arXiv subjects

Chandra Shekhar Murmu

Publications and source records attributed to Chandra Shekhar Murmu.

13 recordsLinked to original sources

arXiv2026

Cosmology with Multi-Wavelength Line Intensity Mapping Synergies in the SKAO Era

Line intensity mapping (LIM) has emerged as a powerful tool for surveying the large-scale structure of the Universe across cosmic time by measuring spatial fluctuations in the cumulative emission of spectral lines from unresolved sources or the intergalactic medium. Besides the most abundant 21-cm hyperfine line of neutral hydrogen, there are bright far-infrared fine-structure lines like [CII] 158 $μ$m, [OIII] 88 $μ$m, [NII] 122/205 $μ$m, and [OI] 63 $μ$m, as well as mid-/high-$J$ CO rotational transitions, hydrogen Ly$α$ and H$α$ as potential LIM probes. A key opportunity lies in combining and cross-correlating 21-cm intensity maps from SKAO with other line intensity maps, targeted by a range of ongoing and forthcoming LIM experiments that probe overlapping cosmic volumes. Cross-correlation between 21-cm maps and other line tracers mitigates uncorrelated systematics and enhances sensitivity to the underlying matter distribution, while multi-line analyses help disentangle cosmological and astrophysical parameters. Beyond cross-power spectra, higher-order and morphological statistics -- such as cross-bispectra, marked correlations, and morphological measures -- capture non-Gaussian features and the environmental dependence of structure formation. This chapter explores the synergies that can be achieved by combining SKAO observations with other line-intensity mapping experiments, demonstrating how such joint analyses can unlock new insights into galaxy evolution and cosmology.

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arXiv2026

Cosmology with Intensity Mapping via Statistics Beyond the Power Spectrum in the SKAO Era

The cosmological distribution of neutral hydrogen (HI) during the post-reionization era is highly non-Gaussian due to the underlying non-linear structure formation, complex galaxy biasing, and potential primordial non-Gaussianity. One needs higher-order (beyond two-point) statistics to maximally extract the non-Gaussian information out of the 21-cm intensity maps. This chapter summarizes the potential of several higher-order statistics, including voxel intensity distribution, emission line stacking, probability density functions, $\ell_1$-norm, bispectrum, and various marked statistics. Additionally, image-based morphological descriptors, such as the Largest Cluster Statistic, local dimensions, and Minkowski functionals, etc., can potentially characterize the morphology and geometry of the cosmic web encoded in the 21-cm intensity maps. This chapter presents forecasts of the detectability of these higher-order statistics in the context of the future SKAO observations. These forecasts incorporate instrumental noise, observational effects, and, in some cases, foreground removal in their analyses. With its unprecedented sensitivity, the future SKAO 21-cm observations will enable us to measure these higher-order statistics more precisely, possibly helping to break degeneracies between astrophysical and cosmological parameters, and maximizing the science outcome from these surveys.

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arXiv2026

Square Kilometer Array Synergies for the Epoch of Reionization and Cosmic Dawn

Synergies with other instruments will be essential in making, verifying, and interpreting a detection of the cosmic 21-cm signal from the Epoch of Reionization (EoR) and Cosmic Dawn (CD) with the Square Kilometer Array (SKA) telescope. Such synergies can (i) provide prior information about galaxies and the intergalactic medium (IGM) during the EoR/CD; (ii) pave the road to a first 21cm detection by mitigating foregrounds and systematics through cross-correlations; and (iii) give complimentary physical insights into the galaxy -- IGM connection. Here we review the current state of synergies and discuss what observations will best compliment SKA-low EoR/CD observations.

