arXiv subjects

Abhirup Datta

Publications and source records attributed to Abhirup Datta.

At least 55 records · Page 3Linked to original sources

arXiv2025

Exploring Machine Learning Regression Models for Advancing Foreground Mitigation and Global 21cm Signal Parameter Extraction

Extracting parameters from the global 21cm signal is crucial for understanding the early Universe. However, detecting the 21cm signal is challenging due to the brighter foreground and associated observational difficulties. In this study, we evaluate the performance of various machine-learning regression models to improve parameter extraction and foreground removal. This evaluation is essential for selecting the most suitable machine learning regression model based on computational efficiency and predictive accuracy. We compare four models: Random Forest Regressor (RFR), Gaussian Process Regressor (GPR), Support Vector Regressor (SVR), and Artificial Neural Networks (ANN). The comparison is based on metrics such as the root mean square error (RMSE) and $R^2$ scores. We examine their effectiveness across different dataset sizes and conditions, including scenarios with foreground contamination. Our results indicate that ANN consistently outperforms the other models, achieving the lowest RMSE and the highest $R^2$ scores across multiple cases. While GPR also performs well, it is computationally intensive, requiring significant RAM and longer execution times. SVR struggles with large datasets due to its high computational costs, and RFR demonstrates the weakest accuracy among the models tested. We also found that employing Principal Component Analysis (PCA) as a preprocessing step significantly enhances model performance, especially in the presence of foregrounds.

astro-ph.CO↗

arXiv2025

ELAIS-N1 deep field uGMRT Band-2: constraints on diffuse Galactic synchrotron emission power spectrum

We present high sensitivity, low radio frequency continuum observations of the ELAIS-N1 field with 32 hours of observations of the uGMRT Band-2 ($120-250$ MHz) covering $5.86\,\text{deg}^2$ area, achieving a central off-source RMS noise of $237\,μ\mathrm{Jy}/\mathrm{beam}$ with a resolution of $11.45''$ at the central frequency of 183 MHz. A radio source catalogue of 1027 sources statistically matches with similar observations at different frequencies within the sensitivity range of the uGMRT. The calibrated data is further used to characterise the dominant foreground, the Diffuse Galactic Synchrotron Emission (DGSE), in angular scale and frequency regime. We derived the angular power spectrum (APS) of DGSE in two ways: image-based estimator (i-APS) and visibility-based Tapered Gridded Estimator (TGE; hereafter as t-APS). We assess the characteristics of DGSE with a power-law form of $C_{\ell} = A({1000}/{\ell})^β$. Combining data from Band-2 and earlier Band-3 observations, we derived a spectral variation of $C_{\ell}$ in the form of $C_{\ell} = A{ν^{-2α}}{\ell^{-β}}$. Our result indicates a spectral break at $ν= 230\,{\pm}\,5$ MHz, corresponding to a synchrotron age of $t_\text{syn} = 106\,{\pm}\,1$ Myr for the cosmic-ray electrons (CRe). This break result suggests a low-energy cutoff in the CRe population, leading to spectral curvature at low frequencies. Using both of the techniques, i-APS and t-APS, we find that the mean spectral index $α$ and power-law index $β$ are consistent within the frequency range $120-500$ MHz.

astro-ph.HE↗

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.

