arXiv subjects

Sarvesh Kumar Yadav

Publications and source records attributed to Sarvesh Kumar Yadav.

10 recordsLinked to original sources

arXiv2026

Demonstrating the Time-Domain Capabilities of the 4-m International Liquid Mirror Telescope: An Early Census of Transient and Variable Detections

The PyLMT transient detection pipeline has been operational since November 2023, detecting transient and variable objects in the ILMT images in almost real time. Using the image subtraction technique, nearly 3700 CCD frames have been analyzed by the automated pipeline, generating nearly 23,000 alerts for the detection of verified transient candidates and cataloged variable sources. Around 21,000 of the alerts correspond to known MPC asteroids, nearly 2000 correspond to variable stars (including eclipsing binaries, RR Lyrae, Delta Scuti, T-Tauri, etc.), 509 correspond to variable AGNs (including QSOs, Seyfert galaxies, and blazars), 21 supernova candidates, and several other interesting candidates. We provide a concise overview of the detections and their significance, emphasizing the surveys potential contributions to a broad class of astrophysical and scientific cases. A transient detection dashboard called DART was developed using Streamlit to visualize and categorize candidates based on PyLMT and SIMBAD classifications. It includes cone-search functionality and displays key metadata, offering an intuitive interface that is publicly accessible. Our results demonstrate the viability of liquid mirror telescopes such as the ILMT for time-domain astronomy, emphasizing the important role that small-field survey facilities can play in systematic transient science programs.

astro-ph.IM↗

arXiv2026

Astrometric Calibration of the 4-m International Liquid Mirror Telescope Observations

The 4-m International Liquid Mirror Telescope (ILMT) is a dedicated time domain survey telescope that continuously scans the zenithal sky over the Indian Himalayas in the g', r' and i' optical bands. Its unique capability to repeatedly image the same strip of sky every night makes it a highly useful instrument for the photometric and astrometric studies of Solar System, Galactic and extragalactic objects. We present a robust astrometric calibration pipeline developed for the ILMT data obtained in the time delay integration (TDI) mode. The pipeline uses a linear transformation model from pixel to world coordinates, with a second order correction for the asymmetric optical distortions introduced by the telescope's optical corrector, and ties the astrometric solution to the Gaia DR3 reference frame. The pipeline is integrated to the routine ILMT data processing workflow. Using data from the first four observing cycles (2022-2025), we present the first assessment of the astrometric performance of the pipeline based on positional residuals of sources cross-matched with Gaia DR3. The pipeline achieves a typical astrometric precision of ~100 milliarcseconds (mas), reaching ~70-80 mas for moderately bright sources (G~16.5-18.5). These results, based on 347 nights of data, demonstrate the stability and reliability of ILMT astrometry over multi-year timescales. The astrometrically calibrated data from these four observing cycles have been made publicly available to the astronomical community. This work establishes a validated framework for precision astrometry with zenith-pointing TDI surveys and provides a foundation for future time-domain studies with ILMT, including variability characterization, transient localization, and long-term positional monitoring.

astro-ph.IM↗

arXiv2026

Detection and identification of asteroids with the 4-m ILMT

The International Liquid Mirror Telescope (ILMT) covers a 22.3' wide strip of sky in declination (δ), centred at δ = +29° 21' 41.4'' and right ascension (α) in the range 0 h <= α < 24 h. Having a short focal length (f /D ~ 2.4) and a large diameter (4 m), makes the ILMT an excellent asteroid hunter. The ILMT began its 4th cycle in October 2024, running through May 2025. The astrometric accuracy has been improved to 0.1'' , and the PyLMT - a detection and classification pipeline -, has been fine-tuned using data from previous cycles. The current detection rate is tens of transients detected each night with high accuracy in classification and identification. We present statistical results for the asteroids detected during ILMT's Cycles 1-4. We first evaluate the astrometric performance of the detections across different ecliptic latitude ranges. We then describe the positions, apparent motions, and V magnitudes predicted by the Minor Planet Center (MPC) for the asteroids observed in the SDSS g', r', and i' bands. Finally, we assess the ILMT's potential for detecting near-Earth objects (NEOs), potentially hazardous asteroids (PHAs), and comets.

astro-ph.EP↗

arXiv2026

Transfer learning for transient search with small-field optical survey telescopes