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arXiv2026

Tracing Large-Scale Structure Morphology with Multiwavelength Line Intensity Maps

Line intensity mapping (LIM) is an emerging technique for probing the large-scale structure (LSS) in the post-reionisation era. This captures the integrated flux of a particular spectral line emission from multiple sources within a patch of the sky without resolving them. Mapping different galaxy line emissions, such as the HI $21$-cm and CO rotational lines via LIM, can reveal complementary information about the bias with which the line emitters trace the underlying matter distribution and how different astrophysical phenomena affect the clustering pattern of these signals. The stage at which the structures in the "cosmic web" merge to form a single connected structure is known as the percolation transition. Using mock HI $21$-cm and CO($1-0$) LIM signals in the post-reionisation universe, we explore the connectivity of structures through percolation analysis and compare it with the underlying galaxy distribution. We probe the relative contributions of voids, filaments, and sheets to the galaxy density and line intensity maps using a morphological measure known as the local dimension. The CO($1-0$) map exhibits an increased filamentary behaviour and larger contribution from sheets than the $21$-cm map. We attempt to explain such an emission of the CO($1-0$) line from biased environments. The upcoming SKA-Mid will produce tomographic intensity maps of the $21$-cm signal at $z \lesssim 3$ in Band-1. CO maps can be produced at these redshifts in phase 2 of SKA-Mid, where the frequency coverage is expected to increase up to $\sim 50$ GHz. We present forecasts for the recovery of the local dimensions of these line intensity maps contaminated by thermal noise and line interlopers in SKA-Mid surveys.

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arXiv2026

Interpreting the HI 21-cm cosmology maps through Largest Cluster Statistics III: Impact of the lightcone effect

The redshifted 21-cm signal emitted by neutral Hydrogen (HI) is a promising probe to understand the evolution of the topology of ionized regions during the Epoch of Reionization (EoR). The topology of ionized regions allows us to infer the nature and properties of ionizing sources, i.e., early galaxies and AGNs. Traditional Fourier statistics, such as the power spectrum, help us quantify the strength of fluctuations in this field at different length scales but do not preserve its phase information. Analyzing the 21-cm brightness temperature field in the image domain retains its non-Gaussian characteristics and morphological information. One such approach is to track the coalescence of multiple ionized regions to form one contiguous ionized region spanning the universe. This is referred to as percolation, and its onset is quantified by a sharp rise in the value of the Largest Cluster Statistic (LCS) approaching unity. In this work, we carry out a percolation analysis of 21-cm brightness temperature fields by studying the redshift evolution of the LCS along a lightcone to distinguish between several simulated reionization scenarios. We have extended previous results on reionization model comparison from the analysis of coeval 21-cm maps to understand how the lightcone effect biases the observed percolation behavior and affects the distinguishability of the source models. We estimate the LCS of subvolumes of different sizes in the 21-cm lightcone maps and study their redshift evolution for different reionization scenarios using a moving volume approach. We find that the percolation transition inferred from a lightcone approaches that from the coeval box as we increase the bandwidth of the moving volume in all but one reionization scenario.

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arXiv2026

Probing ionized bubbles around luminous sources during reionization with SKA 21-cm observations

Detecting and characterizing individual ionized bubbles during the Epoch of Reionization (EoR) using the redshifted HI 21-cm signal provides a direct probe of the early ionizing sources and the intergalactic medium. We develop and validate a computationally efficient estimator that operates on gridded visibilities to detect ionized bubbles. This serves as an accurate alternative to the more computationally demanding bare estimator that uses all baselines and frequency channels. Further, we employ a non-parametric foreground-subtraction method based on Gaussian process regression, which minimizes loss of the HI 21-cm signal and yields improved signal-to-noise ratios. Our analysis indicates that ionized bubbles at redshifts $z \sim 7 - 8$ can be detected with SNR $\gtrsim 10$ using $\sim 100$ hours of SKA1-Low AA$^*$ and AA4 observations. We further derive a scaling relation that connects the SNR to the bubble radius, redshift, total observing time, and the mean neutral hydrogen fraction of the surrounding IGM. This helps to quickly predict the observational outcome for any planned observations and is, therefore, useful for devising observational strategies. Finally, we apply a Bayesian likelihood framework with Markov Chain Monte Carlo sampling to the residual visibilities to recover ionized bubble properties, including radius, position, and the mean neutral fraction. The resulting posterior distributions demonstrate accurate recovery of the bubble parameters. This confirms the feasibility of robustly characterizing individual ionized regions with the SKA1-Low.

