arXiv subjects

Mrinmoy Sarkar

Publications and source records attributed to Mrinmoy Sarkar.

At least 19 recordsLinked to original sources

arXiv2026

High-precision K2/TESS Photometry and HERMES Spectroscopy of Four Bright Field Stars

Space-based photometry from K2 and TESS, coupled with high-resolution spectroscopy, provides a unique opportunity to re-examine the variability and chemical nature of four bright stars (HD 73135, BD +19$^\circ$ 2045, BD +19$^\circ$ 2046, and TYC 1395-855-1), which were poorly characterised by the original ground-based campaign under the Nainital-Cape survey. We aim to establish the nature of the variability, chemical properties, and evolutionary status of these stars. We analysed ground-based Johnson $BV$ photometry combined with K2 and TESS time-series data to establish the nature of their variability. Using high-resolution HERMES spectroscopy, we determined their spectral classifications and chemical abundances. In addition, we used the inferred spectroscopic constraints with grid-based evolutionary modelling to derive their corresponding masses, radii, and ages. The frequency analysis reveals a diversity of low-amplitude variability across the sample. HD 73135 shows a persistent modulation near 1.5 d that is most consistent with rotation, although an ellipsoidal-binary interpretation cannot yet be excluded, while BD +19$^\circ$ 2045 exhibits multiple low-frequency signals and is identified as a new candidate $γ$ Doradus $g$-mode pulsator. BD +19$^\circ$ 2046 and TYC 1395-855-1 are non-variable or only marginally variable in K2 but display coherent low-frequency modulation in TESS of uncertain origin. Spectroscopically, HD 73135 is the only chemically peculiar star in the sample and shows a clear Am abundance pattern, whereas the other three stars are chemically normal. These results demonstrate the value of combining legacy survey data with contemporary photometric and spectroscopic analysis.

astro-ph.SR↗

arXiv2026

LiteVLA-H: Dual-Rate Vision-Language-Action Inference for Onboard Aerial Guidance and Semantic Perception

Vision-language-action (VLA) models have shown strong semantic grounding and task generalization in manipulation, but aerial deployment remains difficult because drones require low-latency closed-loop guidance under strict onboard compute and communication constraints. We present LiteVLA-H, a compact 256M-parameter VLA system designed for dual-rate operation on an NVIDIA Jetson AGX Orin: a fast outer-loop guidance mode for short action-token outputs and a slower semantic mode for scene understanding, hazard description, and operator-facing narration. The central empirical observation is that, in this compact edge regime, end-to-end latency is dominated by multimodal pre-fill rather than by the marginal cost of decoding a few extra tokens. This motivates a scheduler that issues reactive action tokens at 50.65,ms (19.74,Hz) while still supporting sentence-level semantic outputs at 149.90--164.57\ms (6.08--6.67,Hz) on the same embedded platform. To specialize the model without collapsing its descriptive competence, we use a knowledge-preserving fine-tuning recipe that mixes reactive flight data, aerial semantic data, and generic caption/VQA supervision. Beyond reporting current latency measurements, we position the system against recent state-of-the-art architectures, including AnywhereVLA, FutureVLA, and ReMem-VLA, showing that the measured action branch reaches a higher edge inference rate under our deployment conditions while retaining periodic semantic awareness.

cs.CV↗

arXiv2026

LiteVLA-Edge: Quantized On-Device Multimodal Control for Embedded Robotics

Vision-Language-Action (VLA) models provide a unified framework for perception, language conditioning, and action generation, but many existing systems remain difficult to deploy in embedded robotic settings because of their computational requirements and inference latency. In this paper, we present LiteVLA-Edge, a deployment-oriented VLA pipeline for fully on-device inference on Jetson Orin-class hardware. Our approach combines supervised image-to-action fine-tuning in FP32 with post-training 4-bit GGUF quantization and GPU-accelerated inference through the \texttt{llama.cpp} runtime. Under our deployment configuration, LiteVLA-Edge achieves a mean end-to-end latency of 150.5\,ms (approximately 6.6\,Hz) while operating entirely offline within a ROS~2-integrated perception--reasoning--action pipeline. Rather than introducing a new policy objective, our contribution is a practical systems path for executing compact multimodal control models locally on embedded hardware while preserving modular interfaces between perception, reasoning, and actuation. These results establish timing feasibility for reactive language-conditioned control and provide a reproducible baseline for future task-level evaluation of on-device VLAs in robotics.

