arXiv subjects

Aditi Agarwal

Publications and source records attributed to Aditi Agarwal.

17 recordsLinked to original sources

arXiv2026

Intraday Optical Variability of BL Lacertae during its Highly Active 2020-2024 Phase

We present an analysis of the intraday flux and spectral variability of BL Lacertae from 2020 September 30 to 2024 December 7, covering its highest recorded brightness and low, intermediate, and high flux states. Our study involved 62 nights of multi-band (BVRI) optical monitoring using four ground-based telescopes located in Egypt, Türkiye, and Bulgaria. We assessed intraday flux variability using the power-enhanced F-test and the nested ANOVA test. Significant variability was detected in 88 out of 117 light curves, consistent with previous studies of this object during active epochs. The maximum variability amplitude is 44.5 per cent in the B band. Spectral analysis reveals a bluer-when-brighter trend during intraday flares, supporting a synchrotron origin for the variable emission. For a subset of well-sampled flares, we model their profiles with a double exponential function, deriving rise and decay time-scales, thereby constraining the characteristic times of particle acceleration and cooling processes within the relativistic jet. Assuming a turbulent jet model, we determined limits on the radii and magnetic field strengths of the emitting regions. We detected soft time lags for a multi-band flare and from their analysis, derived the Doppler factor and magnetic field strength of the corresponding emitting region. Our long-term, high-cadence study confirms that BL Lacertae was in an exceptionally active phase during the 2020-2024 period, with intraday variability being a common phenomenon. The results underscore the dynamic nature of the jet emission region and provide valuable observational constraints for models of blazar variability and jet physics.

astro-ph.HE↗

arXiv2026

Agricultural Landscape Understanding At Country-Scale

Comprehensive agricultural landscape understanding is critical for addressing global challenges in food security, climate change, and resource management. This requires mapping not just crop fields, but also vital features like trees and water bodies which form an intricate mosaic in complex \textit{smallholder} systems dominating the Global South. Previous efforts to develop such land use maps have been limited by a narrow focus on methods for field delineation only, and also do not develop robust post-processing steps essential for real-world deployment. Further, to our knowledge, no prior system for smallholder farms has been deployed and evaluated at a national scale. This work addresses these limitations by presenting the first national-scale agricultural mapping system that moves beyond simple field delineation to enable segmentation of agricultural instances like fields, trees and water bodies. Our system is refined for real-world application using novel post-processing heuristics to ensure map consistency and accuracy, and is validated through a rigorous, multi-faceted evaluation process. Fine-grained land use maps generated by our system are publicly accessible via an API at \textit{\href{http://agri.withgoogle.com}{http://agri.withgoogle.com}}, enabling a wide range of applications from precision agriculture and policy-making to advancing global sustainability development goals.

cs.CV↗

arXiv2026

LogogramNLP: Comparing Visual and Textual Representations of Ancient Logographic Writing Systems for NLP

Standard natural language processing (NLP) pipelines operate on symbolic representations of language, which typically consist of sequences of discrete tokens. However, creating an analogous representation for ancient logographic writing systems is an extremely labor intensive process that requires expert knowledge. At present, a large portion of logographic data persists in a purely visual form due to the absence of transcription -- this issue poses a bottleneck for researchers seeking to apply NLP toolkits to study ancient logographic languages: most of the relevant data are images of writing. This paper investigates whether direct processing of visual representations of language offers a potential solution. We introduce LogogramNLP, the first benchmark enabling NLP analysis of ancient logographic languages, featuring both transcribed and visual datasets for four writing systems along with annotations for tasks like classification, translation, and parsing. Our experiments compare systems that employ recent visual and text encoding strategies as backbones. The results demonstrate that visual representations outperform textual representations for some investigated tasks, suggesting that visual processing pipelines may unlock a large amount of cultural heritage data of logographic languages for NLP-based analyses.

cs.CL↗

arXiv2025

Segmentation-Aware Latent Diffusion for Satellite Image Super-Resolution: Enabling Smallholder Farm Boundary Delineation

