arXiv subjects

Nirupam Roy

Publications and source records attributed to Nirupam Roy.

At least 37 records · Page 2Linked to original sources

arXiv2025

Deep uGMRT observations for enhanced calibration of 21 cm arrays -- I. First image and source catalogue

Radio-interferometric arrays require very precise calibration to detect the Epoch of Reionization 21-cm signal. A remarkably complete and accurate sky model is therefore needed in the patches of the sky used to perform the calibration. Instruments such as HERA, which use a redundant calibration strategy, also require a reference sky model to fix degenerate gain solutions. We have carried out a deep (20 hours) observation using the upgraded GMRT to make a high-fidelity sky model of one of the HERA calibration fields GLEAM 02H (J0200$-$3053). Here, we present the results from a $16.7\,\rm{MHz}$ bandwidth data centred at $147.4\,\rm{MHz}$. Using multiple GMRT pointings, we have made a $6.9^\circ\times6.9^\circ$ mosaic, which yields a median rms of $3.9^{+3.7}_{-1.4}\,{\rm mJy/beam}$ that reduces to $\sim2\,{\rm mJy/beam}$ at source-free regions. In the overlapping patch, this rms is deeper than the GLEAM catalogue, which is used for HERA calibration. We produce a catalogue of $640$ sources ($26\%$ extended) in the flux range $0.01-19.08\,{\rm Jy}$. The catalogue has a sub-arcsec positional accuracy, and the estimated fluxes are consistent with existing catalogues. The differential source counts are found to be deeper than GLEAM and consistent with LoTSS. Preliminary simulations of the sky models from GLEAM and our catalogue show $\sim 10-25\%$ difference in the visibility amplitude, with relatively small phase difference ($\approx 2^\circ$). Future work is planned for larger survey areas and wider bandwidth to reduce the rms and measure the in-band source spectral indices, which are expected to enhance the fidelity of the HERA calibration model.

astro-ph.CO↗

arXiv2025

Identification of recurrent novae from parametric modeling of the optical light curve

Novae, characterized by sudden brightening in binary star systems, are categorized into classical novae (CNe) and recurrent novae (RNe) based on their recurrence timescales. However, identifying RNe, which occur within 100 years, presents observational challenges. A reasonable signature of RNe has been theorized and statistically validated to address this -- the presence of a plateau in the optical light curve. Among the known RNe, except T CrB and V3890 Sgr displaying S-class light curve, the rest 9 out of 11 have a P-class light curve. But classical novae can also present plateaus, which further complicates the problem of distinguishing CNe from RNe just based on plateau. Hence, in this study, we aim to conduct a phenomenological analysis of P-class light curves to comment on the recurrence nature of novae. We utilize data primarily from the AAVSO database and identify a parameter space to represent all P-class light curves, anticipating distinct parameter distributions for CNe and RNe. Analysis of parameter distributions successfully distinguishes RNe from CNe and reveals potential connections with white dwarf mass and mass accretion rate, which are the key factors. Our method indicates KT Eri to be a recurrent nova, consistent with a recent study, despite only one observed outburst. The analysis also indicates the possibility of recurrence for V2860 Ori, a prediction that may be tested by deep search for nova super-remnant for this source. Our method demonstrates the feasibility of distinguishing P-class classical and recurrent novae based solely on the optical light curve. As observations of new novae increase, this method holds promise for more precise predictions of nova recurrence nature in the future.

astro-ph.SR↗

arXiv2025

SpINRv2: Implicit Neural Representation for Passband FMCW Radars

We present SpINRv2, a neural framework for high-fidelity volumetric reconstruction using Frequency-Modulated Continuous-Wave (FMCW) radar. Extending our prior work (SpINR), this version introduces enhancements that allow accurate learning under high start frequencies-where phase aliasing and sub-bin ambiguity become prominent. Our core contribution is a fully differentiable frequency-domain forward model that captures the complex radar response using closed-form synthesis, paired with an implicit neural representation (INR) for continuous volumetric scene modeling. Unlike time-domain baselines, SpINRv2 directly supervises the complex frequency spectrum, preserving spectral fidelity while drastically reducing computational overhead. Additionally, we introduce sparsity and smoothness regularization to disambiguate sub-bin ambiguities that arise at fine range resolutions. Experimental results show that SpINRv2 significantly outperforms both classical and learning-based baselines, especially under high-frequency regimes, establishing a new benchmark for neural radar-based 3D imaging.

