arXiv subjects

Abinash Kumar Shaw

Publications and source records attributed to Abinash Kumar Shaw.

At least 19 recordsLinked to original sources

arXiv2026

Probing the large-scale structure with 21cm-galaxy cross-bispectrum: Estimates from simulations and forecasts for upcoming cosmological surveys

The redshifted 21cm signal from the post-reionization epoch is highly non-Gaussian; thus, higher-order statistics, such as the bispectrum, are required to extract this non-Gaussian information. However, high signal-to-noise ratio (SNR) detection of the 21cm auto-bispectrum will be hindered by the presence of residual systematics. Cross-correlating the 21cm signal with galaxies offers a promising path to suppress this uncertainty from residual systematics and potentially increase the SNR. We present a comprehensive analysis of the HI-galaxy cross-bispectrum using the predictions of theoretical galaxy evolution models defined on large cosmological volumes. Our analysis includes the cross-bispectrum for different triangle sizes and shapes, as well as for different combinations of the HI and galaxy fields. We forecast the detectability of the 21cm-galaxy cross-bispectrum at redshift $z\approx1$ with the Euclid-like galaxy survey and SKA-Mid observations in both interferometric and single-dish modes of the survey. We find that the 21cm-galaxy cross-bispectrum shows enhanced detectability compared to the 21cm auto-bispectrum for all unique triangles in the interferometric mode of observations. We forecast a 10$σ$ detection of the cross-bispectrum for squeezed-limit triangles and a 100$σ$ detection for all shapes combined for scales $0.2~\text{Mpc}^{-1}\leq k_1 \leq 0.9~\text{Mpc}^{-1}$ with 100 hours of SKA-Mid observations per pointing. However, the detectability of the cross-bispectrum for large scales ($k_1 < 0.1~\text{Mpc}^{-1}$), which is accessible with the single-dish mode of the survey, is limited by cosmic variance. Additionally, the signal loss due to foreground removal further suppresses the detectability. Our analysis presents a first step toward an end-to-end analysis pipeline for the future 21cm-galaxy cross-bispectrum observations.

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arXiv2026

Machine Learning and the SKA for Cosmic Dawn and the Epoch of Reionization

When operational, the SKA will generate unprecedented amounts of data and provide exquisite sensitivity for 21 cm tomography of Cosmic Dawn (CD) and the Epoch of Reionization (EoR). With this comes opportunities for new data-driven algorithms that unlock new methods for instrument modelling, data analysis, theoretical simulation, and inference for understanding the high-redshift universe. In this chapter, we provide an overview of some machine learning algorithms that have been proposed for CD and EoR science with the SKA

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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

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

Overview of 21cm Experiments at high redshift with SKAO

We provide an overview of the eight SKAO Science Book chapters that motivate the Epoch of Reionisation and Cosmic Dawn experiments with SKA-Low. We describe the individual SKA-Low experiments and expected sensitivity - power spectrum, tomography, 21-cm forest, cross-correlations, building on the broad observational plan laid out in the 2015 SKA Science Book. Finally, we outline features of the telescope that will be critical for the success of EoR/CD science, e.g., beam apodization, substations, and multi-beaming.

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arXiv2026

Inferring Cosmology and Astrophysics from the High-redshift 21cm Signal with SKA-Low

The Square Kilometre Array's low frequency telescope (SKA-Low) will enable inference of astrophysical and cosmological parameters from the redshifted 21 cm signal, probing the Cosmic Dawn and Epoch of Reionisation. While the power spectrum is the primary target for initial detection, the inherently non-Gaussian nature of the 21 cm signal, driven by the patchy evolution of ionised regions and spin temperature fluctuations, encodes rich information accessible through higher-order statistics and morphological measurements. Extracting these constraints requires diverse inference tools, encompassing both sophisticated modelling frameworks (analytical, semi-numerical, numerical, and emulators) used to predict the 21 cm signal, and advanced inference techniques (Bayesian, simulation-based, field-level) to connect statistics to the underlying physics. This chapter reviews these tools and explores the constraining power of different statistical probes accessible with SKA-Low, including the power spectrum, statistics beyond order two, moments of the signal distribution, and morphological measures. Combining these complementary statistics is crucial for breaking parameter degeneracies and unveiling the properties of the early Universe. We specifically assess the potential of the initial SKA-Low configuration (AA*) to measure galaxy and IGM properties, demonstrating its capability for early science results. This chapter forms part of a comprehensive set detailing the Epoch of Reionisation and Cosmic Dawn science case for the SKA-Low telescope.

