arXiv subjects

Tanuka Chattopadhyay

Publications and source records attributed to Tanuka Chattopadhyay.

At least 19 recordsLinked to original sources

arXiv2022

Effect of dark matter halos on the orbital and escape dynamics of barred galaxies

This study examines the effect of dark matter halos on the orbital and escape dynamics of stars in the central region of barred galaxies. A three-dimensional gravitational model with a central bulge, bar, disc, and dark matter halo (or simply dark halo) has been set up and analyzed from the viewpoint of escape in open Hamiltonian systems for this purpose. Additionally, this model has been examined separately for the dark halo profiles: oblate and NFW. In both circumstances, an escape mechanism has been identified near the saddle points of the phase space, which correspond to the bar ends. The escaping motion of stars is seen using orbital maps and Poincaré surface section maps generated in various phase planes. Finally, the relationship between chaos and dark halo parameters such as mass, size, circular velocity, and nature has been studied. Our findings suggest that oblate dark halos are preferred over NFW dark halos for justifying the formation of full-fledged spiral arms and extended distribution of dark halos in giant spiral galaxies with supermassive black holes (SMBHs) at their centers. Again, the oblate dark halos well justify the emergence of less prominent or poor spiral arms and the core-dominated distribution of dark halos in dwarf and LSB galaxies in the absence of central SMBHs. On the other hand, extreme central baryonic feedback is required for the NFW halos to generate spiral patterns, and such dark halos should be preferred for galaxies with extremely energetic centers.

astro-ph.GA↗

arXiv2022

Clustering of eclipsing binary light curves through functional principal component analysis

In this paper, we revisit the problem of clustering 1318 new variable stars found in the Milky way. Our recent work distinguishes these stars based on their light curves which are univariate series of brightness from the stars observed at discrete time points. This work proposes a new approach to look at these discrete series as continuous curves over time by transforming them into functional data. Then, functional principal component analysis is performed using these functional light curves. Clustering based on the significant functional principal components reveals two distinct groups of eclipsing binaries with consistency and superiority compared to our previous results. This method is established as a new powerful light curve-based classifier, where implementation of a simple clustering algorithm is effective enough to uncover the true clusters based merely on the first few relevant functional principal components. Simultaneously we discard the noise from the data study involving the higher order functional principal components. Thus the suggested method is very useful for clustering big light curve data sets which is also verified by our simulation study.

stat.AP↗

arXiv2022

Structural properties and classification of variable stars: A study through unsupervised machine learning techniques

The advancement in the field of data science especially in machine learning along with vast databases of variable star projects like the Optical Gravitational Lensing Experiment (OGLE) encourages researchers to analyse as well as classify light curves of different variable stars automatically with efficiency. In the present work, we have demonstrated the relative performances of principal component analysis (PCA) and independent component analysis (ICA) applying to huge databases of OGLE variable star light curves after obtaining 1000 magnitudes between phase 0 to 1 with step length 0.001 for each light curves in identifying resonances for fundamental mode (FU) and first overtone (FO) Cepheids and in the classification of variable stars for Large Magellanic Cloud (LMC), Small Magellanic Cloud (SMC) as well as Milky Way (MW). We have seen that the performance of ICA is better for finding resonances for Cepheid variables as well as for accurately classifying large data sets of light curves than PCA. Using K-means clustering algorithm (CA) with respect to independent components (ICs), we have plotted period-luminosity diagrams and colour-magnitude diagrams separately for LMC, SMC and MW and found that ICA along with K-means CA is a very robust tool for classification as well as future prediction on the nature of light curves of variable stars.

astro-ph.SR↗

arXiv2021

Investigation of the Effect of Bars on the Properties of Spiral Galaxies: A Multivariate Statistical Study

Subjective classification of spiral galaxies is not sufficient for studying the effect of bars on their physical characteristics. In reality the problem is to comprehend the complex correlations in a multivariate parametric space. Multivariate tools are the best ones for understanding this complex correlation. In this work an objective classification of a large set (26,089) of spiral galaxies was compiled as a value added galaxy catalogue from sdss DR 15 virtual data archive. Initially for dimensionality reduction, Independent Component Analysis is performed to determine a set of Independent Components that are linear combinations of 48 observed features (namely ionised lines, Lick indices, photometric and morphological properties). Subsequently a K-means cluster analysis is carried out on the basis of the 14 best chosen Independent Components to obtain 12 distinct homogeneous groups of spiral galaxies. Amongst these, 3 groups are the oldest ones (1.6 Gyr - 5.9 Gyr), while 5 groups fall in the medium aged category (1.4 Gyr - 1.6 Gyr), 2 groups consist of only unbarred spirals, 1 group is the youngest one and the remaining one is an outlier. In many groups there are clear indication of recurrent bar formation phenomena which is consistent with few previous simulation works. In order to study the robustness a second method of clustering by Gaussian Mixture Modeling Method (GMMBC) is applied.

astro-ph.GA↗

arXiv2021

Role of galactic bars in the formation of spiral arms: A study through orbital and escape dynamics -- I