astro-ph.CO↗

arXiv2025

Illuminating the Diffuse Radio Emission in Low-Mass Cluster: Abell 13

Recent advances in high-sensitivity radio observations have uncovered a population of faint, ultra-steep-spectrum sources in galaxy clusters, commonly known as radio phoenixes. However, their observational classification remains poorly constrained due to the limited number of confirmed detections. This study presents a detailed multi-frequency, high-sensitivity, and high-resolution analysis of diffuse radio emission in the merging galaxy cluster Abell 13. Using GMRT (147.5 MHz), uGMRT (400 MHz), ASKAP-low (887.5 MHz), and MGCLS (1284 MHz) images, we detect complex, filamentary diffuse emission with a largest linear extent of 521 kpc. This emission originates from the cluster center and extends westward, confined within the X-ray-emitting intra-cluster medium (ICM). Chandra X-ray data confirm that Abell 13 is undergoing a merger, and the radio morphology reflects signatures of this ongoing dynamical activity. We observed filamentary structures extending towards east-northeast and southwest directions. The spectral index across the emission appears irregular and lacks a coherent spatial gradient. The integrated spectrum reveals a steep spectral index of -1.85 +/- 0.05 and a spectral curvature of -0.93 +/- 0.21. These spectral properties, along with the observed morphology and brightness distribution, are consistent with a re-energization of a fossil radio plasma driven by adiabatic compression, supporting the classification of the emission as a radio phoenix.

astro-ph.CO↗

arXiv2025

Impact of Calibration and Position Errors on Astrophysical Parameters of the HI 21cm Signal

The Epoch of Reionization (EoR) and Cosmic Dawn (CD) are pivotal stages during the first billion years of the universe, exerting a significant influence on the development of cosmic structure. The detection of the redshifted 21-cm signal from these epochs is challenging due to the dominance of significantly stronger astrophysical foregrounds and the presence of systematics. This work used the 21cm E2E (end to end) pipeline, followed by simulation methodology described \cite{2022Mazumder} to conduct synthetic observations of a simulated sky model that includes both the redshifted 21-cm signal and foregrounds. A framework was constructed using Artificial Neural Networks (ANN) and Bayesian techniques to directly deduce astrophysical parameters from the measured power spectrum. This approach eliminates the need for explicit telescope layout effects correction in interferometric arrays such as SKA-Low. The present work investigates the impact of gain calibration errors and sky model position errors on the recovery of the redshifted 21-cm power spectrum for the SKA-Low AA$^{\ast}$ array configuration. We assessed the effects of these inaccuracies on the deduced astrophysical parameters and established acceptable tolerance levels. Based on our results, the gain calibration error tolerance for ideal signal detection is 0.001 \%. However, if the sky model position errors exceed 0.048 arcseconds, the remaining foregrounds would obscure the target signal.

astro-ph.CO↗

arXiv2025

LAVA: Language Model Assisted Verbal Autopsy for Cause-of-Death Determination

Verbal autopsy (VA) is a critical tool for estimating causes of death in resource-limited settings where medical certification is unavailable. This study presents LA-VA, a proof-of-concept pipeline that combines Large Language Models (LLMs) with traditional algorithmic approaches and embedding-based classification for improved cause-of-death prediction. Using the Population Health Metrics Research Consortium (PHMRC) dataset across three age categories (Adult: 7,580; Child: 1,960; Neonate: 2,438), we evaluate multiple approaches: GPT-5 predictions, LCVA baseline, text embeddings, and meta-learner ensembles. Our results demonstrate that GPT-5 achieves the highest individual performance with average test site accuracies of 48.6% (Adult), 50.5% (Child), and 53.5% (Neonate), outperforming traditional statistical machine learning baselines by 5-10%. Our findings suggest that simple off-the-shelf LLM-assisted approaches could substantially improve verbal autopsy accuracy, with important implications for global health surveillance in low-resource settings.

cs.CL↗

arXiv2025

Unified calibration and spatial mapping of fine particulate matter data from multiple low-cost air pollution sensor networks in Baltimore, Maryland

Low-cost air pollution sensor networks are increasingly being deployed globally, supplementing sparse regulatory monitoring with localized air quality data. In some areas, like Baltimore, Maryland, there are only few regulatory (reference) devices but multiple low-cost networks. While there are many available methods to calibrate data from each network individually, separate calibration of each network leads to conflicting air quality predictions. We develop a general Bayesian spatial filtering model combining data from multiple networks and reference devices, providing dynamic calibrations (informed by the latest reference data) and unified predictions (combining information from all available sensors) for the entire region. This method accounts for network-specific bias and noise (observation models), as different networks can use different types of sensors, and uses a Gaussian process (state-space model) to capture spatial correlations. We apply the method to calibrate PM$_{2.5}$ data from Baltimore in June and July 2023 -- a period including days of hazardous concentrations due to wildfire smoke. Our method helps mitigate the effects of preferential sampling of one network in Baltimore, results in better predictions and narrower confidence intervals. Our approach can be used to calibrate low-cost air pollution sensor data in Baltimore and any other areas with multiple low-cost networks.

