arXiv subjects

Saswata Dasgupta

Publications and source records attributed to Saswata Dasgupta.

14 recordsLinked to original sources

arXiv2026

Impact of numerical stability in Bayesian noise wave calibration on global 21-cm experiments

Detecting the global 21-cm signal from the Cosmic Dawn and Epoch of Reionization requires calibration accuracy far below the level of astrophysical foregrounds. REACH models its receiver using the noise wave formalism, with five frequency-dependent low-noise amplifier parameters fitted jointly to multiple calibration sources. We identify a numerical instability in this Bayesian calibration pipeline: the condition number of the posterior covariance matrix reaches $κ(\mathbf{V}^*) \sim 10^{9}$--$10^{11}$, making solutions non-reproducible across computing environments. Singular value decomposition shows that the instability is driven by near-collinearity between the design-matrix columns associated with the excess noise source temperature, $X_\mathrm{NS}$, and the load temperature, $X_\mathrm{L}$. Using a Chebyshev basis, we develop a two-step mitigation. First, fixing $T_\mathrm{NS}$ to a scalar removes the degeneracy and reduces $κ(\mathbf{V}^*)$ to $\sim 60$. Second, to retain frequency dependence, we recover $T_\mathrm{NS}(ν)$ directly from the hot-load calibration measurement. On mock data, this method preserves the stability of the reduced model while achieving comparable calibration accuracy. Masking narrow channels around cable standing-wave degeneracies further removes local artefacts in the design matrix. These steps provide a stable, reproducible, and data-driven calibration procedure. Because the $X_\mathrm{NS}$--$X_\mathrm{L}$ degeneracy is inherent to the noise wave formalism, the method is relevant to other global 21-cm experiments.

astro-ph.CO↗

arXiv2026

High-Redshift Signatures from the Cosmic Dawn and the Epoch of Reionization

In this chapter, we provide a comprehensive overview of the astrophysical and cosmological processes that shape the 21-cm signal during Cosmic Dawn and the Epoch of Reionization. We investigate both standard and exotic signatures potentially observable with SKA-Low. Standard signatures are those expected within the $Λ$CDM framework, including contributions from the first stars, galaxies, and black holes. Exotic signatures are more speculative indicating new physics, such as primordial black holes, modifications to the dark matter sector, non-standard primordial fluctuations, or strongly emitting radio galaxies. The effects of these different sources or scenarios are evaluated in the context of the expected sensitivity of SKA-Low, considering the AA* and AA4 configurations. The chapter aims to provide an overview of the theoretical landscape of 21-cm signatures and to highlight how the forthcoming SKA-Low observations will improve our understanding of astrophysical processes at early times and may open the door towards new physics beyond the $Λ$CDM framework.

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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

Imaging the 21-cm Signal from the Cosmic Dawn & Epoch of Reionization and the Connection with the Global Signal

The original baseline design for SKA-Low was motivated by the ability to produce tomographic images of the redshifted 21-cm signal, thus allowing the research field to move beyond the simple statistic of the power spectrum. In this chapter we review the imaging capabilities of SKA-Low, the wide variety of methods proposed for quantatively analysing image data, as well as the connection with the global 21-cm signal.

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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

Impact of Stochastic Pop~III X-ray Binaries on the Cosmological 21-cm Signal

High-mass X-ray binaries are one of the primary drivers of the 21-cm signal from Cosmic Dawn and Reionization, playing a leading role in the thermal history of the intergalactic medium. In traditional semi-numerical simulations, a deterministic scaling relation between the total X-ray luminosity of high-mass X-ray binaries, $L_{\rm X}$, and star formation rate (SFR) is usually adopted. However, this assumption is inaccurate for high-redshift low-SFR regions hosting few sources. The spatial variation in the number and luminosity of these sources is expected to enhance fluctuations in the Cosmic Dawn 21-cm signal. Here we quantify this effect by introducing a stochastic $L_{\rm X}$ model sampled from a power-law X-ray luminosity function. Implementing this in 21cmSPACE, a large-scale simulation framework of Cosmic Dawn and Reionization, we find that the stochasticity leads to enhanced fluctuations in X-ray heating rate fields, and affects the 21-cm power spectrum on small scales ($k>0.3~ \mathrm{cMpc^{-1}}$). The impact of stochasticity on the global 21-cm signal and on the large-scale power spectrum is found to be negligible. Our results suggest these effects will remain undetected by the upcoming Square Kilometer Array. However, large-scale lunar-based experiments may be sensitive to the signatures of stochastic X-ray heating at $z\sim 25$. Quantifying these corrections is a vital step toward robust 21-cm modeling and ensuring that future precision data interpretation is free from astrophysical biases.