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arXiv2025

From ANN to BNN: Inferring Reionization Parameters using Uncertainty-aware Emulators of 21-cm Summaries

Inferring astrophysical parameters from radio interferometric observations of the redshifted 21-cm signal from the Epoch of Reionization (EoR) is a challenging yet crucial task. The 21-cm signal from EoR is expected to be highly non-Gaussian; therefore, we need to use higher-order statistics, e.g., bispectrum. Moreover, the forward modeling of the signal and its statistics for a varying set of model parameters requires rerunning the simulations many times, which is computationally very expensive. To overcome this challenge, many artificial neural network (ANN) based emulators have been introduced, which produce the 21-cm summaries in a fraction of the time. However, ANN emulators have a drawback: they can only produce point-value predictions; thus, they fail to capture the uncertainty associated with their predictions. Therefore, when such emulators are used in the Bayesian inference pipeline, they cannot naturally propagate their prediction uncertainties to the estimated model parameters. To address this problem, we have developed Bayesian neural network (BNN) emulators for the 21-cm signal statistics, which provide the posterior distribution of the predicted signal statistics, including their prediction uncertainty. We use these BNN emulators in our Bayesian inference pipeline to infer the EoR parameters through 21-cm summaries of the mock observation of 21-cm signal with telescopic noise for $1000$ hr of SKA-LOW observation. We show that BNN emulators can capture the prediction uncertainty for the 21-cm power spectrum and bispectrum, and using these emulators in the inference pipeline provides better and tighter constraints on them. We reduced the training dataset and showed that, for smaller training datasets, BNN outperforms the ANN emulators. We also show that using the bispectrum as a summary statistic gives better constraints on EoR parameters than the power spectrum.

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arXiv2024

Detecting ionized bubbles around luminous sources during the reionization era using HI 21-cm signal

Measuring the properties of the intergalactic medium (IGM) and sources during the Epoch of Reionization (EoR) is of immense importance. We explore the prospects of probing the IGM and sources through redshifted 21-cm observations of individual ionized bubbles surrounding known luminous sources during the EoR. Accordingly, we simulate HI 21-cm maps, foreground contaminants, and system noise which are specific to the uGMRT and SKA1-Low observations. Following the subtraction of the foreground from the total visibility, we employ a visibility-based matched filter technique to optimally combine the desired HI 21-cm signal while minimizing the system noise. Our analysis suggests that these ionized bubbles can be detected with more than $5 σ$ significance using approximately $\sim 2000$ and $\sim 3000$ hours of observation time with the uGMRT at redshift $7.1$ and $8.3$, respectively, when the mean neutral hydrogen fraction outside the targeted bubble is $ \sim 0.9$. The SKA1-Low should be able to detect these bubbles with more than $8 σ$ significance using only $\sim 100$ hrs of observations. The total observing time increases both for the uGMRT and SKA1-Low when the mean neutral hydrogen fraction outside the targeted bubble decreases. Further, we investigate the impact of foreground subtraction on the detectability and find the signal-to-noise ratio decreases when smaller bandwidth is used. More importantly, we show that the matched filtering method can measure ionized bubble radius and constrain HI-neutral fraction reasonably well, providing deeper insights into the source properties and the intergalactic medium.

