20$ per cent). The effect shows only a weak dependence on spatial scale and reionization topology.

astro-ph.CO↗
arXiv2015

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.

astro-ph.CO↗
arXiv2015

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/EoR

astro-ph.CO↗
arXiv2015

Epoch of Reionization modelling and simulations for SKA

In this chapter we provide an overview of the current status of the simulations and modelling of the Cosmic Dawn and Epoch of Reionization. We discuss the modelling requirements as dictated by the characteristic scales of the problem and the SKA instrumental properties and the planned survey parameters. Current simulations include most of the relevant physical processes. They can follow the full nonlinear dynamics and are now reaching the required scale and dynamic range, although small-scale physics still needs to be included at sub-grid level. However, despite a significant progress in developing novel numerical methods for efficient utilization of current hardware they remain quite computationally expensive. In response, a number of alternative approaches, particularly semi-analytical/semi-numerical methods, have been developed. While necessarily more approximate, if appropriately constructed and calibrated on simulations they could be used to quickly explore the vast parameter space available. Further work is still required on including some physical processes in both simulations and semi-analytical modelling. This hybrid approach of fast, approximate modelling calibrated on numerical simulations can then be used to construct large libraries of reionization models for reliable interpretation of the observational data.

astro-ph.CO↗
arXiv2014

On the use of semi-numerical simulations in predicting the 21-cm signal from the epoch of reionization

We present a detailed comparison of three different simulations of the epoch of reionization (EoR). The radiative transfer simulation (${\rm C}^2$-RAY) among them is our benchmark. Radiative transfer codes can produce realistic results, but are computationally expensive. We compare it with two semi-numerical techniques: one using the same halos as ${\rm C}^2$-RAY as its sources (Sem-Num), and one using a conditional Press-Schechter scheme (CPS+GS). These are vastly more computationally efficient than ${\rm C}^2$-RAY, but use more simplistic physical assumptions. We evaluate these simulations in terms of their ability to reproduce the history and morphology of reionization. We find that both Sem-Num and CPS+GS can produce an ionization history and morphology that is very close to ${\rm C}^2$-RAY, with Sem-Num performing slightly better compared to CPS+GS. We also study different redshift space observables of the 21-cm signal from EoR: the variance, power spectrum and its various angular multipole moments. We find that both semi-numerical models perform reasonably well in predicting these observables at length scales relevant for present and future experiments. However, Sem-Num performs slightly better than CPS+GS in producing the reionization history, which is necessary for interpreting the future observations.

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