cs.CV↗

arXiv2025

Observability of radio reflections from exoplanet ionospheres with next generation radio telescopes

Much has been learned about exoplanets and their atmospheres in the last three decades with the help of highly sensitive optical telescopes. Limited observations using X-ray telescopes have revealed the presence of ionospheres with very high density plasma around the hot Jupiter HD189733b. Owing to high density, the cutoff frequency of this plasma would lie in the range of few GHz. As the planet goes around the star, we suggest it might be possible to capture the stellar radio emission reflected from the ionosphere of the planet. We find that the reflected spectrum has a slope which is representative of the plasma density profile of the ionosphere and has a cutoff frequency. After investigating the reflection and free-free absorption process in the ionosphere, we find that this reflected signal, though feeble, can be captured by very sensitive radio telescopes operating in the low frequency range. We estimate the reflected signal from the ionosphere of a hot Jupiter and find that the flux ratio of the planet to the star are about $\sim 0.01\%$. In the view of development of facilities like Square Kilometer Array, it might be possible to capture the reflected radio signal from the ionosphere and constrain the thermal state of the ionosphere.

astro-ph.EP↗

arXiv2025

The vertical structure of the stellar disk in NGC 551

We self-consistently determine the 3D density distribution of NGC 551's stellar disk and study observational signatures of two-component stellar disks. Assuming baryonic disks are in hydrostatic equilibrium, we solved the Poisson-Boltzmann equation to estimate 3D density distribution. We used integral-field spectroscopic observations to estimate stellar velocity dispersion and built a 3D dynamical model using these density solutions and the observed rotation curve. We generated simulated surface brightness maps and compared them with observations to verify modeling consistency. The dynamical model was inclined to 90° to produce an edge-on surface density map, which we investigated by fitting different 2D functions and plotting vertical cuts in logarithmic scale. We estimated vertical stellar velocity dispersion using an iterative method, obtaining results consistent with the Disk Mass Survey formalism. Through dynamical modeling, we produced moment maps that reasonably matched observations. We examined the simulated edge-on model by taking vertical cuts and decomposing them into multiple Gaussian components. We find that artificial double Gaussian components arise due to line-of-sight integration effects, even for single-component disks. This indicates that decomposing vertical intensity cuts into multiple Gaussian components is unreliable for multicomponent disks. Instead, an up-bending break visible in logarithmic-scale vertical cuts serves as a more reliable indicator for two-component disks. We performed 2D fitting on the edge-on surface density map using the product of a scaled modified Bessel function and $sech^2$ function to estimate structural parameters. These traditional methods systematically underestimate the scale length and flattening ratio. Therefore, we suggest using detailed modeling to accurately deduce stellar disk structural parameters.

astro-ph.GA↗

arXiv2025

First detection of Circular Polarization in radio continuum towards a Massive Protostar

Polarization measurements provide strong constraints on magnetic fields in star-forming systems. While magnetic field estimates of a few kiloGauss (kG) have been obtained near the surface of low-mass protostars, there are no analogous measurements in the immediate vicinity of the surface of massive protostars. We report the measurement of radio continuum circular polarization (CP) towards a massive protostar IRAS 18162-2048 for the first time wielding Karl G. Jansky Very Large Array (VLA) observations. The fractional CP varies between $3-5\%$ across the observed frequency range of $4-6$ GHz. We consider multiple hypotheses for the production of CP and propose (i) gyrosynchrotron emission and (ii) Faraday conversion due to turbulence in the magnetic medium - both driven by mildly relativistic electrons as plausible mechanisms. We estimate, for the first time, a magnetic field $B\gtrsim20-35$ G close to the massive protostar. The Lorentz factor of the low energy electrons is estimated to be in the range $γ_{min}\sim5-7$ for gyrosynchrotron emission and $80-100$ for Faraday conversion from our observations. The magnetic field estimate can provide important constraints to the formation models of massive stars.

astro-ph.GA↗

arXiv2025

Calibration requirements for Epoch of Reionization 21-cm signal observations -- IV. Bias and variance with time and frequency correlated residual gains