cs.RO↗

arXiv2025

Lite VLA: Efficient Vision-Language-Action Control on CPU-Bound Edge Robots

The deployment of artificial intelligence models at the edge is increasingly critical for autonomous robots operating in GPS-denied environments where local, resource-efficient reasoning is essential. This work demonstrates the feasibility of deploying small Vision-Language Models (VLMs) on mobile robots to achieve real-time scene understanding and reasoning under strict computational constraints. Unlike prior approaches that separate perception from mobility, the proposed framework enables simultaneous movement and reasoning in dynamic environments using only on-board hardware. The system integrates a compact VLM with multimodal perception to perform contextual interpretation directly on embedded hardware, eliminating reliance on cloud connectivity. Experimental validation highlights the balance between computational efficiency, task accuracy, and system responsiveness. Implementation on a mobile robot confirms one of the first successful deployments of small VLMs for concurrent reasoning and mobility at the edge. This work establishes a foundation for scalable, assured autonomy in applications such as service robotics, disaster response, and defense operations.

cs.RO↗

arXiv2025

Asteroseismology of HD 23734, HD 68703, and HD 73345 using K2-TESS Space-based Photometry and High-resolution Spectroscopy

In this paper, we present a comprehensive study of three stars, HD 23734, HD 68703, and HD 73345, which were previously observed as chemically peculiar candidates within the Nainital-Cape survey and reported as null results for the pulsational variability. Frequency analyses of \ktwo\ and \tess\ time-series photometric data reveal the co-existence of rotational modulation and pulsation. We use the spectrum synthesis technique to determine fundamental parameters and chemical composition, which shows that all the three stars are likely to be chemically normal. The evolutionary status of the target stars corresponds to the main-sequence phases and places them within the $δ$ Scuti instability strip of the Hertzsprung-Russell diagram. The line profile variability is observed in all three stars, especially intriguing in HD\,68703 and a typical signature of the non-radial pulsation, demands further detailed examination. Using \tess\ photometry, we identified the radial modes of orders $n$=3 and 4 for HD\,23734, $n$=1, 3, and 4 for HD\,68703, and $n$=3,4 and 5 for HD\,73345. In addition to the presence of pulsation and rotation, HD\,73345 exhibits a steady increase in radial velocity that we interpret as the star being likely to be part of a long-period binary system. Finally, we propose an extended campaign aimed for the in-depth spectroscopic and spectropolarimetric study of selected pulsating stars monitored under the Nainital-Cape survey project.

astro-ph.SR↗

arXiv2025

Unveiling the Variability and Chemical Composition of AL Col

Using \tess\ short-cadence (120\,s) SAP flux, we identified a rotational frequency of 0.09655\,$\mathrm{d}^{-1}$ ($P_\mathrm{rot}=10.35733$\,d). Wavelet analysis reveals that while the amplitudes of the harmonic components vary over time, the strength of the primary rotational frequency remains stable. A SED analysis of multi-band photometric data yields an effective temperature ($T_\mathrm{eff}$) of {11,750\,K.} %MDPI: Comma added for five digits in the whole text, please check. High-resolution spectroscopic observations covering wavelengthrange 4500--7000\,Å provide refined estimates of \teff\, =\, 13,814\, $\pm$\, 400\,K, \logg\,=\, 4.09\, $\pm$\, 0.08\,dex, and \vsini\, =\, 16 $\pm$ 1\,\kms. Abundance analysis shows solar-like composition of O\,\textsc{ii}, Mg\,\textsc{ii}, S\,\textsc{ii}, and Ca\,\textsc{ii}, while helium is under-abundant by 0.62\,dex. Rare earth elements (REEs) exhibit over-abundances of up to 5.2\,dex, classifying the star as an Ap/Bp-type star. AL\,Col has a radius of $R = 3.74\,\pm\,0.48{\rm R_{\odot}}$, with its H--R diagram position estimating a mass of $M = 4.2\,\pm\,0.2{\rm M_{\odot}}$ and an age of $0.12\,\pm\,0.01$ Gyr, indicating that the star has slightly evolved from the main sequence. The \tess\ light curves were modeled using a three-evolving-spot configuration, suggesting the presence of differential rotation. This star is a promising candidate for future investigations of magnetic field diagnostics and the vertical stratification of chemical elements in its atmosphere.