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arXiv2026

Optimisation of calibration sources for global 21-cm experiments: the REACH case

The spin-flip 21-cm signal from the Cosmic Dawn and the Epoch of Reionization is an essential probe of the conditions that led to the formation of the first luminous objects in the early Universe. However, its detection remains a major challenge owing to its low strength compared to the bright foregrounds and the requirement of precise calibration of the instrument to prevent systematics that could hinder a detection or lead to false inferences. REACH (Radio Experiment for the Analysis of Cosmic Hydrogen) is a radiometer experiment designed to detect this sky-averaged signal in the frequency range of 50--130~MHz. Using a wide-beam antenna, REACH calibration relies on internal reference sources, covering a broad range of temperatures and reflection coefficients. The choice of type and number of calibrators used significantly influences the quality of the calibration. This work investigates these effects and introduces a novel method for selecting an optimal set of calibration sources. With an optimised set, we aim to reduce calibration time, thereby increasing sky integration time while preserving calibration accuracy. We explore two optimisation strategies: one applied across the full receiver band and another performed on a frequency-by-frequency basis. Finally, we demonstrate that, with a total calibration time comparable to the conventional full-calibrator set, an optimised set with fewer calibrators achieves approximately a $15~\%$ reduction in calibrated temperature noise and improved absolute calibration of the instrument. This has implications for better calibration strategies in similar radiometer experiments.

astro-ph.IM↗

arXiv2026

Circuit Modeling for In Situ 21 cm Radiometer Calibration

Recent experiments in cosmology, particularly those aimed at detecting the faint, redshifted, global 21 cm hydrogen line (depth < ~200 mK, z > 7.5), have imposed stringent new requirements on radiometer calibration. In this work, we present a framework for circuit modeling and parameter inference to strengthen these calibration pipelines. This new approach enables in situ characterization of otherwise immeasurable systematics using physically motivated models. A combination of frequentist and Bayesian techniques are employed in a pipeline that supports iterative modeling, robust parameter estimation, and detailed uncertainty quantification. The framework is applied to the REACH telescope, where the precise correction of variations in the radio signal paths arising from component aging or environmental effects is critical. Circuit models of REACH's calibration sources are developed, with the goal of predicting source temperature corrections that are conventionally obtained from laboratory measurements. By fitting the models to measured data using a convolutional cost function, a strong agreement with RMS residuals no worse than -37 dB is obtained. However, Bayesian inference reveals that the resulting temperature corrections can have uncertainties on the order of 1 to 2 K, caused by reflection coefficient degeneracies, measurement noise, and errors in the models. To combat this, posteriors obtained from laboratory measurements are employed as updated priors, reducing correction uncertainties down to 75 mK. Ultimately, the framework provides a means of dynamically accounting for drift in system non-idealities over time, addressing the increasing precision demands of global 21 cm radio astronomy.

