arXiv subjects

Kaustubh Vaghmare

Publications and source records attributed to Kaustubh Vaghmare.

12 recordsLinked to original sources

arXiv2021

Deep Co-Added Sky from Catalina Sky Survey Images

A number of synoptic sky surveys are underway or being planned. Typically they are done with small telescopes and relatively short exposure times. A search for transient or variable sources involves comparison with deeper baseline images, ideally obtained through the same telescope and camera. With that in mind we have stacked images from the 0.68~m Schmidt telescope on Mt. Bigelow taken over ten years as part of the Catalina Sky Survey. In order to generate deep reference images for the Catalina Real-time Transient Survey, close to 0.8 million images over 8000 fields and covering over 27000~sq.~deg. have gone into the deep stack that goes up to 3 magnitudes deeper than individual images. CRTS system does not use a filter in imaging, hence there is no standard passband in which the optical magnitude is measured. We estimate depth by comparing these wide-band unfiltered co-added images with images in the $g$-band and find that the image depth ranges from 22.0--24.2 across the sky, with a 200-image stack attaining an equivalent AB magnitude sensitivity of 22.8. We compared various state-of-the-art software packages for co-adding astronomical images and have used SWarp for the stacking. We describe here the details of the process adopted. This methodology may be useful in other panoramic imaging applications, and to other surveys as well. The stacked images are available through a server at Inter-University Centre for Astronomy and Astrophysics (IUCAA).

astro-ph.IM↗

arXiv2021

Gravitational interaction signatures in isolated galaxy triplet systems: a photometric analysis

Galaxy triplets are interesting laboratories where we can study the formation and the evolution of small and large systems of galaxies. This study aims to investigate signs of interaction between the members of nine isolated galaxy triplet systems (27 galaxies) selected from the "SDSS-based catalogue of Isolated Triplets" (SIT) with members brighter than 17.0 ($m_r\le$ 17.0) in the $r-$band, and mean projected separation between the members of $r_p \leq$ 0.1 Mpc. In this work, we performed a one-dimensional (1D) fitting of the surface brightness profiles and a two-dimensional (2D) modeling of the sample galaxies. In the 1D fitting, we examined the far outer part of the light profiles of disk galaxies (22 galaxies) and categorized them into type I (simple exponential), type II (down-bending), and type III (up-bending). This fitting results showed that 55$\%$ of disk galaxies in our sample represent type III i.e are in state of interaction. In the 2D modeling, we fit smooth axisymmetric profiles to the 27 galaxies and found that 70$\%$ exhibit asymmetric features and signs of interactions in their residual images. Thus, we conclude that galaxy triplets, with projected separations ($r_p \leq$ 0.1 Mpc) between their members, are physically bounded systems that show pronounced signs of interactions.

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arXiv2020

Stellar Spectral Interpolation using Machine Learning

Theoretical stellar spectra rely on model stellar atmospheres computed based on our understanding of the physical laws at play in the stellar interiors. These models, coupled with atomic and molecular line databases, are used to generate theoretical stellar spectral libraries (SSLs) comprising of stellar spectra over a regular grid of atmospheric parameters (temperature, surface gravity, abundances) at any desired resolution. Another class of SSLs is referred to as empirical spectral libraries; these contain observed spectra at limited resolution. SSLs play an essential role in deriving the properties of stars and stellar populations. Both theoretical and empirical libraries suffer from limited coverage over the parameter space. This limitation is overcome to some extent by generating spectra for specific sets of atmospheric parameters by interpolating within the grid of available parameter space. In this work, we present a method for spectral interpolation in the optical region using machine learning algorithms that are generic, easily adaptable for any SSL without much change in the model parameters, and computationally inexpensive. We use two machine learning techniques, Random Forest (RF) and Artificial Neural Networks (ANN), and train the models on the MILES library. We apply the trained models to spectra from the CFLIB for testing and show that the performance of the two models is comparable. We show that both the models achieve better accuracy than the existing methods of polynomial based interpolation and the Gaussian radial basis function (RBF) interpolation.