stat.AP↗

arXiv2025

On the estimation of solar wind velocity under varying solar activity conditions using Akatsuki measurements

We present an analysis of solar wind dynamics based on Doppler spectral width measurements of X-band radio signals from the Japanese Akatsuki spacecraft. The dataset includes two solar conjunction occultation experiments conducted in 2016 and 2022, capturing the transition from the descending phase of Solar Cycle 24, a period of low solar activity, to the ascending phase of Solar Cycle 25, which exhibited moderate to intense activity. Our study demonstrates the utility of this technique for estimating both slow and fast solar wind velocities across different phases of solar activity. A key focus is the 2022 experiment, which probed the solar corona near coronal holes at heliocentric distances ranging from 1.4 to 10 $R_\odot$. We also investigate the impact of electron density estimates on the accuracy of solar wind speed determinations, underscoring the need for improved electron density modeling to enhance the robustness of such measurements.

astro-ph.SR↗

arXiv2025

Broadband Modelling of GRB 230812B Afterglow: Implications for VHE $γ$-ray Detection with IACTs

A significant fraction of the energy from the $γ$-ray burst (GRB) jets, after powering the keV-MeV emission, forms an ultra-relativistic shock propagating into the circumburst medium. The particles in the medium accelerate through the shock and produce afterglow emission. Recently, a few GRB afterglows have been observed in TeV $γ$-rays by Cherenkov Telescopes. This provides access to broadband spectra of GRB afterglows containing rich information about the microphysics of relativistic shocks and the profile of the circumburst medium. Since the transition from synchrotron to inverse Compton regime in afterglow spectra occurs between hard X-rays and the very-high-energy (VHE) $γ$-rays, detection in one of these bands is required to identify the two spectral components. The early afterglow data in the hard X-rays, along with the GeV emission, could accurately constrain the spectral shape and help in capturing the spectral turnover to distinguish the two components. We present the multiwavelength spectral and temporal study, focused on the keV-VHE domain, of GRB 230812B, one of the brightest GRBs detected by Fermi Gamma Ray Burst Monitor (GBM), along with the detection of a 72 GeV photon in Large Area Telescope (LAT) during the early afterglow phase. Through a detailed modelling of the emission within the afterglow external forward shock in a wind-like scenario, we predict optical to high-energy observations up to ~1 day. We emphasize the importance of following up poorly localised GRBs by demonstrating that even without prompt sub-degree localisation, such as in GRB 230812B, it is possible to recover the emission using imaging atmospheric Cherenkov telescopes, thanks to their relatively wider field of view. Moreover, we show that the low energy threshold of Large-Sized Telescope is essential in discovering the VHE component at much higher redshifts, typical of long GRBs.

astro-ph.HE↗

arXiv2025

Fast Variational Bayes for Large Spatial Data

Recent variational Bayes methods for geospatial regression, proposed as an alternative to computationally expensive Markov chain Monte Carlo (MCMC) sampling, have leveraged Nearest Neighbor Gaussian processes (NNGP) to achieve scalability. Yet, these variational methods remain inferior in accuracy and speed compared to spNNGP, the state-of-the-art MCMC-based software for NNGP. We introduce spVarBayes, a suite of fast variational Bayesian approaches for large-scale geospatial data analysis using NNGP. Our contributions are primarily computational. We replace auto-differentiation with a combination of calculus of variations, closed-form gradient updates, and linear response corrections for improved variance estimation. We also accommodate covariates (fixed effects) in the model and offer inference on the variance parameters. Simulation experiments demonstrate that we achieve comparable accuracy to spNNGP but with reduced computational costs, and considerably outperform existing variational inference methods in terms of both accuracy and speed. Analysis of a large forest canopy height dataset illustrates the practical implementation of proposed methods and shows that the inference results are consistent with those obtained from the MCMC approach. The proposed methods are implemented in publicly available Github R-package spVarBayes.