Delineating farm boundaries through segmentation of satellite images is a fundamental step in many agricultural applications. The task is particularly challenging for smallholder farms, where accurate delineation requires the use of high resolution (HR) imagery which are available only at low revisit frequencies (e.g., annually). To support more frequent (sub-) seasonal monitoring, HR images could be combined as references (ref) with low resolution (LR) images -- having higher revisit frequency (e.g., weekly) -- using reference-based super-resolution (Ref-SR) methods. However, current Ref-SR methods optimize perceptual quality and smooth over crucial features needed for downstream tasks, and are unable to meet the large scale-factor requirements for this task. Further, previous two-step approaches of SR followed by segmentation do not effectively utilize diverse satellite sources as inputs. We address these problems through a new approach, $\textbf{SEED-SR}$, which uses a combination of conditional latent diffusion models and large-scale multi-spectral, multi-source geo-spatial foundation models. Our key innovation is to bypass the explicit SR task in the pixel space and instead perform SR in a segmentation-aware latent space. This unique approach enables us to generate segmentation maps at an unprecedented 20$\times$ scale factor, and rigorous experiments on two large, real datasets demonstrate up to $\textbf{25.5}$ and $\textbf{12.9}$ relative improvement in instance and semantic segmentation metrics respectively over approaches based on state-of-the-art Ref-SR methods.

cs.CV↗

arXiv2025

A Novel AI-Driven System for Real-Time Detection of Mirror Absence, Helmet Non-Compliance, and License Plates Using YOLOv8 and OCR

Road safety is a critical global concern, with manual enforcement of helmet laws and vehicle safety standards (e.g., rear-view mirror presence) being resource-intensive and inconsistent. This paper presents an AI-powered system to automate traffic violation detection, significantly enhancing enforcement efficiency and road safety. The system leverages YOLOv8 for robust object detection and EasyOCR for license plate recognition. Trained on a custom dataset of annotated images (augmented for diversity), it identifies helmet non-compliance, the absence of rear-view mirrors on motorcycles, an innovative contribution to automated checks, and extracts vehicle registration numbers. A Streamlit-based interface facilitates real-time monitoring and violation logging. Advanced image preprocessing enhances license plate recognition, particularly under challenging conditions. Based on evaluation results, the model achieves an overall precision of 0.9147, a recall of 0.886, and a mean Average Precision (mAP@50) of 0.843. The mAP@50 95 of 0.503 further indicates strong detection capability under stricter IoU thresholds. This work demonstrates a practical and effective solution for automated traffic rule enforcement, with considerations for real-world deployment discussed.

cs.CV↗

arXiv2025

PyHexTop: a compact Python code for topology optimization using hexagonal elements

Python serves as an open-source and cost-effective alternative to the MATLAB programming language. This paper introduces a concise topology optimization Python code, named ``\texttt{PyHexTop}," primarily intended for educational purposes. Code employs hexagonal elements to parameterize design domains as such elements provide checkerboard-free optimized design naturally. \texttt{PyHexTop} is developed based on the ``\texttt{HoneyTop90}" MATLAB code~\cite{kumar2023honeytop90} and uses the \texttt{NumPy} and \texttt{SciPy} libraries. Code is straightforward and easily comprehensible, proving a helpful tool that can help people new in the topology optimization field to learn and explore. \texttt{PyHexTop} is specifically tailored to address compliance minimization with specified volume constraints. The paper provides a detailed explanation of the code for solving the Messerschmitt-Bolkow-Blohm beam and extensions to solve problems different problems. The code is publicly shared at: https://github.com/PrabhatIn/PyHexTop

cs.CE↗

arXiv2024

Ultraviolet flux and spectral variability study of blazars observed with UVIT/AstroSat

Blazars, the peculiar class of active galactic nuclei (AGN), are known to show flux variations across the accessible electromagnetic spectrum. Though they have been studied extensively for their flux variability characteristics across wavelengths, information on their ultraviolet (UV) flux variations on time scales of hours is very limited. Here, we present the first UV flux variability study on intraday time scales of a sample of 10 blazars comprising 2 flat spectrum radio quasars (FSRQs) and 8 BL Lacertae objects (BL Lacs). These objects, spanning a redshift (z) range of 0.034 <= z <= 1.003, were observed in the far-UV (FUV: 1300 - 1800 \textÅ) and near-UV (NUV: 2000 - 3000 \textÅ) wavebands using the ultraviolet imaging telescope on board AstroSat. UV flux variations on time scales of hours were detected in 9 sources out of the observed 10 blazars. The spectral variability analysis showed a bluer-when-brighter trend with no difference in the UV spectral variability behavior between the studied sample of FSRQs and BL Lacs. The observed UV flux and spectral variability in our sample of both FSRQs and BL Lacs revealed that the observed UV emission in them is dominated by jet synchrotron process.

astro-ph.HE↗

arXiv2024

Investigating Optical Variability of the Blazar S5 0716+714 On Diverse Time-scales