In the present work we have developed a three-dimensional gravitational model of barred galaxies, in order to study orbital and escape dynamics of the stars inside their central barred region. Our gravitational model is composed of four components, central nucleus, bar, disc and dark matter halo. Furthermore we have analysed the model for two different types of bar potentials. The study has been carried out for a Hamiltonian system and thorough numerical studies have been done in order to categorize regular and chaotic motions of stars. We have seen that escape mechanism has only seen near saddle points ($L_2$, $L_4$ and $L_2^{'}$, $L_4^{'}$) of the Hamiltonian system. Orbital structures in $x$ - $y$ plane indicate that this escaping motion corresponds to the two ends of the bar. Classifications of orbits are found by calculating maximal Lyapunov exponent of the stellar trajectories corresponding to a specific initial condition vector. Poincaré surface section maps are studied in both $x$ - $y$ and $x$ - $p_x$ ($p_x$ is the momentum along $x$ - direction) plane to get a complete view of the escape properties of the system in the phase space. Also we studied in detail how the chaotic dynamics varies with mass, length and nature of the bar. We found that under suitable physical conditions the chaos plays a pivotal role behind the formation of grand design or poor spiral pattern for stronger bars and ring structures for weaker bars.

astro-ph.GA↗

arXiv2020

Exploration about the origin of galactic and extragalactic star clusters through simulated H-R diagrams

The present work explores the origin of the formation of star clusters in our Galaxy and in Small Magellanic Cloud (SMC) through simulated H-R diagrams and compare those with observed star clusters. The simulation study produces synthetic H-R diagrams by Markov Chain Monte Carlo (MCMC) technique using star formation history (SFH), luminosity function (LF), abundance of heavy metal (Z) and a big library of isochrones as basic inputs and compares them with observed H-R diagrams of various star clusters. The distance based comparison between those two diagrams is carried out through two dimensional matching of points in Color-Magnitude Diagram (CMD) after optimal choice of bin size and appropriate distance function. It is found that a poor medium of heavy elements (Z = 0.0004), Gaia LF along with mixture of multiple Gaussian distributions of SFH may be the origin of formation of globular clusters (GCs). On the contrary, enriched medium (Z = 0.019) is favoured with Gaia LF along with double power law (i.e. unimodal) SFH. For SMC clusters, the choice of exponential LF and exponential SFH is a proper combination for poor medium whereas Gaia LF with Beta type SFH is preferred in an enriched medium for the formation of star clusters.

astro-ph.GA↗

arXiv2020

Unsupervised classification of eclipsing binary light curves through k-medoids clustering

This paper proposes k-medoids clustering method to reveal the distinct groups of 1,318 variable stars in the Galaxy based on their light curves, where each light curve represents the graph of brightness of the star against time. To overcome the deficiencies of subjective traditional classification, we separate the stars more scientifically according to their geometrical configuration and show that our approach outperforms the existing classification schemes in astronomy. It results in two optimum groups of eclipsing binaries corresponding to bright, massive systems and fainter, less massive systems.

astro-ph.SR↗

arXiv2020

Random fragmentation of turbulent molecular clouds lying in the central region of giant galaxies

A stochastic model of fragmentation of molecular clouds has been developed for studying the resulting Initial Mass Function (IMF) where the number of fragments, inter-occurrence time of fragmentation, masses and velocities of the fragments are random variables. Here two turbulent patterns of the velocities of the fragments have been considered, namely, Gaussian and Gamma distributions. It is found that for Gaussian distribution of the turbulent velocity, the IMFs are shallower in general compared to Salpeter mass function. On the contrary, a skewed distribution for turbulent velocity leads to an IMF which is much closer to Salpeter mass function. The above result might be due to the fact that strong driving mechanisms e.g. shocks, arising out of a big explosion occurring at the centre of the galaxy or due to big number of supernova explosions occurring simultaneously in massive parent clouds during the evolution of star clusters embedded into them are responsible for stripping out most of the gas from the clouds. This inhibits formation of massive stars in large numbers making the mass function a steeper one.

astro-ph.GA↗

arXiv2018

Unsupervised Classification of Galaxies. I. ICA feature selection

Subjective classification of galaxies can mislead us in the quest of the origin regarding formation and evolution of galaxies since this is necessarily limited to a few features. The human mind is not able to apprehend the complex correlations in a manyfold parameter space, and multivariate analyses are the best tools to understand the differences among various kinds of objects. In this series of papers, an objective classification of 362,923 galaxies from the Value Added Galaxy Catalogue (VAGC) is carried out with the help of two methods of multivariate analysis. First, Independent Component Analysis (ICA) is used to determine a set of derived independent components that are linear combinations of 47 observed features (viz. ionized lines, Lick indices, photometric and morphological properties, star formation rates etc.) of the galaxies. Subsequently, a K-means cluster analysis is applied on the nine independent components to obtain ten distinct and homogeneous groups. In this first paper, we describe the methods and the main results. It appears that the nine Independent Components represent a complete physical description of galaxies (velocity dispersion, ionisation, metallicity, surface brightness and structure). We find that our ten groups can be essentially placed into traditional and empirical classes (from colour-magnitude and emission-line diagnostic diagrams, early- vs late-types) despite the classical corresponding features (colour, line ratios and morphology) being not significantly correlated with the nine Independent Components. More detailed physical interpretation of the groups will be performed in subsequent papers.