stat.CO↗

arXiv2025

Calibration requirement for Epoch of Reionization 21-cm signal observation -- III. Bias and variance in uGMRT ELAIS-N1 field power spectrum

Power spectrum of \HI 21-cm radiation is one of the promising probes to study large scale structure of the universe and understand galaxy formation and evolution. The presence of foregrounds, that are orders of magnitude larger in the same frequency range of the redshifted 21-cm signal has been one of the largest observational challenges. The foreground contamination also hinders the calibration procedures and introduces residual calibration errors in the interferometric data. It has been shown that the calibration errors can introduce bias in the 21-cm power spectrum estimates and introduce additional systematics. In this work, we assess the efficacy of 21-cm power spectrum estimation for the uGMRT Band-3 observations of the ELAIS-N1 field. We first evaluate the statistics of the residual gain errors and perform additional flagging based on these statistics. We then use an analytical method to estimate the bias and variance in the power spectrum. We found that (a) the additional flagging based on calibration accuracy help reduce the bias and systematics in the power spectrum, (b) the majority of the systematics at the lower angular scales, $\ell < 6000$, are due to the residual gain errors, (c) for the uGMRT baseline configuration and system parameters, the variance is always higher than the bias in the power spectrum estimates. Based on our analysis we observe that for an angular multipole of $\ell \sim3000$, $2000$ hours of `on source time' is required with the uGMRT to detect redshifted 21-cm signal at $3-σ$ significance from a redshift of $2.55$. In this work we only consider the power spectrum measurement in the plane of the sky, an assessment of residual gain statistics and its effect on multifrequency angular power spectrum estimation for the uGMRT and the SKA like telescopes will be presented in a companion paper.

astro-ph.IM↗

arXiv2025

How the Shortest and Longest HILDCAAs Shaped Earth Outer Radiation Belt During the Van Allen Probes Era?

High-intensity long-duration continuous auroral electrojet (AE) activity (HILDCAA) events are associated with the enhancement of relativistic electron fluxes in the inner magnetosphere. The physical mechanisms underlying this enhancement are not well established yet. In this study, we analyze two contrasting HILDCAA events, one representing the shortest and the other the longest duration, using NASA Van Allen Probes observations, which have provided unprecedented, unique in-situ observations of the harsh radiation environment around the Earth. Detailed spectral and temporal analyses reveal that while both events trigger enhancements in electron flux across multiple energy channels, the shortest event is characterized by rapid, transient increases in energy levels. In contrast, the longest event produced sudden and markedly higher flux variation. The long duration event showed an acceleration of electrons to higher energy as compared to the shorter one. Moreover, a clear correlation between elevated ULF wave power for the longest event compared to the shortest is observed, apart from chorus waves responsible for relativistic electron acceleration. These findings underscore the importance of considering the duration of events in space weather models and assessment and provide valuable insights into the magnetospheric processes that modulate the variability of the radiation belt during HILDCAA conditions.

physics.space-ph↗

arXiv2025

Exploring the Dynamical Nature and Radio Halo Emission of Abell 384: A Combined Radio, X-ray and Optical Study