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arXiv2026

Exploring the Cosmic Dawn through the 21 cm Forest and High-redshift Radio Sources with the SKA

The 21~cm forest, seen as absorption features in the spectra of distant radio sources, is produced by intervening neutral hydrogen and offers a direct probe of the neutral intergalactic medium during the epoch of reionization (EoR). Because it is sensitive to small-scale structure and gas temperature, it can constrain the thermal history of the early Universe and physics that affects structure formation. Detecting individual absorption lines is challenging, mainly because of their weakness and the scarcity of high-redshift radio-bright sources. Recent progress, however, has made 21~cm forest studies increasingly feasible: new statistical observables can improve sensitivity within realistic observing times, updated radio-source counts have revised expectations for suitable background quasars, and deep-learning methods can extract physical information more efficiently. In addition, new approaches have been developed to separate astrophysical effects from early galaxies from fundamental-physics effects on small-scale structure. With the Square Kilometre Array (SKA), the 21~cm forest will therefore provide a promising route to study early heating, possible exotic energy injection, dark matter properties, neutrino mass, the running spectral index, and baryon--dark-matter relative velocity. This chapter reviews recent developments in 21~cm forest research and discusses observational strategies and prospects for constraining the first galaxies and fundamental physics with SKA-Low.

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arXiv2026

Machine Learning-Driven Analysis of kSZ Maps to Predict CMB Optical Depth $τ$

Upcoming measurements of the kinetic Sunyaev-Zel'dovich (kSZ) effect, which results from Cosmic Microwave Background (CMB) photons scattering off moving electrons, offer a powerful probe of the Epoch of Reionization (EoR). The kSZ signal contains key information about the timing, duration, and spatial structure of the EoR. A precise measurement of the CMB optical depth $τ$, a key parameter that characterizes the universe's integrated electron density, would significantly constrain models of early structure formation. However, the weak kSZ signal is difficult to extract from CMB observations due to significant contamination from astrophysical foregrounds. We present a machine learning approach to extract $τ$ from simulated kSZ maps. We train advanced machine learning models, including swin transformers, on high-resolution seminumeric simulations of the kSZ signal. To robustly quantify prediction uncertainties of $τ$, we employ the Laplace Approximation (LA). This approach provides an efficient and principled Gaussian approximation to the posterior distribution over the model's weights, allowing for reliable error estimation. We investigate and compare two distinct application modes: a post-hoc LA applied to a pre-trained model, and an online LA where model weights and hyperparameters are optimized jointly by maximizing the marginal likelihood. This approach provides a framework for robustly constraining $τ$ and its associated uncertainty, which can enhance the analysis of upcoming CMB surveys like the Simons Observatory and CMB-S4.

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arXiv2026

The size and shape dependence of the SDSS galaxy bispectrum

We have measured the spherically averaged bispectrum of the SDSS main galaxy sample, considering a volume-limited $[296.75\, \rm Mpc]^3$ data cube with mean galaxy number density $0.63 \times 10^{-3} \, {\rm Mpc}^{-3}$ and median redshift $0.102$. Our analysis considers $\sim 1.37 \times 10^{8}$ triangles, for which we have measured the binned bispectrum and analysed its dependence on the size and shape of the triangle. It spans wavenumbers $k_1=(0.075-0.434)\,{\rm Mpc}^{-1}$ for equilateral triangles, and a smaller range of $k_1$ (the largest side) for triangles of other shapes. For all shapes, we find that the measured bispectrum is well modelled by a power law $A\,\big(k_1/1\mpci\big)^{n}$, where the best-fit values of $A$ and $n$ vary with the shape. We have also analysed mock galaxy samples constructed from $Λ$CDM N-body simulations by applying a simple Eulerian bias prescription where the galaxies reside in regions where the smoothed density field exceeds a threshold. We find that the bispectrum from the mock samples with bias $b_1=1.2$ is in good agreement with the SDSS results. We further divided our galaxy sample into red and blue classes and studied the nature of the bispectrum for each category. The red galaxies exhibit higher bispectrum amplitude $A$ than the blue galaxies for all possible triangle configurations. Red galaxies are old, and their larger bispectra indicate non-linear evolutionary interactions within their environments over time, resulting in their distribution being highly clustered and more biased than younger blue galaxies.