astro-ph.SR↗

arXiv2019

Application of Convolutional Neural Networks for Stellar Spectral Classification

Due to the ever-expanding volume of observed spectroscopic data from surveys such as SDSS and LAMOST, it has become important to apply artificial intelligence (AI) techniques for analysing stellar spectra to solve spectral classification and regression problems like the determination of stellar atmospheric parameters Teff, log g, [Fe/H]. We propose an automated approach for the classification of stellar spectra in the optical region using Convolutional Neural Networks. Traditional machine learning (ML) methods with "shallow" architecture (usually up to 2 hidden layers) have been trained for these purposes in the past. However, deep learning methods with a larger number of hidden layers allow the use of finer details in the spectrum which results in improved accuracy and better generalisation. Studying finer spectral signatures also enables us to determine accurate differential stellar parameters and find rare objects. We examine various machine and deep learning algorithms like Artificial Neural Networks (ANN), Random Forest (RF), and Convolutional Neural Network (CNN) to classify stellar spectra using the Jacoby Atlas, ELODIE and MILES spectral libraries as training samples. We test the performance of the trained networks on the Indo-U.S. Library of Coude Feed Stellar Spectra (CFLIB). We show that using convolutional neural networks, we are able to lower the error up to 1.23 spectral sub-classes as compared to that of 2 sub-classes achieved in the past studies with ML approach. We further apply the trained model to classify stellar spectra retrieved from the SDSS database with SNR>20.

astro-ph.SR↗

arXiv2018

A SALT Spectral Study of S0s Hosting Pseudobulges

We present a SALT-RSS spectroscopic study of a sample of S0 galaxies established by Vaghmare et al. (2015) as having pseudobulges using a combination of photometric criteria. We extract the spectra of various regions along the galaxy major axis using standard long-slit spectroscopic reduction procedures and model the spectra using STARLIGHT to derive detailed star formation histories. The central spectra of galaxies without bars in our sample reveal a complex star formation history, which is consistent with the belief that pseudobulges have a history of star formation distributed over extended periods of time. The spectra of the unbarred galaxies contain strong emission lines such as H $α$, indicating active star formation, which appears to be in contradiction with the expectation that S0 galaxies have been stripped of gas. In the case of the two barred galaxies in the sample, the spectrum is dominated by light from a much older stellar population. This seems to suggest an accelerated formation of the pseudobulge made possible by the action of the bar. One of these galaxies appears to have exhausted its reservoir of gas and thus has no signature of a recently formed population of stars while the other galaxy has managed to give rise to new stars through a recent funnelling action. We have also confirmed the influence of bars on the nature of the stellar population in a pseudobulge using an alternate sample based on the SDSS

astro-ph.GA↗

arXiv2018

Detection of Bars in Galaxies using a Deep Convolutional Neural Network

We present an automated method for the detection of bar structure in optical images of galaxies using a deep convolutional neural network which is easy to use and provides good accuracy. In our study we use a sample of 9346 galaxies in the redshift range 0.009-0.2 from the Sloan Digital Sky Survey, which has 3864 barred galaxies, the rest being unbarred. We reach a top precision of ~94 per cent in identifying bars in galaxies using the trained network. This accuracy matches the accuracy reached by human experts on the same data without additional information about the images. Since Deep Convolutional Neural Networks can be scaled to handle large volumes of data, the method is expected to have great relevance in an era where astronomy data is rapidly increasing in terms of volume, variety, volatility and velocity along with other V's that characterize big data. With the trained model we have constructed a catalogue of barred galaxies from SDSS and made it available online.

astro-ph.IM↗

arXiv2017

Information Retrieval and Recommendation System for Astronomical Observatories

We present a machine learning based information retrieval system for astronomical observatories that tries to address user defined queries related to an instrument. In the modern instrumentation scenario where heterogeneous systems and talents are simultaneously at work, the ability to supply with the right information helps speeding up the detector maintenance operations. Enhancing the detector uptime leads to increased coincidence observation and improves the likelihood for the detection of astrophysical signals. Besides, such efforts will efficiently disseminate technical knowledge to a wider audience and will help the ongoing efforts to build upcoming detectors like the LIGO-India etc even at the design phase to foresee possible challenges. The proposed method analyses existing documented efforts at the site to intelligently group together related information to a query and to present it on-line to the user. The user in response can further go into interesting links and find already developed solutions or probable ways to address the present situation optimally. A web application that incorporates the above idea has been implemented and tested for LIGO Livingston, LIGO Hanford and Virgo observatories.

astro-ph.IM↗

arXiv2016

Which bulges are favoured by barred S0 galaxies?

S0 galaxies are known to host classical bulges with a broad range of size and mass, while some such S0s are barred and some not. The origin of the bars has remained as a long-standing problem -- what made bar formation possible in certain S0s? By analysing a large sample of S0s with classical bulges observed by the Spitzer space telescope, we find that most of our barred S0s host comparatively low-mass classical bulges, typically with bulge-to-total ratio ($B/T$) less than $0.5$; whereas S0s with more massive classical bulges than these do not host any bar. Furthermore, we find that amongst the barred S0s, there is a trend for the longer and massive bars to be associated with comparatively bigger and massive classical bulges -- possibly suggesting bar growth being facilitated by these classical bulges. In addition, we find that the bulge effective radius is always less than the bar effective radius --indicating an interesting synergy between the host classical bulge and bars being maintained while bar growth occurred in these S0s.

