arXiv subjects

Arpan Pal

Publications and source records attributed to Arpan Pal.

At least 19 recordsLinked to original sources

arXiv2026

The SPOTLIGHT Pulsar Search Pipeline: A GPU-Accelerated FFT Approach

We present the pulsar search component of SPOTLIGHT (Survey for sPoradic radiO bursTs via a commensaL multI-beam Gpu-powered Hpc at the gmrT), a GPU-accelerated commensal backend operating at the upgraded Giant Metrewave Radio Telescope (uGMRT). While SPOTLIGHT is primarily designed for real-time detection and localisation of fast radio bursts (FRBs), it simultaneously records a subset of beamformed data products for periodicity searches without requiring dedicated telescope time. To process the large data volumes generated by the survey, we have developed a scalable FFT-based pulsar search pipeline that combines radio-frequency interference mitigation, GPU-accelerated dedispersion and periodicity searches, multi-beam candidate sifting, efficient folding and machine-learning classification. Using population synthesis and archival uGMRT observations, we estimate that a fully operational SPOTLIGHT survey with 160 PC and one IA beam could discover $\sim$ 450 new pulsars, probing both high-sky coverage and faint pulsars over three and a half years of commensal observations. The pipeline has been validated on GMRT Cycle 48 and 49 observations (i.e. April 2025 to Mar 2026), successfully re-detecting numerous known pulsars with a wide range of Period, DM and flux densities, and is currently operational for SPOTLIGHT commensal data processing. We describe the SPOTLIGHT observing system, pulsar survey design, search parameter space, candidate-selection strategy, current status, and future developments. SPOTLIGHT demonstrates the scientific potential of commensal pulsar surveys and serves as a pathfinder for real-time, large-scale pulsar and transient searches in the SKA era.

astro-ph.HE↗

arXiv2026

The SPOTLIGHT Multibeam Real-Time Transient Detection System

Fast Radio Bursts (FRBs) are among the most enigmatic transient phenomena in the Universe. In order to unravel the mystery behind these events, one requires instruments that possess the ability to search, detect, localise, and capture these events in high resolution over large fields-of-view in real-time. The SPOTLIGHT project is one such backend, leveraging the upgraded Giant Metrewave Radio Telescope (uGMRT) to conduct a commensal search for FRBs and other radio transients, using a dedicated high-performance computing facility, comprised of 90 NVIDIA A100 GPUs and 60 compute servers. Here we present the design, implementation, and performance of SPOTLIGHT's real-time transient search pipeline, a GPU-accelerated system capable of processing up to 2000 post-correlation beams in real time. The pipeline combines AstroAccelerate-powered brute-force dedispersion and single pulse search, with a multi-stage and robust candidate optimisation framework, as well as a triggering system for automatic capture of high-resolution visibility and baseband data. To ensure continuous validation of pipeline performance, we have also developed a real-time signal injection framework capable of injecting synthetic bursts directly into SPOTLIGHT's beamformed data stream. The system operates commensally with routine uGMRT observations, processing data streams in real-time while maintaining high sensitivity to ms-duration transients across dispersion measures extending up to 2000 pc cm$^{-3}$. During its initial deployment in uGMRT Cycle 49 and Cycle 50, the pipeline detected 2870 bursts from 42 known sources, and demonstrated sensitivity consistent with the predicted survey threshold of $\sim$ 0.2 Jy ms. The SPOTLIGHT system establishes a scalable framework for wide-field, low-frequency transient discovery and localisation, and provides a key technological foundation for next-generation radio transient surveys.

astro-ph.IM↗

arXiv2026

Probing Merger Shocks in Galaxy Clusters in the SKA Era

Galaxy cluster mergers represent the most energetic phenomena in the Universe since the Big Bang releasing gravitational potential energy of $\sim 10^{63-64}$ erg, injecting turbulence and driving shocks through the intracluster medium (ICM). These merger shocks can accelerate cosmic ray electrons and compress magnetic fields, sometimes producing Mpc-scale synchrotron radio structures known as radio relics. Radio relics are powerful tracers of merger dynamics, particle acceleration, and magnetic field evolution, yet fundamental questions about the underlying physics and their time evolution remain unresolved. In this chapter, we review the current understanding of cluster merger shocks and their radio signatures, presenting the observational evidence from the SKA pathfinders and precursors, linking radio relics to shocks alongside outstanding theoretical challenges. We also consider related shock-influenced phenomena: radio phoenices from revived fossil AGN plasma and Gently Re-Energised Tails. Further, we outline the directions of investigation using the sensitivities of the SKA-Low and Mid complemented with X-ray observations that will allow us to make significant progress in understanding the cluster merger shocks. Detailed studies of individual targets in continuum and polarization and studies of populations of relics using wide surveys will both provide insights to the micro-physics and cosmic evolution of merger shocks. We present SKAO capabilities across staged deployments starting from AA0.5 to AA4 and identify science verification targets that will illuminate the physics of cluster merger shocks in the SKA era

astro-ph.HE↗

arXiv2026

VROOM-SBI: A Fast Simulation-Based Bayesian Inference Methodology for Stokes QU-Fitting in Radio Interferometry