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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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arXiv2025

Asking Fast Radio Bursts for More than Reionization History

We propose different estimators to probe the intergalactic medium (IGM) during epoch of reionization (EoR) using the dispersion measure (${\rm DM}$) of the fast radio bursts. We consider three different reionization histories, which we can distinguish with a total of $\lesssim 1000\,{\rm DM}$ measurements during EoR if their redshifts are known. We note that the redshift derivatives of ${\rm DM}$ are also directly sensitive to the reionization history. The major point of this work is to explore the variance in the ${\rm DM}$ measurements and the information encoded in them. We find that the all-sky average $\overline{\rm DM}(z)$ gets biased from the line-of-sight (LoS) fluctuations in the ${\rm DM}$ measurements introduced by the ionization of IGM during EoR. We find that the ratio $σ_{\rm DM}/\overline{\rm DM}$ depends directly on the ionization bubble sizes as well as the reionization history. On the other hand, we also find that angular variance (coined as $\textit{structure function}$) of ${\rm DM}$ encodes the information about the duration of reionization and the typical bubble sizes as well. We establish the usefulness of variances in ${\rm DM}$ using toy models of reionization and later verify it with the realistic reionization simulations.

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arXiv2025

Inferring IGM parameters from the redshifted 21-cm Power Spectrum using Artificial Neural Networks

The high redshift 21-cm signal promises to be a crucial probe of the state of the intergalactic medium (IGM). Understanding the connection between the observed 21-cm power spectrum and the physical quantities intricately associated with the IGM is crucial to fully understand the evolution of our Universe. In this study, we develop an emulator using artificial neural network (ANN) to predict the 21-cm power spectrum from a given set of IGM properties, namely, the bubble size distribution and the volume averaged ionization fraction. This emulator is implemented within a standard Bayesian framework to constrain the IGM parameters from a given 21-cm power spectrum. We compare the performance of the Bayesian method to an alternate method using ANN to predict the IGM parameters from a given input power spectrum, and find that both methods yield similar levels of accuracy, while the ANN is significantly faster. We also use this ANN method of parameter estimation to predict the IGM parameters from a test set contaminated with noise levels expected from the SKA-LOW instrument after 1000 hours of observation. Finally, we train a separate ANN to predict the source parameters from the IGM parameters directly, at a redshift of $z=9.1$, demonstrating the possibility of a non-analytic inference of the source parameters from the IGM parameters for the first time. We achieve high accuracies, with R2-scores ranging between $0.898-0.978$ for the ANN emulator and between $0.966-0.986$ and $0.817-0.981$ for the predictions of IGM parameters from 21-cm power spectrum and source parameters from IGM parameters, respectively. The predictions of the IGM parameters from the Bayesian method incorporating the ANN emulator leads to tight constraints with error bars around $\pm{0.14}$ on the IGM parameters.