The advent of optical sky surveys has enabled several automated programs for searching transients. Many of these programs extensively use supervised machine learning (ML) algorithms to automate these searches. Effective implementation of such a strategy has an advantage over non-automated methods of transient search in terms of reduced manual labour and reporting latency. Training the relevant ML algorithms often requires extensive labelled training datasets that might not be readily available for new or small field-of-view survey telescopes. Transfer Learning (TL) is an ML technique that is often employed to address this issue by transferring knowledge from a pre-trained model, trained on an extensive dataset for a related task, to enhance performance on a new task with a limited dataset available. This paper demonstrates TL for a Convolutional Neural Network (CNN)-based real/bogus classifier model for transient detection between extensive publicly available image data from the Zwicky Transient Facility (ZTF) and a small and labelled dataset from the 4-m International Liquid Mirror Telescope (ILMT). The same technique was employed to train two different types of transient alert classifiers to characterise the detected candidates based on detection image stamps into 3 and 4 classes, respectively. The resulting model for the real/bogus classifier achieved an accuracy of 97.3% on the test dataset. Additionally, an accuracy of 92.9% was achieved for the 3-class classifier and 85.6% for the 4-class classifier. Furthermore, the statistical significance of the effectiveness of this technique was established with an unpaired t-test between TL models and baseline models trained without TL.

astro-ph.IM↗

arXiv2025

SN 2024aecx: a fast-evolving Type IIb supernova with a prominent shock-cooling peak

SN 2024aecx is a nearby ($\sim$11 Mpc) Type IIb SN discovered within $\sim$1 d after explosion. In this paper we report high-cadence photometric (typically 0.5$\sim$1 day) and spectroscopic follow-up observations, conducted from as early as 0.27 d post discovery out to the nebular phase at 158.4 d. We analyze the environment of SN 2024aecx and derive a new distance (11.3$\pm$1.1 Mpc), metallicity and host extinction. The light curve exhibits a hot and luminous shock-cooling peak at the first few days, followed by a main peak with very rapid post-maximum decline. The earliest spectra are blue and featureless, while from 2.3 d after discovery prominent P-Cygni profiles emerge. At nebular phase, the emission lines exhibit asymmetric and double-peaked profiles, indicating asphericity and/or early dust formation in the ejecta. Nebular spectral modelling indicates a blueshifted O-rich clump moving toward observer, and the $[\text{OI}]/[\text{CaII}]$ line ratio suggests an intermediate-mass progenitor. We simulated the progenitor and explosion using a two-component model of shock cooling and radioactive $^{56}$Ni heating; our model favors an extended, low-mass H-rich envelope with $M_{\mathrm{e}} = 0.04\pm{0.01} M_{\odot}$ and a low ejecta mass of$M_{\mathrm{ej}} = 1.55^{+0.18}_{-0.14} M_{\odot}$. And the nebular-phase spectra and light-curve modelling both suggest that it most likely originated from an intermediate-mass binary progenitor system. The comprehensive monitoring of SN 2024aecx, coupled with the detailed characterization of its local environment, establishes it as a benchmark event for probing the progenitors and explosion mechanisms of Type IIb SNe.

astro-ph.SR↗

arXiv2024

A perceptron based ILC method to obtain accurate CMB B-mode angular power spectrum

Observations of the Cosmic Microwave Background (CMB) radiation have made significant contributions to our understanding of cosmology. While temperature observations of the CMB have greatly advanced our knowledge, the next frontier lies in detecting the elusive B-modes and obtaining precise reconstructions of the CMB's polarized signal in general. In anticipation of proposed and upcoming CMB polarization missions, this study introduces a novel method for accurately determining the angular power spectrum of CMB B-modes. We have developed a Neural Network-based approach to enhance the performance of the Internal Linear Combination (ILC) technique. Our method is applied to the frequency channels of the proposed ECHO (Exploring Cosmic History and Origins) mission and its performance is rigorously assessed. Our findings demonstrate the method's efficiency in achieving precise reconstructions of CMB B-mode angular power spectra, with errors constrained primarily by cosmic variance.

astro-ph.CO↗

arXiv2024

Accurate and Unbiased Reconstruction of CMB B Mode using Deep Learning

An ingeniously designed autoencoder (PrimeNet) using simulated observations of future generation ECHO satellite mission recovers CMB B mode map, angular spectrum for multipoles $\ell \lesssim 9$ and tensor to scalar ratio $r$ {\it limited only by cosmic variance down to $r= 0.0001$ and below}. We use diverse, realistically complex and detailed foreground models. PrimeNet predicts accurate results even when data with $r=0$ are tested which were not used in training, implying robust and efficient predictive power. The work eliminates a major bottleneck of weak CMB B mode reconstruction and takes a leap forward for understanding fundamental physics of the primordial Universe.

astro-ph.CO↗

arXiv2022

Investigating non-Gaussianity in Cosmic Microwave Background Temperature Maps using Spherical Harmonic Phases