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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.

astro-ph.CO↗

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.

astro-ph.CO↗

arXiv2025

Interpreting the HI 21-cm cosmology maps through Largest Cluster Statistics. Part II. Impact of the realistic foreground and instrumental noise on synthetic SKA1-Low observations

The Largest Cluster Statistics\,(LCS) analysis of the redshifted 21\,cm maps has been demonstrated to be an efficient and robust method for following the time evolution of the largest ionized regions\,(LIRs) during the Epoch of Reionization\,(EoR). The LCS can, in principle, constrain the reionization model and history by quantifying the morphology of neutral hydrogen\,(\HI) distribution during the different stages of the EoR. Specifically, the percolation transition of ionized regions, quantified and constrained via LCS, provides a crucial insight about the underlying reionization model. The previous LCS analysis of EoR 21\,cm maps demonstrates that the convolution of the synthesized beam of the radio interferometric arrays, e.g. SKA1-Low with the target signal, shifts the apparent percolation transition of ionized regions towards the lower redshifts. In this study, we present an optimal thresholding strategy to reduce this bias in the recovered percolation transition. We assess the robustness of LCS analysis of the 21\,cm maps, considering the effects of antenna-based gain calibration errors and instrumental noise for SKA1-Low. This analysis is performed using synthetic observations simulated by the \textsc{21cmE2E} pipeline, considering SKA1-Low AA4 configuration within a radius of 2\,km from the array centre. Our findings suggest that a minimum of $2000$\,hours of observation (SNR $\gtrapprox 3$) are required for the LCS analysis to credibly suppress the confusion introduced by thermal noise. Further, we also demonstrate that for a maximum antenna-based calibration error tolerance of $\sim 0.02\%$ (post calibration), the reionization history can be recovered in a robust and relatively unbiased manner using the LCS.

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arXiv2023

Interpreting the HI 21-cm cosmology maps through Largest Cluster Statistics -- I: Impact of the synthetic SKA1-Low observations

We analyse the evolution of the largest ionized region using the topological and morphological evolution of the redshifted 21-cm signal coming from the neutral hydrogen distribution during the different stages of reionization. For this analysis, we use the "Largest Cluster Statistics" - LCS. We mainly study the impact of the array synthesized beam on the LCS analysis of the 21-cm signal considering the upcoming low-frequency Square Kilometer Array (SKA1-Low) observations using a realistic simulation for such observation based on the 21cmE2E-pipeline using OSKAR. We find that bias in LCS estimation is introduced in synthetic observations due to the array beam. This in turn shifts the apparent percolation transition point towards the later stages of reionization. The biased estimates of LCS, occurring due to the effect of the lower resolution (lack of longer baselines) and the telescope synthesized beam will lead to a biased interpretation of the reionization history. This is important to note while interpreting any future 21-cm signal images from upcoming or future telescopes like the SKA, HERA, etc. We conclude that one may need denser $uv$-coverage at longer baselines for a better deconvolution of the array synthesized beam from the 21-cm images and a relatively unbiased estimate of LCS from such images.

astro-ph.CO↗

arXiv2022

Distinguishing reionization models using the largest cluster statistics of the 21-cm maps

The evolution of topology and morphology of ionized or neutral hydrogen during different stages of the Epoch of Reionization (EoR) have the potential to provide us a great amount of information about the properties of the ionizing sources during this era. We compare a variety of reionization source models in terms of the geometrical properties of the ionized regions. We show that the percolation transition in the ionized hydrogen, as studied by tracing the evolution of the Largest Cluster Statistics (LCS), is a robust statistic that can distinguish the fundamentally different scenarios -- inside-out and outside-in reionization. Particularly, the global neutral fraction at the onset of percolation is significantly higher for the inside-out scenario as compared to that for the outside-in reionization. In complementary to percolation analysis, we explore the shape and morphology of the ionized regions as they evolve in different reionization models in terms of the Shapefinders (SFs) that are ratios of the Minkowski functionals (MFs). The shape distribution can readily discern the reionization scenario with extreme non-uniform recombination in the IGM, such as the clumping model. In the rest of the reionization models, the largest ionized region abruptly grows only in terms of its third SF - 'length' - during percolation while the first two SFs - 'thickness' and 'breadth' - remain stable. Thus the ionized hydrogen in these scenarios becomes highly filamentary near percolation and exhibit a 'characteristic cross-section' that varies among the source models. Therefore, the geometrical studies based on SFs, together with the percolation analysis can shed light on the reionization sources.

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