Observation of multifrequency angular power spectrum of the redshifted 21-cm brightness temperature fluctuation from the neutral hydrogen holds the key to understand the structure formation and its evolution during the reionization and post-reionization era. A major challenge in observing the neutral hydrogen arises from presence of strong foreground signals in the frequency range of interest. Mitigating the direct effect of foregrounds are being addressed through various techniques in literature. An additional second order effect arises, in presence of foreground, with limited accuracy in time and frequency dependent gain calibrations. This manifests as the residual gain and bandpass error in the observed data, introduces bias and increases uncertainty in the estimates of multifrequency angular power spectrum. In this work, we present an analytic method to estimate the bias and excess uncertainty in the estimates of multifrequency angular power spectrum in presence of residual gain and bandpass errors. We use this framework to estimate the effect of these errors for detection of redshifted 21-cm emission from a redshift of $\sim 8$ with the upcoming SKA1-Low. Due to the high baseline density at the required range of angular multipoles, the SKA1-Low is found to be a tuned instrument for the redshifted 21-cm signal detection. We find that, there are scenario with residual gain and bandpass errors where there can be significant bias in these estimates. Certain foreground mitigation strategies, is expected to reduce a part of the bias. The detailed study of different aspects of gain and bandpass errors and their relative effects are discussed. We find, with assumed models of gain and bandpass errors, signal detection is possible at this redshift with $128$ hours of observations. However, to achieve this one needs to have better calibration accuracy than present day interferometers.

astro-ph.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

DeepSync: A Learning Framework for Pervasive Localization using Code Synchronization on Compressed Cellular Spectrum

Pervasive localization is essential for continuous tracking applications, yet existing solutions face challenges in balancing power consumption and accuracy. GPS, while precise, is impractical for continuous tracking of micro-assets due to high power requirements. Recent advances in non-linear compressed spectrum sensing offer low-power alternatives, but existing implementations achieve only coarse positioning through Received Signal Strength Indicator (RSSI) measurements. We present DeepSync, a deep learning framework that enables precise localization using compressed cellular spectrum. Our key technical insight lies in formulating sub-sample timing estimation as a template matching problem, solved through a novel architecture combining temporal CNN encoders for multi-frame processing with cross-attention mechanisms. The system processes non-linear inter-modulated spectrum through hierarchical feature extraction, achieving robust performance at SNR levels below -10dB -- a regime where conventional timing estimation fails. By integrating real cellular infrastructure data with physics-based ray-tracing simulations, DeepSync achieves 2.128-meter median accuracy while consuming significantly less power than conventional systems. Real-world evaluations demonstrate 10x improvement over existing compressed spectrum approaches, establishing a new paradigm for ultra-low-power localization.

eess.SY↗

arXiv2025

SpINR: Neural Volumetric Reconstruction for FMCW Radars

In this paper, we introduce SpINR, a novel framework for volumetric reconstruction using Frequency-Modulated Continuous-Wave (FMCW) radar data. Traditional radar imaging techniques, such as backprojection, often assume ideal signal models and require dense aperture sampling, leading to limitations in resolution and generalization. To address these challenges, SpINR integrates a fully differentiable forward model that operates natively in the frequency domain with implicit neural representations (INRs). This integration leverages the linear relationship between beat frequency and scatterer distance inherent in FMCW radar systems, facilitating more efficient and accurate learning of scene geometry. Additionally, by computing outputs for only the relevant frequency bins, our forward model achieves greater computational efficiency compared to time-domain approaches that process the entire signal before transformation. Through extensive experiments, we demonstrate that SpINR significantly outperforms classical backprojection methods and existing learning-based approaches, achieving higher resolution and more accurate reconstructions of complex scenes. This work represents the first application of neural volumetic reconstruction in the radar domain, offering a promising direction for future research in radar-based imaging and perception systems.