Multiwavelength studies of galaxy clusters are crucial for understanding the complex interconnection of the thermal and non-thermal constituents of these massive structures and uncovering the physical processes involved in their formation and evolution. Here, we report a multiwavelength assessment of the galaxy cluster A384, which was previously reported to host a radio halo with a 660 kpc size at MeerKAT 1.28 GHz. The halo is slightly offset from the cluster centre. Our uGMRT observation reveals that the halo extends up to 690 kpc at 407 MHz with a nonuniform spectral index $α^{1284\ \mathrm{MHz}}_{407\ \mathrm{MHz}}$ distribution varying from flat (-0.5) to steep (-1.3) values. In addition, we use legacy GMRT 608 MHz, \textit{XMM-Newton} X-ray, and the Dark Energy Survey optical observations to obtain an extensive understanding of the dynamical nature of the galaxy cluster. The X-ray surface brightness concentration parameter ($C_{\rm{SB}} = 0.16$) and centroid shift ($w = 0.057$) reveal an ongoing dynamical disturbance in the cluster. This is also supported by the elongated 2-D optical galaxy density distribution map of the cluster. The obtained centre shift between optical and X-ray peaks and the asymmetry parameter from optical analysis further supports the dynamical disturbance in the cluster. The radio and X-ray surface brightness follows a sub-linear correlation. Our observations suggest that the cluster is currently in a merging state where particle re-acceleration in the turbulent ICM resulted in the radio halo emission.

astro-ph.CO↗

arXiv2025

Ionospheric effect on the synthetic Epoch of Reionization observations with the SKA1-Low

The redshifted $21$\,cm signal of neutral hydrogen can be used as a direct probe of the intergalactic medium during Cosmic Dawn\,(CD) and Epoch of Reionization\,(EoR). However, detecting this inherently weak signal has numerous challenges. The major ones include accurate foreground removal from low-frequency radio observations and systematics arising from instrumental effects. The Earth's ionosphere poses a major obstacle at these low radio frequencies. Thus, a systematic study of ionospheric effects on these sensitive low-frequency observations is critical, given that the construction of the Square Kilometre Array (SKA1-Low) is in full progress. We use the end-to-end pipeline, called {\sc 21cme2e}, to study the effect of time-varying ionospheric corruption on the $21$\,cm power spectrum recovery. We use two models: a) a catalogue-based model focused on source position shift due to the refractive effect of the ionosphere and b) a realistic ionospheric condition generated using Kolmogorov's turbulence model. We assess the effect of the imperfections thus generated on the extraction of \HI\ $21$\,cm signal power spectrum. Our study shows that beyond ``median ionospheric offset" ($θ_{\text{MIO}} \lesssim 0.1''$), the $21$\,cm signal from the EoR is unaffected by residual ionospheric effects. Our study emphasizes the need for the development of efficient ionospheric calibration algorithms for the upcoming SKA1-Low observations to extract the \HI\ $21$\,cm power spectra from the CD/EoR.

astro-ph.CO↗

arXiv2025

Insights into Solar Wind Flow Speeds from the Coronal Radio occultation Experiment: Findings from the Indian Mars Orbiter Mission

Using data collected by the Indian Mars Orbiter Mission in October 2021, we investigated coronal regions of the Sun by analyzing the Doppler spectral width of radio signals to estimate solar wind velocity. A simplified equation is introduced to directly relate these two parameters. The study focuses on observations conducted from October 2 to October 14, 2021, a relatively quiet phase of solar cycle 25. The analysis targeted the coronal region within heliocentric distances of 5-8 RSun, near the ecliptic plane. In this region, solar wind velocities ranged from 100 to 150 kms^-1, while electron densities were on the order of 10^10 m^(-3). We also compared our results with electron density observations and models derived from previous studies. Though the decrease in the electron densities with respect to increasing helio-centric distance matches quite well with the theoretical models, MOM estimates fall at the lower edge of the distribution. This difference may be attributed to the prolonged weak solar activity during the MOM observations, in contrast to prior studies conducted during periods of comparatively higher solar activity in earlier solar cycles.