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arXiv2024

Probing the intergalactic medium during the Epoch of Reionization using 21-cm signal power spectra

The redshifted 21-cm signal from the epoch of reionization (EoR) directly probes the ionization and thermal states of the intergalactic medium during that period. In particular, the distribution of the ionized regions around the radiating sources during EoR introduces scale-dependent features in the spherically-averaged EoR 21-cm signal power spectrum. The goal is to study these scale-dependent features at different stages of reionization using numerical simulations and build a source model-independent framework to probe the properties of the intergalactic medium using EoR 21-cm signal power spectrum measurements. Under the assumption of high spin temperature, we modelled the redshift evolution of the ratio of EoR 21-cm brightness temperature power spectrum and the corresponding density power spectrum using an ansatz consisting of a set of redshift and scale-independent parameters. This set of eight parameters probes the redshift evolution of the average ionization fraction and the quantities related to the morphology of the ionized regions. We have tested this ansatz on different reionization scenarios generated using different simulation algorithms and found that it is able to recover the redshift evolution of the average neutral fraction within an absolute deviation $\lesssim 0.1$. Our framework allows us to interpret 21-cm signal power spectra in terms of parameters related to the state of the IGM. This source model-independent framework can efficiently constrain reionization scenarios using multi-redshift power spectrum measurements with ongoing and future radio telescopes such as LOFAR, MWA, HERA, and SKA. This will add independent information regarding the EoR IGM properties.

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arXiv2023

The monopole and quadrupole moments of the Epoch of Reionization (EoR) 21-cm bispectrum

We study the monopole ($\bar{B}^0_0$) and quadrupole ($\bar{B}^0_2$) moments of the 21-cm bispectrum (BS) from EoR simulations and present results for squeezed and stretched triangles. Both $\bar{B}^0_0$ and $\bar{B}^0_2$ are positive at the early stage of EoR where the mean neutral hydrogen (HI) density fraction $\bar{x}_{\rm HI} \approx 0.99$. The subsequent evolution of $\bar{B}^0_0$ and $\bar{B}^0_2$ at large and intermediate scales $(k=0.29$ and $0.56 \, {\rm Mpc}^{-1}$ respectively) is punctuated by two sign changes which mark transitions in the HI distribution. The first sign flip where $\bar{B}^0_0$ becomes negative occurs in the intermediate stages of EoR $(\bar{x}_{\rm HI} > 0.5)$, at large scale first followed by the intermediate scale. This marks the emergence of distinct ionized bubbles in the neutral background. $\bar{B}^0_2$ is relatively less affected by this transition, and it mostly remains positive even when $\bar{B}^0_0$ becomes negative. The second sign flip, which affects both $\bar{B}^0_0$ and $\bar{B}^0_2$, occurs at the late stage of EoR $(\bar{x}_{\rm HI} < 0.5)$. This marks a transition in the topology of the HI distribution, after which we have distinct HI islands in an ionized background. This causes $\bar{B}^0_0$ to become positive. The negative $\bar{B}^0_2$ is a definite indication that the HI islands survive only in under-dense regions.

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arXiv2023

Studying the Multi-frequency Angular Power Spectrum of the Cosmic Dawn 21-cm Signal

The light-cone (LC) anisotropy arises due to cosmic evolution of the cosmic dawn 21-cm signal along the line-of-sight (LoS) axis of the observation volume. The LC effect makes the signal statistically non-ergodic along the LoS axis. The multi-frequency angular power spectrum (MAPS) provides an unbiased alternative to the popular 3D power spectrum as it does not assume statistical ergodicity along every direction in the signal volume. Unlike the 3D power spectrum which mixes the cosmic evolution of the 21-cm signal along the LoS $k$ modes, MAPS keeps the evolution information disentangled. Here we first study the impact of different underlying physical processes during cosmic dawn on the behaviour of the 21-cm MAPS using simulations of various different scenarios and models. We also make error predictions in 21-cm MAPS measurements considering only the system noise and cosmic variance for mock observations of HERA, NenuFAR and SKA-Low. We find that $100~{\rm h}$ of HERA observations will be able to measure 21-cm MAPS at $\geq 3σ$ for $\ell \lesssim 1000$ with $0.1\,{\rm MHz}$ channel-width. The better sensitivity of SKA-Low allows reaching this sensitivity up to $\ell \lesssim 3000$. Note that due to the difference in the frequency coverage of the various experiements, the CD-EoR model considered for NenuFAR is different than those used for the HERA and SKA-Low predictions. Considering NenuFAR with the new model, measurements $\geq 2σ$ are possible only for $\ell \lesssim 600$ with $0.2\,{\rm MHz}$ channel-width and for a ten times longer observation time of $t_{\rm obs} = 1000~{\rm h}$. However, for the range $300 \lesssim \ell \lesssim 600$ and $t_{\rm obs}=1000~{\rm h}$ more than $3σ$ measurements are still possible for NenuFAR when combining consecutive frequency channels within a $5 ~{\rm MHz}$ band.