We present the results of the observational study of the blazar S5 0716+716 in the optical bands B, V, R, and I between March 2019 and August 2023 to investigate its variability on diverse time-scales. The blazar was followed up by the T60 robotic telescope in Turkey for 416 nights to obtain long-term variability during this period. In order to search for intraday variability of the object, we have carried out 21 nights of observations with the T100 telescope for at least 1 hour. The blazar showed a ~2.47 mag variation in the optical R-band during our monitoring period, the brightest state on 18.01.2020 (MJD 58866) as R=12.109$\pm$0.011 and the faintest state on 23.03.2019 (MJD 58565) as R=14.580$\pm$0.013. We employed the nested ANOVA test and the power enhanced F-test to quantify intraday variability which showed that the blazar was significantly variable in the R-band on 12 out of 21 nights. Correlation analysis of the light curves shows that the emission in the BVRI optical bands was strongly correlated both in the short and long term without any time lag. The blazar has likely quasi-periods of 186$\pm$30, 532$\pm$76 days in the optical R-band light curve according to the WWZ, and the LS periodogram. The IDV and LTV features are discussed within the frame of prospective scenarios.

astro-ph.HE↗

arXiv2023

Multi-wavelength study of TeV blazar 1ES 1218+304 using gamma-ray, X-ray and optical observations

We report the multi-wavelength study for a high-synchrotron-peaked BL Lac 1ES 1218+304 using near-simultaneous data obtained during the period from January 1, 2018, to May 31, 2021 (MJD 58119-59365) from various instruments including Fermi-LAT, Swift-XRT, AstroSat, and optical from Swift-UVOT $\&$ TUBITAK observatory in Turkey. The source was reported to be flaring in TeV $γ$-ray band during 2019, but no significant variation is observed with Fermi-LAT. A sub-hour variability is seen in the SXT light curve, suggesting a compact emission region for their variability. However, hour scale variability is observed in the $γ$-ray light curve. A "softer-when-brighter" trend is observed in $γ$-rays, and an opposite trend is seen in X-rays suggesting both emissions are produced via two different processes as expected from an HBL source. We have chosen the two epochs in January 2019 to study and compare their physical parameters. A joint fit of SXT and LAXPC provides a constraint on the synchrotron peak, roughly estimated to be $\sim$1.6 keV. A clear shift in the synchrotron peak is observed from $\sim$1 keV to above 10 keV revealing its extreme nature or behaving like an EHBL-type source. The optical observation provides color-index variation as "blue-when-brighter". The broadband SED is fitted with a single-zone SSC model, and their parameters are discussed in the context of a TeV blazar and the possible mechanism behind the broadband emission.

astro-ph.HE↗

arXiv2023

Classification of blazar candidates of unknown type in Fermi 4LAC by unanimous voting from multiple Machine Learning Algorithms

The Fermi fourth catalog of active galactic nuclei (AGNs) data release 3 (4LAC-DR3) contains 3407 AGNs, out of which 755 are flat spectrum radio quasars (FSRQs), 1379 are BL Lacertae objects (BL Lacs), 1208 are blazars of unknown (BCUs) type, while 65 are non AGNs. Accurate categorization of many unassociated blazars still remains a challenge due to the lack of sufficient optical spectral information. The aim of this work is to use high-precision, optimized machine learning (ML) algorithms to classify BCUs into BL Lacs and FSRQs. To address this, we selected the 4LAC-DR3 Clean sample (i.e., sources with no analysis flags) containing 1115 BCUs. We employ five different supervised ML algorithms, namely, random forest, logistic regression, XGBoost, CatBoost, and neural network with seven features: Photon index, synchrotron-peak frequency, Pivot Energy, Photon index at Pivot\_Energy, Fractional variability, $νFν$ at synchrotron-peak frequency, and Variability index. Combining results from all models leads to better accuracy and more robust predictions. These five methods together classified 610 BCUs as BL Lacs and 333 BCUs as FSRQs with a classification metric area under the curve $>$ 0.96. Our results are significantly compatible with recent studies as well. The output from this study provides a larger blazar sample with many new targets that could be used for forthcoming multi-wavelength surveys. This work can be further extended by adding features in X-rays, UV, visible, and radio wavelengths.

astro-ph.HE↗

arXiv2023

Analysis of the intra-night variability of BL Lacertae during its August 2020 flare