Bayesian QU-fitting is among the most accurate approaches for line-of-sight Faraday inference, but its per-pixel computational cost has made survey-scale application infeasible. QU-fitting is an alternative to Faraday synthesis with comparable accuracy in recovering line-of-sight Faraday components, but it has historically been computationally prohibitive at survey scale. Fitting to the Stokes spectra in $Q$ and $U$ through Bayesian inference is effective but slow. We introduce \texttt{VROOM-SBI}, which uses simulation-based inference, particularly neural posterior estimation, to speed up inference. Our results are comparable to both Faraday synthesis and QU-fitting, and deliver a speedup of $\sim$$500$ over classical QU-fitting implementations. We provide an open code repository and tools along with trained models via HuggingFace for the four standard depolarization models in common use, trained on VLA L-band frequency coverage.

astro-ph.IM↗

arXiv2026

Reliability of uGMRT Band-4 Polarimetry: Results from a Quadrature Hybrid Polarizer Bypass Experiment

Polarimetric observations at sub-GHz frequencies offer unique access to the magnetized universe through Faraday rotation and depolarization studies, but achieving reliable polarization calibration at these frequencies remains challenging. We report the identification and resolution of a systematic polarization calibration instability in the upgraded Giant Metrewave Radio Telescope (uGMRT) Band 4 (550--750\,MHz). Through diagnostic observations of multiple calibrators, we discovered that the cross-hand phase response varies with the fractional polarization of the observed source, violating the fundamental assumption of calibration transferability in radio interferometry. Systematic engineering tests traced this behaviour to the Quadrature Hybrid (QH) polarizer in the frontend signal chain. We conducted a controlled experiment in which the QH was bypassed in seven antennas, converting them to linear polarization feeds. The bypassed system shows dramatically improved performance: instrumental leakage reduced from 10--15\% to 2--5\%, residual leakage after calibration reduced from $\sim$0.5\% to less than $0.2\%$, and stable cross-hand phases independent of source polarization. For the polarized source DA\,240 (RM\,$=$\,3.3\,rad\,m$^{-2}$), the QH-bypassed system accurately recovers the expected $25^\circ$ polarization angle rotation across the band, which the with QH system fails to reproduce. These results establish that the QH polarizer is the dominant source of polarimetric instability in uGMRT Band\,4 and demonstrate that its removal enables reliable sub-GHz polarimetry. We recommend the linear feed configuration for science cases requiring accurate polarization angle and rotation measure measurements.

astro-ph.IM↗

arXiv2026

Wiggling Through the ICM: Multi-Resolution Radio Imaging of a Tailed Radio Galaxy in MACS J1354.6+7715

Tailed radio galaxies are powerful tracers of interactions between active galactic nuclei (AGN) and the intracluster medium (ICM), providing unique insights into cluster dynamics. We present LOw Frequency ARray (LOFAR) 144 MHz and uGMRT 400 MHz observations of the cluster MACS J1354.6+7715 (z = 0.3967) to investigate the radio emission associated with its member galaxies and the cluster environment. The dominant tailed radio galaxy in the cluster exhibits a sharply bent tail extending over approximately 300 kpc, with the spectral index steepening from approximately -0.46 +/- 0.21 near the AGN core to approximately -2.43 +/- 0.30 in the outermost regions. Synchrotron modelling of the tail yields a radiative age of 150 +/- 10 Myr, implying a galaxy velocity of 1956 +/- 130 km s^-1, which is of order ~ 0.9 times the escape velocity. We find no evidence of relics or halos in our radio images, and the X-ray morphology from Chandra appears relatively undisturbed, suggesting that the system is a pre-merging candidate. Our results indicate that the radio galaxy is undergoing its first infall into the cluster, providing an excellent laboratory for studying the impact of the ICM on AGN activity and galaxy evolution, and demonstrating how multi-frequency radio observations of tailed galaxies can uniquely probe both AGN lifecycles and the early stages of cluster assembly.