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arXiv2015

Spiral Galaxies as Progenitors of Pseudobulge Hosting S0s

We present observations of pseudobulges in S0 and spiral galaxies using imaging data taken with the Spitzer Infra-Red Array Camera. We have used 2-d bulge-disk-bar decomposition to determine structural parameters of 185 S0 galaxies and 31 nearby spiral galaxies. Using the Sersic index and the position on the Kormendy diagram to classify their bulges as either classical or pseudo, we find that 25 S0s (14%) and 24 spirals (77%) host pseudoblges. The fraction of pseudobulges we find in spiral galaxies is consistent with previous results obtained with optical data and show that the evolution of a large fraction of spirals is governed by secular processes rather than by major mergers. We find that the bulge effective radius is correlated with the disk scale length for pseudobulges of S0s and spirals, as expected for secular formation of bulges from disk instabilities, though the disks in S0s are significantly smaller than those in spirals. We show that early-type pseudobulge hosting spirals can transform to pseudobulge hosting S0s by simple gas stripping. However, simple gas stripping mechanism is not sufficient to transform the late-type pseudobulge hosting spirals into pseudobulge hosting S0s.

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arXiv2015

AstroStat - A VO Tool for Statistical Analysis

AstroStat is an easy-to-use tool for performing statistical analysis on data. It has been designed to be compatible with Virtual Observatory (VO) standards thus enabling it to become an integral part of the currently available collection of VO tools. A user can load data in a variety of formats into AstroStat and perform various statistical tests using a menu driven interface. Behind the scenes, all analysis is done using the public domain statistical software - R and the output returned is presented in a neatly formatted form to the user. The analyses performable include exploratory tests, visualizations, distribution fitting, correlation & causation, hypothesis testing, multivariate analysis and clustering. The tool is available in two versions with identical interface and features - as a web service that can be run using any standard browser and as an offline application. AstroStat will provide an easy-to-use interface which can allow for both fetching data and performing power statistical analysis on them.

astro-ph.IM↗

arXiv2013

A Spitzer Study of Pseudobulges in S0 Galaxies : Secular Evolution of Disks

In this Letter, we present a systematic study of lenticular (S0) galaxies based on mid-infrared imaging data on 185 objects taken using the Spitzer Infra Red Array Camera. We identify the S0s hosting pseudobulges based on the position of the bulge on the Kormendy diagram and the Sérsic index of the bulge. We find that pseudobulges preferentially occur in the fainter luminosity class (defined as having total K-band absolute magnitude M_K fainter than -22.66 in the AB system). We present relations between bulge and disk parameters obtained as a function of the bulge type. The disks in the pseudobulge hosting galaxies are found to have distinct trends on the r_e-r_d and μ_d (0) - r_d correlations compared to those in galaxies with classical bulges. We show that the disks of pseudobulge hosts possess on average a smaller scale length and have a fainter central surface brightness than their counterparts occurring in classical bulge hosting galaxies. The differences found for discs in pseudobulge and classical bulge hosting galaxies may be a consequence of the different processes creating the central mass concentrations.

astro-ph.CO↗

arXiv2013

Luminosity dependent star-formation history of S0 galaxies: evidence from GALEX-SDSS-2MASS-WISE colours

We combine UV/Optical/near-IR/mid-IR data on a sample of ~240 S0 galaxies to examine various star formation related processes in them. We split the sample into bright and faint S0 galaxies based on their K band luminosity. Comparing the FUV-NUV versus NUV-K color-color diagram with a Simple Stellar Population (SSP) model shows that ellipticals and bright S0 galaxies are dominated by a stellar population of age > 10^9 years while faint S0 galaxies may contain stars as young as 10^8 years, providing evidence for relatively recent star formation activity. The strength of the 4000A break is also systematically higher in brighter S0 galaxies, again indicating the presence of an old stellar population. Their mid-IR colours indicate that bright S0 colours are like those of ellipticals while faint S0 colours are more like spirals. All these observations are consistent with a scenario in which low-luminosity S0 galaxies likely formed by the stripping of gas from the discs of late-type spiral galaxies, which in turn formed their pseudo bulges through secular evolution processes, possibly involving multiple episodes of star formation. On the other hand, more luminous S0 galaxies likely formed the bulk of their stars at early epochs, similar to the star formation in elliptical galaxies, and are characterised by an old coeval stellar population and classical bulge

astro-ph.CO↗