astro-ph.SR↗

arXiv2025

Investigating Pulsating Variables and Eclipsing Binaries in NGC 2126 using Ground and Space-based Photometry, Astrometry, Spectroscopy and Modeling

Pulsating variables are prevalent in the classical δ Scuti instability strip of intermediate-age open star clusters. The cluster membership of these stars facilitates a comparative analysis of their evolution in analogous environments. In this study, we integrate ground-based observations, TESS Full Frame Images (FFIs), and Gaia DR3 data to investigate variable stars in the intermediate-age open star cluster NGC 2126. We performed ground-based time-series observations of NGC 2126 to identify variable stars within its vicinity. Next, we determined the membership of these stars using parallax and the proper motions from Gaia DR3 archive. Then, we searched the TESS Full Frame Images (FFIs) for counterparts to the variables identified above and performed their frequency analysis and classification. Finally, we modeled the light curves (LCs) of detected eclipsing binaries (EBs), including V551 Aur, which has a pulsating component. We found 25 members and 85 field variable stars. In TESS FFIs, we found LCs for 11 known variables and a new rotational variable. We determined that the pulsating EB V551 Aur is a member of the cluster. The low- and medium-resolution spectra revealed the line profile variation and the basic parameters for the star, respectively. Simultaneous modeling of the eclipses and the embedded pulsations resulted in improved orbital parameters for the binary system. We also report the determination of orbital parameters for the previously uncharacterized EB system UCAC4 700-043174.

astro-ph.SR↗

arXiv2024

Asteroseismology of the mild Am $δ$ Sct star HD 118660 : TESS photometry and modelling

We present the results of an asteroseismic study of HD 118660 (TIC 171729860), being a chemically peculiar (mild Am) star exhibiting $δ$ Scuti ($δ$ Sct) pulsations. It is based on the analysis of two sectors of time-series photometry from the space mission TESS and seismic modelling. It yielded the detection of 15 and 16 frequencies for TESS sectors 23 and 50, respectively. The identified pulsation modes include four radial ($\ell=0$) and five dipolar ($\ell=1$) ones. The radial modes are overtones with order $n$ ranging from $3$ and $6$. Such high values of $n$ are theoretically not expected for stars with the effective temperature of HD 118660 ($\rm T_{\rm eff}\approx 7550 \rm K$ ) located near the red edge of the $δ$ Sct instability strip. To estimate the asteroseismic parameters, we have generated a grid of stellar models assuming a solar metallicity ($Z=0.014$) and different values for the convective overshooting parameter ($0.1\leq α_{\rm ov}\leq 0.3$). We conclude that the analysis of the radial modes is insufficient to constrain $α_{\rm ov}$ and $Z$ for $δ$ Sct stars. The value for the equatorial velocity of HD 118660 derived from the seismic radius and the rotational frequency is consistent with values found in the literature.

astro-ph.SR↗

arXiv2024

Linear polarization study of open clusters towards the anticenter direction: Signature of the spiral arms

Our objective is to investigate the distribution of dust and associated large-scale structures of the Galaxy using optical linear polarization measurements of various open clusters located at different distances in the Galactic anticenter direction. We present R-band linear polarization observations of stars towards five open clusters: Kronberger~1, Berkeley~69, Berkeley~71, Berkeley~19, and King~8 in the anticenter direction. The polarization observations were carried out using AIMPOL instrument mounted on the 104 cm Sampurnanand telescope of ARIES, Nainital, making it the first study to target the polarization observations towards distant clusters ($\sim$6~kpc). We combined the observed polarization data with the distance information from the Gaia space telescope to infer the dust distribution along the line of sight. The variation in the degree of polarization and extinction with distance reveals the presence of multiple dust layers along each cluster direction. In addition, common foreground dust layers detected towards different cluster directions highlight the presence of global features such as spiral arms. Our results show that the dust clouds at 2~kpc towards Berkeley~69 and Berkeley~71 coincide with the Perseus arm, while the dust layer at $\sim$4~kpc towards distant clusters, Berkeley~19 and King~8, indicates the presence of the Outer arm. The large-scale dust distribution obtained by combining our polarization results with the previous polarization studies of nearby open clusters suggests that the anticenter direction is characterized by low extinction, homogeneous dust distribution with somewhat uniform orientation of the plane-of-sky component of the magnetic field along the line of sight. Our study demonstrates the utility of polarization as a tool to study the large-scale dust distribution.