astro-ph.GA↗

arXiv2026

Photometric Redshift Estimation Using Scaled Ensemble Learning

The development of the state-of-the-art telescopic systems capable of performing expansive sky surveys such as the Sloan Digital Sky Survey, Euclid, and the Rubin Observatory's Legacy Survey of Space and Time (LSST) has significantly advanced efforts to refine cosmological models. These advances offer deeper insight into persistent challenges in astrophysics and our understanding of the Universe's evolution. A critical component of this progress is the reliable estimation of photometric redshifts (Pz). To improve the precision and efficiency of such estimations, the application of machine learning (ML) techniques to large-scale astronomical datasets has become essential. This study presents a new ensemble-based ML framework aimed at predicting Pz for faint galaxies and higher redshift ranges, relying solely on optical (grizy) photometric data. The proposed architecture integrates several learning algorithms, including gradient boosting machine, extreme gradient boosting, k-nearest neighbors, and artificial neural networks, within a scaled ensemble structure. By using bagged input data, the ensemble approach delivers improved predictive performance compared to stand-alone models. The framework demonstrates consistent accuracy in estimating redshifts, maintaining strong performance up to z ~ 4. The model is validated using publicly available data from the Hyper Suprime-Cam Strategic Survey Program by the Subaru Telescope. Our results show marked improvements in the precision and reliability of Pz estimation. Furthermore, this approach closely adheres to-and in certain instances exceeds-the benchmarks specified in the LSST Science Requirements Document. Evaluation metrics include catastrophic outlier, bias, and rms.

astro-ph.GA↗

arXiv2025

A Linearly Polarized Merger Shock Down to 550 MHz: A uGMRT Study of the Merging Cluster Abell 746

Radio relics, arc-like polarized sources with highly aligned magnetic fields, are typically found on the outskirts of merging galaxy clusters. The magneto-ionic media responsible for the significant coherence observed in radio relics remain poorly understood. Low-frequency measurements of radio relics are essential for constraining depolarization models, which provide crucial insights into the magnetic field distribution. However, these measurements are challenging due to the emission properties and interferometer systematics. We have detected polarization signals from the northwest radio relic in Abell 746 at 650 MHz with the upgraded Giant Meterwave Radio Telescope, marking the first-ever detection of polarisation from radio relics below 1 GHz. At this frequency, the average Rotation Measure (RM) corrected magnetic fields align well with shock radio emission, typical of radio relics. The fractional polarization at 650 MHz is $\sim 18\pm4 \%$. Our results indicate that a single internal depolarization model cannot explain the observed depolarization spectra, suggesting a non-uniform magnetic field distribution or complex contribution of different polarized regions in the radio relic. Our detection of polarization signals at 650 MHz reveals critical insights into radio relic magnetic field structures, offering a low-frequency approach to understanding ICM magnetic fields in merging galaxy clusters.

astro-ph.HE↗

arXiv2025

The Promise of Spiking Neural Networks for Ubiquitous Computing: A Survey and New Perspectives

Spiking neural networks (SNNs) have emerged as a class of bio -inspired networks that leverage sparse, event-driven signaling to achieve low-power computation while inherently modeling temporal dynamics. Such characteristics align closely with the demands of ubiquitous computing systems, which often operate on resource-constrained devices while continuously monitoring and processing time-series sensor data. Despite their unique and promising features, SNNs have received limited attention and remain underexplored (or at least, under-adopted) within the ubiquitous computing community. To address this gap, this paper first introduces the core components of SNNs, both in terms of models and training mechanisms. It then presents a systematic survey of 76 SNN-based studies focused on time-series data analysis, categorizing them into six key application domains. For each domain, we summarize relevant works and subsequent advancements, distill core insights, and highlight key takeaways for researchers and practitioners. To facilitate hands-on experimentation, we also provide a comprehensive review of current software frameworks and neuromorphic hardware platforms, detailing their capabilities and specifications, and then offering tailored recommendations for selecting development tools based on specific application needs. Finally, we identify prevailing challenges within each application domain and propose future research directions that need be explored in ubiquitous community. Our survey highlights the transformative potential of SNNs in enabling energy-efficient ubiquitous sensing across diverse application domains, while also serving as an essential introduction for researchers looking to enter this emerging field.