We present an analysis of the $BVRI$ photometry of the blazar BL Lacertae on diverse timescales from mid-July to mid-September 2020. We have used 11 different optical telescopes around the world and have collected data over 84 observational nights. The observations cover the onset of a new activity phase of BL Lacertae started in August 2020 (termed as the August 2020 flare by us), and the analysis is focused on the intra-night variability. On short-term timescales, (i) flux varied with ~2.2\,mag in $R$ band, (ii) the spectral index was found to be weakly dependent on the flux (i.e., the variations could be considered mildly chromatic) and (iii) no periodicity was detected. On intra-night timescales, BL Lacertae was found to show bluer-when-brighter chromatism predominantly. We also found two cases of significant inter-band time lags of the order of a few minutes. The duty cycle of the blazar during the August 2020 flare was estimated to be quite high (~90\% or higher). We decomposed the intra-night light curves into individual flares and determined their characteristics. On the basis of our analysis and assuming the turbulent jet model, we determined some characteristics of the emitting regions: Doppler factor, magnetic field strength, electron Lorentz factor, and radius. The radii determined were discussed in the framework of the Kolmogorov theory of turbulence. We also estimated the weighted mean structure function slope on intra-night timescales, related it to the slope of the power spectral density, and discussed it with regard to the origin of intra-night variability.

astro-ph.HE↗

arXiv2021

A comprehensive study of 2019-2020 flare of OJ 287 using AstroSat, Swift, and NuSTAR

OJ 287 is a well-studied binary black hole system, that occasionally exhibits bright X-ray and optical flares. Here we present a detailed spectral study of its second brightest X-ray flare observed during 2019-2020 using archival Swift and NuSTAR observations along with ToO observations from AstroSat. The entire flaring period is divided into three states, defined as low, intermediate, and high states. The variation of hardness ratio (HR) with 0.3-10.0 keV integrated flux suggests a \enquote{softer-when-brighter} behavior, as also previously reported based on flux-index variations. Simultaneous high state X-ray spectra obtained using Swift, NuSTAR and AstroSat are very steep with a power-law index $>$2. A significant spectral change is observed in AstroSat-SXT and LAXPC spectrum which is consistent with Swift-XRT and NuSTAR spectrum. Together, optical-UV and X-ray spectrum during the high flux state, suggesting the emergence of a new high BL Lacertae (HBL) component. We have modeled the synchrotron peak with publicly available code named GAMERA for low, intermediate, and high flux state. Our modeling suggests the need of high magnetic field to explain the high state under the leptonic scenarios. Increase in the magnetic field value inside the jet could be linked to the increase in accretion rate as expected in the BH-disk impact scenario. The color-magnitude diagram reveals a \enquote{bluer-when-brighter} spectral energy distribution chromatism during the flaring period. Different chromatism or no chromatism at various occasions suggests a complex origin of optical emission, which is believed to be produced by disc impact or through synchrotron emission in the jet.

astro-ph.HE↗

arXiv2021

Multi-wavelength Analysis and Modeling of OJ 287 During 2017-2020

Context. The blazar OJ 287 has been proposed as a binary black hole system based on its periodic optical outburst. Among blazars with parsec scale jets, the black hole binary systems are very rare and hence this source is very interesting to study. Aims. The BL Lac OJ 287 is an interesting object for multi-wavelength study due to its periodic outbursts. We have analyzed the optical, X-ray, and gamma-ray data of OJ 287 for the period of 2017-2020. There are several high states in optical-UV and X-ray frequencies during this period. Based on the observed variability in optical and X-ray frequencies the entire period 2017-2020 is divided into five segments, referred to as A, B, C, D, & E in this paper. A detailed temporal and spectral analysis is performed to understand the nature of its flaring activities. Methods. To understand the temporal variability in this source we have studied the intra-day, and fractional variability for all the various states, and along with that fast variability time was also estimated to understand the nature of variability. Further, the multi-wavelength SED modeling is performed to know more about the physical processes responsible for the simultaneous broadband emission and the fast variability. Results. The Fermi-LAT observations show a moderate flux level of this source in gamma-ray frequency throughout this period, though flux variability has been observed. The source has shown a strong flux variability in X-ray, optical, and UV during early 2017 and mid-2020 when the source was in a very high state. A single zone SSC emission model is considered to model the spectral energy distributions and this helps us to explore the nature of this BL Lac with binary super-massive black holes.