cs.CV↗

arXiv2025

Spatial Audio Processing with Large Language Model on Wearable Devices

Integrating spatial context into large language models (LLMs) has the potential to revolutionize human-computer interaction, particularly in wearable devices. In this work, we present a novel system architecture that incorporates spatial speech understanding into LLMs, enabling contextually aware and adaptive applications for wearable technologies. Our approach leverages microstructure-based spatial sensing to extract precise Direction of Arrival (DoA) information using a monaural microphone. To address the lack of existing dataset for microstructure-assisted speech recordings, we synthetically create a dataset called OmniTalk by using the LibriSpeech dataset. This spatial information is fused with linguistic embeddings from OpenAI's Whisper model, allowing each modality to learn complementary contextual representations. The fused embeddings are aligned with the input space of LLaMA-3.2 3B model and fine-tuned with lightweight adaptation technique LoRA to optimize for on-device processing. SING supports spatially-aware automatic speech recognition (ASR), achieving a mean error of $25.72^\circ$-a substantial improvement compared to the 88.52$^\circ$ median error in existing work-with a word error rate (WER) of 5.3. SING also supports soundscaping, for example, inference how many people were talking and their directions, with up to 5 people and a median DoA error of 16$^\circ$. Our system demonstrates superior performance in spatial speech understanding while addressing the challenges of power efficiency, privacy, and hardware constraints, paving the way for advanced applications in augmented reality, accessibility, and immersive experiences.

cs.SD↗

arXiv2025

Enhancing Celestial Imaging: High Dynamic Range with Neuromorphic Cameras

Conventional frame-based cameras often struggle with limited dynamic range, leading to saturation and loss of detail when capturing scenes with significant brightness variations. Neuromorphic cameras, inspired by human retina, offer a solution by providing an inherently high dynamic range. This capability enables them to capture both bright and faint celestial objects without saturation effects, preserving details across a wide range of luminosities. This paper investigates the application of neuromorphic imaging technology for capturing celestial bodies across a wide range of flux levels. Its advantages are demonstrated through examples such as the bright planet Saturn with its faint moons and the bright star Sirius A alongside its faint companion, Sirius B.

astro-ph.IM↗

arXiv2025

Neuromorphic Cameras in Astronomy: Unveiling the Future of Celestial Imaging Beyond Conventional Limits

To deepen our understanding of optical astronomy, we must advance imaging technology to overcome conventional frame-based cameras' limited dynamic range and temporal resolution. Our Perspective paper examines how neuromorphic cameras can effectively address these challenges. Drawing inspiration from the human retina, neuromorphic cameras excel in speed and high dynamic range by utilizing asynchronous pixel operation and logarithmic photocurrent conversion, making them highly effective for celestial imaging. We use 1300 mm terrestrial telescope to demonstrate the neuromorphic camera's ability to simultaneously capture faint and bright celestial sources while preventing saturation effects. We illustrate its photometric capabilities through aperture photometry of a star field with faint stars. Detection of the faint gas cloud structure of the Trapezium cluster during a full moon night highlights the camera's high dynamic range, effectively mitigating static glare from lunar illumination. Our investigations also include detecting meteorite passing near the Moon and Earth, as well as imaging satellites and anthropogenic debris with exceptionally high temporal resolution using a 200mm telescope. Our observations show the immense potential of neuromorphic cameras in advancing astronomical optical imaging and pushing the boundaries of observational astronomy.

astro-ph.IM↗

arXiv2025

Research on the Interstellar Medium and Star Formation in the Galaxy: An Indian Perspective

Although the star formation process has been studied for decades, many important aspects of the physics involved remain unsolved. Recent advancement of instrumentation in the infrared, far-infrared and sub-millimetre wavelength regimes have contributed to a significantly improved understanding of processes in the interstellar medium (ISM) leading to star formation. The future of research on the ISM and star formation looks exciting with instruments like the JWST, ALMA, etc., already contributing to the topic by gathering high-resolution high-sensitivity data and with several larger ground- and space-bound facilities either being planned or constructed. India has a sizable number of astronomers engaged in research on topics related to the ISM and star formation. In this white paper invited by the Astronomical Society of India to prepare a vision document for Indian astronomy, we review the Indian contributions to the global understanding of the star formation process and suggest areas that require focused efforts both in creating observing facilities and in theoretical front in India, in order to improve the impact of our research in the coming decades.

astro-ph.GA↗

arXiv2024

Revisiting rotationally excited CH at radio wavelengths: A case study towards W51

Ever since they were first detected in the interstellar medium, the radio wavelength (3.3 GHz) hyperfine-structure splitting transitions in the rotational ground state of CH have been observed to show anomalous excitation. Astonishingly, this behaviour has been uniformly observed towards a variety of different sources probing a wide range of physical conditions. While the observed level inversion can be explained globally by a pumping scheme involving collisions, a description of the extent of 'over-excitation' observed in individual sources requires the inclusion of radiative processes, involving transitions at higher rotational levels. Therefore, a complete description of the excitation mechanism in the CH ground state, observed towards individual sources entails observational constraints from the rotationally excited levels of CH and in particular that of its first rotationally excited state. Given the limited detections of these lines, the objective of this work is to characterise the physical and excitation properties of the rotationally excited lines of CH near 700 MHz, and investigate their influence on the pumping mechanisms of the ground-state lines of CH. This work presents the first interferometric search for the rotationally excited lines of CH near 700 MHz carried out using the uGMRT array and jointly models the physical and excitation conditions traced by lines from both the ground and first rotationally excited states of CH.