cs.NE↗

arXiv2025

A Possible Four-Month Periodicity in the Activity of FRB 20240209A

Fast Radio Bursts (FRBs) are millisecond-duration radio transients from distant galaxies. While most FRBs are singular events, repeaters emit multiple bursts, with only two-FRB 121102 and FRB 180916B-showing periodic activity (160 and 16 days, respectively). FRB 20240209A, discovered by CHIME-FRB, is localized to the outskirts of a quiescent elliptical galaxy (z = 0.1384). We discovered a periodicity of ~ 126 days in the activity of the FRB 20240209A, potentially adding to the list of extremely rare periodic repeating FRBs. We used auto-correlation and Lomb-Scargle periodogram analyses, validated with randomized control samples, to confirm the periodicity. The FRB's location in an old stellar population disfavors young progenitor models, instead pointing to scenarios involving globular clusters, late-stage magnetars, or low-mass X-ray binaries (LMXBs). Though deep X-ray or polarimetric observations are not available, the localization of the FRB and a possible periodicity points to progenitors likely to be a binary involving a compact object and a stellar companion or a precessing or rotating old neutron star.

astro-ph.HE↗

arXiv2024

An upgraded GMRT and MeerKAT study of radio relics in the low mass merging cluster PSZ2 G200.95-28.16

Diffuse radio sources known as radio relics are direct tracers of shocks in the outskirts of merging galaxy clusters. PSZ2 G200.95-28.16, a low-mass merging cluster($\textrm{M}_{500} = (2.7 \pm 0.2) \times 10^{14}~\mathrm{M}_{\odot}$) features a prominent radio relic, first identified by Kale et al. 2017. We name this relic as the Seahorse. The MeerKAT Galaxy Cluster Legacy Survey has confirmed two additional radio relics, R2 and R3 in this cluster. We present new observations of this cluster with the Upgraded GMRT at 400 and 650 MHz paired with the Chandra X-ray data. The largest linear sizes for the three relics are~1.53 Mpc, 1.12~kpc, and 340~kpc. All three radio relics are polarized at 1283~MHz. Assuming the diffusive shock acceleration model, the spectral indices of the relics imply shock Mach Numbers of $3.1 \pm 0.8$ and $2.8 \pm 0.9$ for the Seahorse and R2, respectively. The Chandra X-ray surface brightness map shows two prominent subclusters, but the relics are not perpendicular to the likely merger axis as typically observed; no shocks are detected at the locations of the relics. We discuss the possible merger scenarios in light of the low mass of the cluster and the radio and X-ray properties of the relics. The relic R2 follows the correlation known in the radio relic power and cluster mass plane, but the Seahorse and R3 relics are outliers. We have also discovered a radio ring in our 650~MHz uGMRT image that could be an Odd radio circle candidate.

astro-ph.GA↗

arXiv2024

Concise tensors of minimal border rank

We determine defining equations for the set of concise tensors of minimal border rank in $C^m\otimes C^m\otimes C^m$ when $m=5$ and the set of concise minimal border rank $1_*$-generic tensors when $m=5,6$. We solve this classical problem in algebraic complexity theory with the aid of two recent developments: the 111-equations defined by Buczyńska-Buczyński and results of Jelisiejew-Šivic on the variety of commuting matrices. We introduce a new algebraic invariant of a concise tensor, its 111-algebra, and exploit it to give a strengthening of Friedland's normal form for $1$-degenerate tensors satisfying Strassen's equations. We use the 111-algebra to characterize wild minimal border rank tensors and classify them in $C^5\otimes C^5\otimes C^5$.

math.AG↗

arXiv2024

A pulsar-like swing in the polarisation position angle of a nearby fast radio burst

Fast radio bursts (FRBs) last for milliseconds and arrive at Earth from cosmological distances. While their origin(s) and emission mechanism(s) are presently unknown, their signals bear similarities with the much less luminous radio emission generated by pulsars within our Galaxy and several lines of evidence point toward neutron star origins. For pulsars, the linear polarisation position angle (PA) often exhibits evolution over the pulse phase that is interpreted within a geometric framework known as the rotating vector model (RVM). Here, we report on a fast radio burst, FRB 20221022A, detected by the Canadian Hydrogen Intensity Mapping Experiment (CHIME) and localized to a nearby host galaxy ($\sim 65\; \rm{Mpc}$), MCG+14-02-011. This one-off FRB displays a $\sim 130$ degree rotation of its PA over its $\sim 2.5\; \rm{ms}$ burst duration, closely resembling the "S"-shaped PA evolution commonly seen from pulsars and some radio magnetars. The PA evolution disfavours emission models involving shocks far from the source and instead suggests magnetospheric origins for this source which places the emission region close to the FRB central engine, echoing similar conclusions drawn from tempo-polarimetric studies of some repeating sources. This FRB's PA evolution is remarkably well-described by the RVM and, although we cannot determine the inclination and magnetic obliquity due to the unknown period/duty cycle of the source, we can dismiss extremely short-period pulsars (e.g., recycled millisecond pulsars) as potential progenitors. RVM-fitting appears to favour a source occupying a unique position in the period/duty cycle phase space that implies tight opening angles for the beamed emission, significantly reducing burst energy requirements of the source.