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arXiv2024

Impact of the Epoch of Reionization sources on the 21-cm bispectrum

The morphology of the 21-cm signal emitted by the neutral hydrogen present in the intergalactic medium (IGM) during the Epoch of Reionization (EoR) depends both on the properties of the sources of ionizing radiation and on the underlying physical processes within the IGM. Variation in the morphology of the IGM 21-cm signal due to the different sources of the EoR is expected to have a significant impact on the 21-cm bispectrum, which is one of the crucial observable statistics that can evaluate the non-Gaussianity present in the signal and which can be estimated from radio interferometric observations of the EoR. Here we present the 21-cm bispectrum for different reionization scenarios assuming different simulated models for the sources of reionization. We also demonstrate how well the 21-cm bispectrum can distinguish between different IGM 21-cm signal morphologies, arising due to the differences in the reionization scenarios, which will help us shed light on the nature of the sources of ionizing photons. Our estimated large-scale bispectrum for all unique $k$-triangle shapes shows a significant difference in the magnitude and sign across different reionization scenarios. Additionally, our focused analysis of bispectrum for a few specific $k$-triangle shapes (e.g. squeezed-limit, linear, and shapes in the vicinity of the squeezed-limit) shows that the large scale 21-cm bispectrum can distinguish between reionization scenarios that show inside-out, outside-in and a combination of inside-out and outside-in morphologies. These results highlight the potential of using the 21-cm bispectrum for constraining different reionization scenarios.

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arXiv2024

Impact of astrophysical scatter on the Epoch of Reionization [H I]$_{\rm 21cm}$ bispectrum

It is believed that the first star-forming galaxies are the main drivers of cosmic reionization. It is usually assumed that there is a one-to-one relationship between the star formation rate (SFR) inside a galaxy and the host halo mass in semi-analytical/numerical modeling of large-scale reionization. However, more accurate simulations and observations suggest that the SFR and ionizing luminosity in galaxies may vary considerably even if the host halo mass is the same. This astrophysical scatter can introduce an additional non-Gaussianity in the HI 21-cm signal, which the power spectrum might not capture adequately. In this work, we have studied the impact of the scatter on the HI 21-cm bispectrum using semi-numerical simulations. Although the fractional change in the HI 21-cm bispectra due to the scatter is found to be more than a factor of $10$ at large scales ($k_1 \lesssim 1\, {\rm Mpc}^{-1}$) for $z=7.4$, it is found to be statistically insignificant. However, at small scales ($k_1\sim2.55$~Mpc$^{-1}$), we have found the impact due to the scatter to be high in magnitude ($|\langle ΔB \rangle/B_{\text{no-scatter}}| \sim 1$) and statistically significant ($|\langleΔB\rangle/σ_{ΔB}| \gtrsim 5$) at neutral fraction, $\overline{x}_{\rm HI}\sim 0.8$ for $z=7.4$. The impact due to scatter is found to be even more prominent ($|\langle ΔB \rangle/B_{\text{no-scatter}}| \gtrsim 10$) at small scales for $z=10$ and $\overline{x}_{\rm HI}\sim 0.8$, but with reduced statistical significance ($|\langleΔB\rangle/σ_{ΔB}| \sim 3$), compared to $z=7.4$ at the same neutral fraction. In the most optimistic scenario, SKA1-Low might be able to detect these signatures of astrophysical scatter, at $\sim 3σ$ and $\sim 5σ$ detection significance for $\overline{x}_{\rm HI} \sim$ 0.8 and 0.9 respectively, for the equilateral HI 21-cm bispectrum at $z=7.4$.

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arXiv2022

Revisiting the [C II]$_{158 μ\text{m}}$ line-intensity mapping power spectrum from the EoR using non-uniform line-luminosity scatter