astro-ph.GA↗

arXiv2024

Continuous Pupillography: A Case for Visual Health Ecosystem

This article aims to cover pupillography, and its potential use in a number of ophthalmological diagnostic applications in biomedical space. With the ever-increasing incorporation of technology within our daily lives and an ever-growing active research into smart devices and technologies, we try to make a case for a health ecosystem that revolves around continuous eye monitoring. We tend to summarize the design constraints & requirements for an IoT-based continuous pupil detection system, with an attempt at developing a pipeline for wearable pupillographic device, while comparing two compact mini-camera modules currently available in the market. We use a light algorithm that can be directly adopted to current micro-controllers, and share our results for different lighting conditions, and scenarios. Lastly, we present our findings, along with an analysis on the challenges faced and a way ahead towards successfully building this ecosystem.

cs.CY↗

arXiv2024

A multi-wavelength study of Galactic H II regions with extended emission

H II regions are the signposts of massive ($M\geq\,8\,M_\odot$) star-forming sites in our Galaxy. It has been observed that the ionizing photon rate inferred from the radio continuum emission of H II regions is significantly lower ($\sim$ 90%) than that inferred from far-infrared fluxes measured by IRAS. This discrepancy in the ionizing photon rates may arise due to there being significant amounts of dust within the H II regions or the presence of extended emission that is undetected by high-resolution radio interferometric observations. Here, we study a sample of eight compact and ultracompact H II regions with extended emission to explore its role in resolving the discrepancy. We have used observations at the uGMRT (1.25-1.45 GHz) and data from the GLOSTAR survey (4-8 GHz) to estimate the ionizing photon rate from the radio continuum emission. We have also estimated the ionizing photon rate from the infrared luminosity by fitting a spectral energy distribution function to the infrared data from the GLIMPSE, MIPSGAL, and Hi-GAL surveys. The excellent sensitivity of the radio observations to extended emission allows us to investigate the actual fraction of ionizing photons that are absorbed by dust in compact and ultracompact H II regions. Barring one source, we find a direct association between the radio continuum emission from the compact and diffuse components of the H II region. Our study shows that the ionizing photon rates estimated using the radio and infrared data are within reasonable agreement (5-28%) if we include the extended emission. We also find multiple candidate ionizing stars in all our sources, and the ionizing photon rates from the radio observations and candidate stars are in reasonable agreement.

astro-ph.GA↗

arXiv2024

Reliability of in-band and broadband spectral index measurement: systematic study of the effect of signal to noise for uGMRT data

Low radio frequency spectral index measurements are a powerful tool to distinguish between different emission mechanisms and, in turn, to understand the nature of the sources. Besides the standard method of estimating the ``broadband" spectral index of sources from observations in two different frequency ``bands", if the observations were made with large instantaneous bandwidth, the ``in-band" spectral index can be determined, either using images of emission at multiple frequency ranges within a band or using the novel Multi Term-Multi Frequency Synthesis (MT-MFS) imaging algorithm. Here, using simulated upgraded Giant Metrewave Radio Telescope (uGMRT) data, we have systematically studied the reliability of various methods of spectral index estimation for sources with a wide range of signal-to-noise ratio (SNR). It is found that, for synthetic uGMRT point source data, the MT-MFS imaging algorithm produces in-band spectral indices for SNR~$\lesssim100$ that have errors $\gtrsim 0.2$, making them unreliable. However, at a similar SNR, the sub-band splitting method produces errors $\lesssim 0.2$, which are more accurate and unbiased in-band spectral indices. The broadband spectral indices produce errors $\lesssim 0.2$ even for SNR $\gtrsim 15$, and hence, they are most reliable if there are no higher-order variations in the spectral index. These results may be used to improve the uGMRT observation and data analysis strategies depending on the brightness of the target source.

astro-ph.IM↗