astro-ph.HE↗

arXiv2023

Concept-based Anomaly Detection in Retail Stores for Automatic Correction using Mobile Robots

Tracking of inventory and rearrangement of misplaced items are some of the most labor-intensive tasks in a retail environment. While there have been attempts at using vision-based techniques for these tasks, they mostly use planogram compliance for detection of any anomalies, a technique that has been found lacking in robustness and scalability. Moreover, existing systems rely on human intervention to perform corrective actions after detection. In this paper, we present Co-AD, a Concept-based Anomaly Detection approach using a Vision Transformer (ViT) that is able to flag misplaced objects without using a prior knowledge base such as a planogram. It uses an auto-encoder architecture followed by outlier detection in the latent space. Co-AD has a peak success rate of 89.90% on anomaly detection image sets of retail objects drawn from the RP2K dataset, compared to 80.81% on the best-performing baseline of a standard ViT auto-encoder. To demonstrate its utility, we describe a robotic mobile manipulation pipeline to autonomously correct the anomalies flagged by Co-AD. This work is ultimately aimed towards developing autonomous mobile robot solutions that reduce the need for human intervention in retail store management.

cs.RO↗

arXiv2023

Symmetry Lie Algebras of Varieties with Applications to Algebraic Statistics

The motivation for this paper is to detect when an irreducible projective variety V is not toric. We do this by analyzing a Lie group and a Lie algebra associated to V. If the dimension of V is strictly less than the dimension of the above mentioned objects, then V is not a toric variety. We provide an algorithm to compute the Lie algebra of an irreducible variety and use it to provide examples of non-toric statistical models in algebraic statistics.

math.AG↗

arXiv2023

DOST -- Domain Obedient Self-supervised Training for Multi Label Classification with Noisy Labels

The enormous demand for annotated data brought forth by deep learning techniques has been accompanied by the problem of annotation noise. Although this issue has been widely discussed in machine learning literature, it has been relatively unexplored in the context of "multi-label classification" (MLC) tasks which feature more complicated kinds of noise. Additionally, when the domain in question has certain logical constraints, noisy annotations often exacerbate their violations, making such a system unacceptable to an expert. This paper studies the effect of label noise on domain rule violation incidents in the MLC task, and incorporates domain rules into our learning algorithm to mitigate the effect of noise. We propose the Domain Obedient Self-supervised Training (DOST) paradigm which not only makes deep learning models more aligned to domain rules, but also improves learning performance in key metrics and minimizes the effect of annotation noise. This novel approach uses domain guidance to detect offending annotations and deter rule-violating predictions in a self-supervised manner, thus making it more "data efficient" and domain compliant. Empirical studies, performed over two large scale multi-label classification datasets, demonstrate that our method results in improvement across the board, and often entirely counteracts the effect of noise.

cs.LG↗

arXiv2022

Challenges in Applying Robotics to Retail Store Management

An autonomous retail store management system entails inventory tracking, store monitoring, and anomaly correction. Recent attempts at autonomous retail store management have faced challenges primarily in perception for anomaly detection, as well as new challenges arising in mobile manipulation for executing anomaly correction. Advances in each of these areas along with system integration are necessary for a scalable solution in this domain.

cs.RO↗

arXiv2022

Unsupervised Driving Behavior Analysis using Representation Learning and Exploiting Group-based Training

Driving behavior monitoring plays a crucial role in managing road safety and decreasing the risk of traffic accidents. Driving behavior is affected by multiple factors like vehicle characteristics, types of roads, traffic, but, most importantly, the pattern of driving of individuals. Current work performs a robust driving pattern analysis by capturing variations in driving patterns. It forms consistent groups by learning compressed representation of time series (Auto Encoded Compact Sequence) using a multi-layer seq-2-seq autoencoder and exploiting hierarchical clustering along with recommending the choice of best distance measure. Consistent groups aid in identifying variations in driving patterns of individuals captured in the dataset. These groups are generated for both train and hidden test data. The consistent groups formed using train data, are exploited for training multiple instances of the classifier. Obtained choice of best distance measure is used to select the best train-test pair of consistent groups. We have experimented on the publicly available UAH-DriveSet dataset considering the signals captured from IMU sensors (accelerometer and gyroscope) for classifying driving behavior. We observe proposed method, significantly outperforms the benchmark performance.

cs.LG↗