In this article, we extend previous studies based on CMB spherical harmonic phases (SHP) to examine the validity of the hypothesis that the temperature field of the CMB is consistent with a Gaussian random field (GRF). The null hypothesis is that the corresponding CMB SHP are independent and identically distributed in terms of a uniform distribution in the interval [0, 2$π$] \citep{1986ApJ...304...15B,2013rossmanith}. We devise a new model-independent method where we use ordered and non-parametric Rao's statistic, based on sample arc-lengths to comprehensively test uniformity and independence of SHP. We performed our analysis on the scales limited by spherical harmonic modes $\le$ 128, to restrict ourselves to signal-dominated regions. To find the non-uniform or dependent sets of SHP, we calculate the statistic for the data and 10000 Monte Carlo simulated uniformly random sets of SHP and use 0.05 and 0.001 $α$ levels to distinguish between statistically significant and highly significant detections. We first establish the performance of our method using simulated Gaussian, non-Gaussian CMB temperature maps, along with observed non-Gaussian 100 and 143 GHz Planck channel maps. We find that our method performs efficiently and accurately in detecting phase correlations generated in all of the non-Gaussian simulations and observed foreground contaminated 100 and 143 GHz Planck channel temperature maps. We apply our method on the Planck satellite mission's final released CMB temperature anisotropy maps- COMMANDER, SMICA, NILC, and SEVEM along with WMAP 9 year released ILC map. We report that SHP corresponding to some of the $m$-modes is non-uniform, some of the $\ell$ mode SHP and neighboring mode pair SHP are correlated in cleaned CMB maps. The detection of non-uniformity or correlation in the SHP indicates the presence of non-Gaussian signals in the foreground minimized CMB maps.

astro-ph.CO↗

arXiv2020

A Bayesian ILC method for CMB B-mode posterior estimation and reconstruction of primordial gravity wave signal

The Cosmic Microwave Background (CMB) radiation B mode polarization signal contains the unique signature of primordial metric perturbations produced during the inflation. The separation of the weak CMB B-mode signal from strong foreground contamination in observed maps is a complex task, and proposed new generation low noise satellite missions compete with the weak signal level of this gravitational background. In this article, for the first time, we employ a foreground model-independent internal linear combination (ILC) method to reconstruct the CMB B mode signal using simulated observations over large angular scales of the sky of 6 frequency bands of future generation CMB mission Probe of Inflation and Cosmic Origins (PICO). We estimate the joint CMB B mode posterior density following the interleaving Gibbs steps of B mode angular power spectrum and cleaned map samples using the ILC method. We extend and improve the earlier reported Bayesian ILC method to analyze weak CMB B mode reconstruction by introducing noise bias corrections at two stages during the ILC weight estimation. By performing $200$ Monte Carlo simulations of the Bayesian ILC method, we find that our method can reconstruct the CMB signals and the joint posterior density accurately over large angular scales of the sky. We estimate Blackwell-Rao statistics of the marginal density of CMB B mode angular power spectrum and use them to estimate the joint density of scalar to tensor ratio $r$ and a lensing power spectrum amplitude $A^{\textrm{lens}}$. Using $200$ Monte Carlo simulations of the delensing approach, we find that our method can achieve an unbiased detection of the primordial gravitational wave signal $r$ with more than 8$σ$ significance for levels of $r \geqslant 0.01$.

astro-ph.CO↗

arXiv2016

An Improved Diffuse Foreground Subtraction by ILC method: CMB Map and Angular Power Spectrum using Planck and WMAP Observations

We report an improved technique for diffuse foreground minimization from Cosmic Microwave Background (CMB) maps using a new multi-phase iterative internal-linear-combination (ILC) approach in harmonic space. The new procedure consists of two phases. In phase 1, a diffuse foreground cleaned map is obtained by performing a usual ILC operation in the harmonic space in a single iteration over the desired portion of the sky. In phase 2, we obtain the final foreground cleaned map using an iterative ILC approach also in the harmonic space, however, now, during each iteration of foreground minimization, some of the regions of the sky that are not being cleaned in the current iteration, are replaced by the corresponding cleaned portions of the phase 1 cleaned map. The new ILC method nullifies a foreground leakage signal that is otherwise inevitably present in the old and usual harmonic space iterative ILC method. The new method is flexible to handle input frequency maps, irrespective of whether or not they initially have the same instrumental and pixel resolution, by bringing them to a common and maximum possible beam and pixel resolution at the beginning of the analysis. This dramatically reduces data redundancy and hence memory usage and computational cost. During the ILC weight calculation it avoids any need to deconvolve partial sky spherical harmonic coefficients by the beam and pixel window functions, which in strict mathematical sense, is not well-defined for azimuthally symmetric window functions. Using WMAP 9-year and Planck-2015 published frequency maps we obtain a pair of foreground cleaned CMB maps and CMB angular power spectrum. Our power spectrum match well with Planck-2015 results, with some difference. Finally, we show that the weights for ILC foreground minimization have an intrinsic characteristic that it tends to produce a statistically isotropic CMB map as well.

astro-ph.CO↗