astro-ph.GA↗

arXiv2024

Amplitude Modulation in a Delta Scuti star HD118660

In this paper, we report the detection of amplitude modulation in a delta Scuti star HD118660. We found that the p-mode frequency at 24.3837 c/d varies periodically in amplitude with frequency 0.0558 c/d. However, all other modes are stable in both amplitude and phase which is clear evidence of non-conservation of visible pulsation mode energy. We constructed a two-frequency model by superimposing two sinusoids with frequencies n1 = 24.3837 c/d and n2 = 24.4420 c/d and corresponding phases f1 = 0:5211 rad and f2 = 0:9481 rad to mimic the observed variations of amplitude and phase with time. The plausible explanation of the amplitude modulation in HD118660 is due to beating of two unresolved closed frequencies n1 and n2.

astro-ph.SR↗

arXiv2023

Optical polarisation study of Galactic Open clusters

Dust is a ubiquitous component in our Galaxy. It accounts for only $1\%$ mass of the ISM but still is an essential part of the Galaxy. It affects our view of the Galaxy by obscuring the starlight at shorter wavelengths and re-emitting in longer wavelengths. Studying the dust distribution in the Galaxy at longer wavelengths may cause discrepancies due to distance ambiguity caused by unknown Galactic potential. However, another aspect of dust, i.e., the polarisation of the background starlight, when combined with distance information, will help to give direct observational evidence of the number of dust clouds encountered in the line of sight. We observed 15 open clusters distributed at increasing distances in three lines of sight using two Indian national facilities. The measured polarisation results used to scrutinize the dust distribution and orientation of the local plane of sky magnetic fields towards selected directions. The analysis of the stars observed towards the distant cluster King 8 cluster shows two foreground layers at a distance of $\sim 500$ pc and $\sim$ 3500 pc. Similar analysis towards different clusters also results in multiple dust layers.

astro-ph.GA↗

arXiv2022

Mitigating shortage of labeled data using clustering-based active learning with diversity exploration

In this paper, we proposed a new clustering-based active learning framework, namely Active Learning using a Clustering-based Sampling (ALCS), to address the shortage of labeled data. ALCS employs a density-based clustering approach to explore the cluster structure from the data without requiring exhaustive parameter tuning. A bi-cluster boundary-based sample query procedure is introduced to improve the learning performance for classifying highly overlapped classes. Additionally, we developed an effective diversity exploration strategy to address the redundancy among queried samples. Our experimental results justified the efficacy of the ALCS approach.

cs.LG↗

arXiv2022

Salt Detection Using Segmentation of Seismic Image

In this project, a state-of-the-art deep convolution neural network (DCNN) is presented to segment seismic images for salt detection below the earth's surface. Detection of salt location is very important for starting mining. Hence, a seismic image is used to detect the exact salt location under the earth's surface. However, precisely detecting the exact location of salt deposits is difficult. Therefore, professional seismic imaging still requires expert human interpretation of salt bodies. This leads to very subjective, highly variable renderings. Hence, to create the most accurate seismic images and 3D renderings, we need a robust algorithm that automatically and accurately identifies if a surface target is a salt or not. Since the performance of DCNN is well-known and well-established for object recognition in images, DCNN is a very good choice for this particular problem and being successfully applied to a dataset of seismic images in which each pixel is labeled as salt or not. The result of this algorithm is promising.

cs.CV↗

arXiv2021

DA$^{\textbf{2}}$-Net : Diverse & Adaptive Attention Convolutional Neural Network