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arXiv2022

Probing early universe through redshifted 21-cm signal: Modelling and observational challenges

The redshifted 21-cm radiation from the atomic hydrogen (HI) provides an excellent direct probe to study the evolution of HI in IGM and thus reveal the nature of the first luminous objects, their evolution and role during Cosmic Dawn (CD) and Epoch of Reionization (EoR), and formation and evolution of the structures thereafter. Direct mapping of the HI density during the CD-EoR is rather difficult with the current and future instruments due to large foreground and other observational contamination. The first detection of this redshifted HI signal is planned through statistical estimators. Given the utmost importance of the detection and analysis of the redshifted 21-cm signal, physics of CD-EoR is one of the objectives of the upcoming SKA-Low telescope. This paper summarizes the collective effort of Indian astronomers to understand the origin of the redshifted 21-cm signal, sources of first ionizing photons, their propagation through the IGM, various cosmological effects on the expected 21-cm signal, various statistical measures of the signal like power spectrum, bispectrum, etc. A collective effort on detection of the signal by developing estimators of the statistical measures with rigorous assessment of their expected uncertainties, various challenges like that of the large foreground emission and calibration issues are also discussed. Various versions of the detection methods discussed here have also been used in practice with the GMRT with successful assessment of the foreground contamination and upper limits on the matter density in EoR and post-EoR. The collective efforts compiled here has been a large part of the global effort to prepare proper observational technique and analysis procedure for the first light of the CD-EoR through the SKA-Low.

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arXiv2022

Detecting galaxies in a large H{\sc i}~spectral cube

The upcoming Square Kilometer Array (SKA) is expected to produce humongous amount of data for undertaking H{\sc i}~science. We have developed an MPI-based {\sc Python} pipeline to deal with the large data efficiently with the present computational resources. Our pipeline divides such large H{\sc i}~21-cm spectral cubes into several small cubelets, and then processes them in parallel using publicly available H{\sc i}~source finder {\sc SoFiA-$2$}. The pipeline also takes care of sources at the boundaries of the cubelets and also filters out false and redundant detections. By comapring with the true source catalog, we find that the detection efficiency depends on the {\sc SoFiA-$2$} parameters such as the smoothing kernel size, linking length and threshold values. We find the optimal kernel size for all flux bins to be between $3$ to $5$ pixels and $7$ to $15$ pixels, respectively in the spatial and frequency directions. Comparing the recovered source parameters with the original values, we find that the output of {\sc SoFiA-$2$} is highly dependent on kernel sizes and a single choice of kernel is not sufficient for all types of H{\sc i}~galaxies. We also propose use of alternative methods to {\sc SoFiA-$2$} which can be used in our pipeline to find sources more robustly.

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arXiv2022

Constraints on dark matter self-interaction from galactic core size

Self-interaction of particulate dark matter may help thermalising the central region of the galactic halo and driving core formation. The core radius is expectedly sensitive to the self-interaction strength of dark matter (DM). In this paper we study the feasibility of constraining dark matter self-interaction from the distribution of the core radius in isolated haloes. We perform systematic DM only $N$-body simulations of spherically symmetric isolated galactic haloes in the mass range of $10^{10} $-$10^{15}M_{\odot}$, incorporating the impact of isotropic DM self-interaction. Comparing the simulated profiles with the observational data, we provide a conservative upper limit on the self-interaction cross-section, $ σ/m < $ $ 9.8 $ $\ \rm cm^2 /\rm gm $ at $ 95 \% $ confidence level. We report significant dependence of the derived bounds on the galactic density distribution models assumed for the analysis.

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