Detecting the line-intensity mapping (LIM) signal from the galaxies of the Epoch of Reionization is an emerging tool to constrain their role in reionization. Ongoing and upcoming experiments target the signal fluctuations across the sky to reveal statistical and astrophysical properties of these galaxies via signal statistics, e.g., the power spectrum. Here, we revisit the [C II]$_{158 μ\text{m}}$ LIM power spectrum under non-uniform line-luminosity scatter, which has a halo-mass variation of statistical properties. Line-luminosity scatter from a cosmological hydrodynamic and radiative transfer simulation of galaxies at $z=6$ is considered in this study. We test the robustness of different model frameworks that interpret the impact of the line-luminosity scatter on the signal statistics. We use a simple power-law model to fit the scatter and demonstrate that the mean luminosity-halo mass correlation fit cannot preserve the mean intensity of the LIM signal (hence the clustering power spectrum) under non-uniform scatter. In our case, the mean intensity changes by $\sim 48$ per cent compared to the mean correlation fit in contrast to the general case with semi-analytic scatter. However, we find that the prediction for the mean intensity from the most-probable fit can be modelled robustly, considering the generalized and more realistic non-uniform scatter. We also explore the possibility of diminishing luminosity bias under non-uniform scatter, affecting the clustering power spectrum, although this phenomenon might not be statistically significant. Therefore, we should adopt appropriate approaches that can consistently interpret the LIM power spectrum from observations.

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arXiv2022

Probing the Epoch of Reionization using synergies of line intensity mapping

The Epoch of Reionization (EoR) remains a poorly understood cosmic era for the most part. Yet, efforts are still going on to probe and understand this epoch. We present a review of the latest developments in the techniques (especially line-intensity mapping) to study the EoR and try to highlight the contribution of the Indian community in this field. Line-emissions like [H I]$_{\rm 21cm}$, Lyman-$α$, [C II]$_{\text{158}μ\text{m}}$ and their role as tracers in probing the EoR are discussed. While the [H I]$_{\rm 21cm}$ is an excellent probe of the early IGM, the others are mainly targeted to do an unresolved and large-scale survey of the reionizing sources. Techniques to model these signals include simulations and machine learning approaches, along with the challenge to tackle foregrounds or interlopers. We also discuss synergy opportunities among the various tracers that we mention. Synergy addresses different aspects of the problem, which otherwise is difficult or impossible to tackle. They include statistics like cross-power spectrum, cross-bispectrum, and other techniques such as follow-up studies. We present updates on the relevant experiments; these include the upper limits on the [H I]$_{\rm 21cm}$ power spectrum, along with some highlights on high-redshift galaxy surveys. Finally, we highlight what can be improved further within the community: applying machine learning and simulations based on hydrodynamic and radiative-transfer techniques. Next-generation experiments also need to be conceived to address issues currently beyond our reach.

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arXiv2021

CII and HI 21-cm line intensity mapping from the EoR: Impact of the light-cone effect on auto and cross-power spectra

CII line intensity mapping (LIM) is a potential technique to probe the early galaxies from the Epoch of Reionization (EoR). Several experiments e.g. CONCERTO, TIME, CCAT-p are underway to map the CII LIM signal fluctuations from the EoR, enabling us to estimate the CII power-spectrum and CII$\times$21-cm cross-power spectrum. Observed LIM signal will have its time evolution embedded in it along the Line of Sight (LoS) due to the finite travel time of the signal from its origin to the observer. We have investigated this so-called light-cone effect on the observed statistics of our semi-numerically simulated CII signal from the EoR. Using a suit of simulated CII and neutral hydrogen 21-cm maps and corresponding light-cone boxes, we have shown that the light-cone effect can impact the CII power spectrum by more than 15% at large scales ($k\sim 0.1\, \text{Mpc}^{-1}$, at $z=6.8$). We have also observed that the impact of light-cone effect on the CII power spectrum drops with decreasing redshift within the redshift range considered here ($7.2 \lesssim z \lesssim 6$). The CII$\times$21-cm cross-power spectrum is also affected by light-cone, and in our models where reionization ends before $z=6$, we find that the maximum impact on cross-power can reach up to 20%. At $z=6.4$, we find comparatively pronounced variation in the light-cone effect with reionization history on the cross power. Faster reionization histories have a more drastic light-cone effect on cross-power. We conclude that we need to incorporate the light-cone in order to properly model the signal, constrain the EoR-related astrophysical parameters and reionization history using the CII$\times$21-cm cross-power spectrum.

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