astro-ph.HE↗

arXiv2019

Multi-band optical variability of 3C 279 on diverse timescales

We have monitored the flat spectrum radio quasar, 3C 279, in the optical $B$, $V$, $R$ and $I$ passbands from 2018 February to 2018 July for 24 nights, with a total of 716 frames, to study flux, colour and spectral variability on diverse timescales. 3C\,279 was observed using seven different telescopes: two in India, two in Argentina, two in Bulgaria and one in Turkey to understand the nature of the source in optical regime. The source was found to be active during the whole monitoring period and displayed significant flux variations in $B$, $V$, $R$, and $I$ passbands. Variability amplitudes on intraday basis varied from 5.20\% to 17.9\%. A close inspection of variability patterns during our observation cycle reveals simultaneity among optical emissions from all passbands. During the complete monitoring period, progressive increase in the amplitude of variability with frequency was detected for our target. The amplitudes of variability in $B$, $V$, $R$ and $I$ passbands have been estimated to be 177\%, 172\%, 171\% and 158\%, respectively. Using the structure function technique, we found intraday timescales ranging from $\sim 23$ minutes to about 115 minutes. We also studied colour-magnitude relationship and found indications of mild bluer-when-brighter trend on shorter timescales. Spectral indices ranged from 2.3 to 3.0 with no clear trend on long term basis. We have also generated spectral energy distributions for 3C\,279 in optical $B$, $V$, $R$ and $I$ passbands for 17 nights. Finally, possible emission mechanisms causing variability in blazars are discussed briefly.

astro-ph.HE↗

arXiv2015

Multi-band optical variability of the Blazar S5 0716+714 in outburst state during 2014-2015

We analyzed the multi-band optical behaviour of the BL Lacertae object, S5 0716+714, during its outburst state from 2014 November - 2015 March. We took data on 23 nights at three observatories, one in India and two in Bulgaria, making quasi-simultaneous observations in B, V, R, and I bands. We measured multi-band optical fluxes, colour and spectral variations for this blazar on intraday and short timescales. The source was in a flaring state during the period analyzed and displayed intense variability in all wavelengths. R band magnitude of 11.6 was attained by the target on 18 Jan 2015, which is the brightest value ever recorded for S5 0716+714. The discrete correlation function method yielded good correlation between the bands with no measurable time lags, implying that radiation in these bands originate from the same region and by the same mechanism. We also used the structure function technique to look for characteristic timescales in the light curves. During the times of rapid variability, no evidence for the source to display spectral changes with magnitude was found on either of the timescales. The amplitude of variations tends to increase with increasing frequency with a maximum of $\sim$ 22% seen during flaring states in B band. A mild trend of larger variability amplitude as the source brightens was also found. We found the duty cycle of our source during the analyzed period to be $\sim$ 90%. We also investigated the optical spectral energy distribution of S5 0716+714 using B, V, R, and I data points for 21 nights. We briefly discuss physical mechanisms most likely responsible for its flux and spectral variations.

astro-ph.HE↗

arXiv2015

Multi-band optical-NIR variability of blazars on diverse timescales

To search for optical variability on a wide range of timescales, we have carried out photometric monitoring of two flat spectrum radio quasars, 3C 454.3 and 3C 279, plus one BL Lac, S5 0716+714, all of which have been exhibiting remarkably high activity and pronounced variability at all wavelengths. CCD magnitudes in B, V, R and I pass-bands were determined for $\sim$ 7000 new optical observations from 114 nights made during 2011 - 2014, with an average length of $\sim$ 4 h each, at seven optical telescopes: four in Bulgaria, one in Greece, and two in India. We measured multiband optical flux and colour variations on diverse timescales. Discrete correlation functions were computed among B, V, R, and I observations, to search for any time delays. We found weak correlations in some cases with no significant time lags. The structure function method was used to estimate any characteristic time-scales of variability. We also investigated the spectral energy distribution of the three blazars using B, V, R, I, J and K pass-band data. We found that the sources almost always follows a bluer-when-brighter trend. We discuss possible physical causes of the observed spectral variability.

astro-ph.GA↗

arXiv2015

Multi-band optical variability studies of BL Lacertae

We monitored BL Lacertae for 13 nights in optical B, V, R, and I bands during October and November 2014 including quasi-simultaneous observations in V and R bands using two optical telescopes in India. We have studied multi-band optical flux variations, colour variation and spectral changes in this blazar. Source was found to be active during the whole monitoring period and showed significant intraday variability on 3 nights in V and R filters while displayed hints of variability on 6 other dates in R passband and on 2 nights in V filter. From the colour-magnitude analysis of the source we found that the spectra of the target gets flatter as it becomes brighter on intra-night timescale. Using discrete correlation technique, we found that intraday light curves in both V and R filters are almost consistent and well correlated with each other. We also generated spectral energy distribution (SED) of the target using the B, V, R, and I data sets for all 13 nights which could help us investigate the physical process responsible for the observed variations in BL Lacertae objects. We also discuss possible physical causes of the observed spectral variability.

astro-ph.GA↗