Standard Convolutional Neural Network (CNN) designs rarely focus on the importance of explicitly capturing diverse features to enhance the network's performance. Instead, most existing methods follow an indirect approach of increasing or tuning the networks' depth and width, which in many cases significantly increases the computational cost. Inspired by a biological visual system, we propose a Diverse and Adaptive Attention Convolutional Network (DA$^{2}$-Net), which enables any feed-forward CNNs to explicitly capture diverse features and adaptively select and emphasize the most informative features to efficiently boost the network's performance. DA$^{2}$-Net incurs negligible computational overhead and it is designed to be easily integrated with any CNN architecture. We extensively evaluated DA$^{2}$-Net on benchmark datasets, including CIFAR100, SVHN, and ImageNet, with various CNN architectures. The experimental results show DA$^{2}$-Net provides a significant performance improvement with very minimal computational overhead.

cs.CV↗

arXiv2021

A Supervised Feature Selection Method For Mixed-Type Data using Density-based Feature Clustering

Feature selection methods are widely used to address the high computational overheads and curse of dimensionality in classifying high-dimensional data. Most conventional feature selection methods focus on handling homogeneous features, while real-world datasets usually have a mixture of continuous and discrete features. Some recent mixed-type feature selection studies only select features with high relevance to class labels and ignore the redundancy among features. The determination of an appropriate feature subset is also a challenge. In this paper, a supervised feature selection method using density-based feature clustering (SFSDFC) is proposed to obtain an appropriate final feature subset for mixed-type data. SFSDFC decomposes the feature space into a set of disjoint feature clusters using a novel density-based clustering method. Then, an effective feature selection strategy is employed to obtain a subset of important features with minimal redundancy from those feature clusters. Extensive experiments as well as comparison studies with five state-of-the-art methods are conducted on SFSDFC using thirteen real-world benchmark datasets and results justify the efficacy of the SFSDFC method.

cs.LG↗

arXiv2021

A Framework for eVTOL Performance Evaluation in Urban Air Mobility Realm

In this paper, we developed a generalized simulation framework for the evaluation of electric vertical takeoff and landing vehicles (eVTOLs) in the context of Unmanned Aircraft Systems (UAS) Traffic Management (UTM) and under the concept of Urban Air Mobility (UAM). Unlike most existing studies, the proposed framework combines the utilization of UTM and eVTOLs to develop a realistic UAM testing platform. For this purpose, we first enhanced an existing UTM simulator to simulate the real-world UAM environment. Then, instead of using a simplified eVOTL model, a realistic eVTOL design tool, namely SUAVE, is employed and an dilation sub-module is introduced to bridge the gap between the UTM simulator and SUAVE eVTOL performance evaluation tool to elaborate the complete mission profile. Based on the developed simulation framework, experiments are conducted and the results are presented to analyze the performance of eVTOLs in the UAM environment.

cs.RO↗

arXiv2021

A Clustering-based Framework for Classifying Data Streams

The non-stationary nature of data streams strongly challenges traditional machine learning techniques. Although some solutions have been proposed to extend traditional machine learning techniques for handling data streams, these approaches either require an initial label set or rely on specialized design parameters. The overlap among classes and the labeling of data streams constitute other major challenges for classifying data streams. In this paper, we proposed a clustering-based data stream classification framework to handle non-stationary data streams without utilizing an initial label set. A density-based stream clustering procedure is used to capture novel concepts with a dynamic threshold and an effective active label querying strategy is introduced to continuously learn the new concepts from the data streams. The sub-cluster structure of each cluster is explored to handle the overlap among classes. Experimental results and quantitative comparison studies reveal that the proposed method provides statistically better or comparable performance than the existing methods.

cs.LG↗

arXiv2019

Digital Controllers in Discrete and Continuous Time Domains for a Robot Arm Manipulator

This paper articulates design and performance analysis of digital controllers in discrete and continuous time domains for a single-joint robot arm manipulator. The investigated robot arm system is modeled as a single degree of freedom (DOF) plant and there is a feedback sensor implying a closed-loop system. The design approach incorporates discrete (z-plane) and continuous-time (warped s-plane or w-plane) domain parameters. Four digital controllers - phase-lag, phase-lead, proportional-integral (PI) and proportional-integral-derivative (PID) are theoretically designed and implemented to achieve a phase margin of 40 deg. for the compensated system. For performance evaluations, Bode plots of the compensated open-loop systems and step response characteristics of the closed-loop systems are determined.

eess.SY↗