astro-ph.SR↗

arXiv2025

Random forests for binary geospatial data

The manuscript develops new method and theory for non-linear regression for binary dependent data using random forests. Existing implementations of random forests for binary data cannot explicitly account for data correlation common in geospatial and time-series settings. For continuous outcomes, recent work has extended random forests (RF) to RF-GLS that incorporate spatial covariance using the generalized least squares (GLS) loss. However, adoption of this idea for binary data is challenging due to the use of the Gini impurity measure in classification trees, which has no known extension to model dependence. We show that for binary data, the GLS loss is also an extension of the Gini impurity measure, as the latter is exactly equivalent to the ordinary least squares (OLS) loss. This justifies using RF-GLS for non-parametric mean function estimation for binary dependent data. We then consider the special case of generalized mixed effects models, the traditional statistical model for binary geospatial data, which models the spatial random effects as a Gaussian process (GP). We propose a novel link-inversion technique that embeds the RF-GLS estimate of the mean function from the first step within the generalized mixed effects model framework, enabling estimation of non-linear covariate effects and offering spatial predictions. We establish consistency of our method, RF-GP, for both mean function and covariate effect estimation. The theory holds for a general class of stationary absolutely regular dependent processes that includes common choices like Gaussian processes with Matérn or compactly supported covariances and autoregressive processes. The theory relaxes the common assumption of additive mean functions and accounts for the non-linear link. We demonstrate that RF-GP outperforms competing methods for estimation and prediction in both simulated and real-world data.

stat.ME↗

arXiv2024

Deciphering the spectral properties of the atypical radio relic in A115 using uGMRT, VLA, and LOFAR

The mega-parsec scale radio relics at the galaxy cluster periphery are intriguing structures. While textbook examples of relics posit arc-like elongated structures at the clusters' peripheries, several relics display more complex structures deviating from the conventional type. Abell 115 is a galaxy cluster, hosting an atypical radio relic at its northern periphery. Despite the multi-wavelength study of the cluster over the last decades, the origin of the radio relic is still unclear. In this paper, we present a multi-frequency radio study of the cluster to infer the possible mechanism behind the formation of the radio relic. We used new 400 MHz observations with the uGMRT, along with archival VLA 1.5 GHz observations and archival LOFAR 144 MHz observations. Our analysis supports the previous theory on the relic's origin from the passage of a shock front due to an off-axis merger, where the old population of particles from the radio galaxies at the relic location has been re-energised to illuminate the 2 Mpc radio relic.

astro-ph.CO↗

arXiv2024

Impact of High Intensity Long-Duration Continuous Auroral Electrojet Activity (HILDCAAs) on relativistic electrons of the radiation belt of Earth during Van Allen probe era

This study investigates the impact of High-intensity Long-Duration Continuous Auroral Electrojet Activity (HILDCAA) on the relativistic electrons in radiation belt of Earth. Utilizing data from Van Allen Probe mission of NASA, we conducted a comprehensive statistical analysis to understand the impact of HILDCAA events on the radiation belt fluxes. The super epoch analysis was carried out to determine the general response of L-shell, pitch angle, and energy-dependency of relativistic electrons to HILDCAAs. The analysis reveals a significant flux enhancement in the relativistic electron fluxes, predominantly occurring with a delay of 0 to 2 days following the onset of HILDCAA events. The general response indicates that the maximum energy of accelerated electrons reaches up to 6 MeV. Additionally, electrons with perpendicular pitch angles exhibit a significantly greater enhancement in flux and achieve higher maximum acceleration energies compared to those with parallel pitch angles. The observed time-delayed and pitch angle-dependent response related to the onset of HILDCAAs highlights the significant influence of wave-particle interactions, particularly in relation to ultra-low frequency (ULF) waves in this context. This is further supported by ground-based magnetometers and in-situ magnetic field observations from the RBSP probe, which demonstrated enhanced power of ULF waves during HILDCAA events. The study strengthens our current understanding of radiation belt particle acceleration processes and has potential implications for satellite operations and other space-based technologies, both on Earth and in the magnetospheres of other planets.

physics.space-ph↗