astro-ph.CO↗

arXiv2017

Two phase formation of massive elliptical galaxies : study through cross-correlation including spatial effect

Formation mechanism of present day population of elliptical galaxies have been revisited in the context of hierarchical cosmological models accompanied by accretion and minor mergers through cross correlation function including spatial effect. The present work investigates the formation and evolution of several components of nearby massive early type galaxies (ETGs) through cross-correlation in the spatial coordinates, right ascension and declination (RA, DEC) and mass-size parameter space with high redshift $(0.5\leq z\leq2.7)$ ETGs. It is found that innermost components of nearby ETGs are highly correlated with ETGs in the redshift range $(2\leq z\leq2.7)$ known as 'red nuggets'. The intermediate and outermost parts have moderate correlations with ETGs in the redshift range $(0.5\leq z\leq0.75)$. The quantitative measures are highly consistent with the two phase formation scenario of massive nearby early type galaxies as suggested by various authors and resolves the conflict raised in a previous work suggesting other possibilities for the formation of outermost part of nearby massive ETGs. The improvement is expected to be due to inclusion of spatial effects in addition to other linear parameters.

astro-ph.GA↗

arXiv2017

Clustering of Gamma-Ray bursts through kernel principal component analysis

We consider the problem related to clustering of gamma-ray bursts (from "BATSE" catalogue) through kernel principal component analysis in which our proposed kernel outperforms results of other competent kernels in terms of clustering accuracy and we obtain three physically interpretable groups of gamma-ray bursts. The effectivity of the suggested kernel in combination with kernel principal component analysis in revealing natural clusters in noisy and nonlinear data while reducing the dimension of the data is also explored in two simulated data sets.

stat.AP↗

arXiv2016

Episodic Model For Star Formation History and Chemical Abundances in Giant and Dwarf Galaxies

In search for a synthetic understanding, a scenario for the evolution of the star formation rate and the chemical abundances in galaxies is proposed, combining gas infall from galactic halos, outflow of gas by supernova explosions, and an oscillatory star formation process. The oscillatory star formation model is a consequence of the modelling of the fractional masses changes of the hot, warm and cold components of the interstellar medium. The observed periods of oscillation vary in the range $(0.1-3.0)\times10^{7}$\,yr depending on various parameters existing from giant to dwarf galaxies. The evolution of metallicity varies in giant and dwarf galaxies and depends on the outflow process. Observed abundances in dwarf galaxies can be reproduced under fast outflow together with slow evaporation of cold gases into hot gas whereas slow outflow and fast evaporation is preferred for giant galaxies. The variation of metallicities in dwarf galaxies supports the fact that low rate of SNII production in dwarf galaxies is responsible for variation in metallicity in dwarf galaxies of similar masses as suggested by various authors.

astro-ph.GA↗

arXiv2015

Multivariate analysis of the globular clusters in M87

An objective classification of 147 globular clusters in the inner region of the giant elliptical galaxy M87 is carried out with the help of two methods of multivariate analysis. First independent component analysis is used to determine a set of independent variables that are linear combinations of various observed parameters (mostly Lick indices) of the globular clusters. Next K-means cluster analysis is applied on the independent components, to find the optimum number of homogeneous groups having an underlying structure. The properties of the four groups of globular clusters thus uncovered are used to explain the formation mechanism of the host galaxy. It is suggested that M87 formed in two successive phases. First a monolithic collapse, which gave rise to an inner group of metal-rich clusters with little systematic rotation and an outer group of metal-poor clusters in eccentric orbits. In a second phase, the galaxy accreted low-mass satellites in a dissipationless fashion, from the gas of which the two other groups of globular clusters formed. Evidence is given {\bf for a blue stellar population in the more metal rich clusters, which we interpret by Helium enrichment.} Finally, it is found that the clusters of M87 differ in some of their chemical properties (NaD, TiO1, light element abundances) from globular clusters in our Galaxy and M31.

astro-ph.GA↗

arXiv2015

Cosmic history of integrated galactic stellar initial mass function : a simulation study

Theoretical and indirect observational evidences suggest that stellar initial mass function (IMF) increases with redshift. On the other hand star formation rates (SFR) may be as high as 100 $M_{\odot}$ yr$^{-1}$ in star burst galaxies. These may lead to formation of massive clusters hence massive stars to make the integrated galactic stellar initial mass function (IGIMF) top heavy (i.e. proportion of massive stars is higher than less massive stars). We investigate the joint effect of evolving IMF and several measures of SFR in dependence of galaxy wide IMF. The resulting IGIMF have slopes $α_{2,IGIMF}$ in the high mass regime, which is highly dependent on the minimum mass of the embedded cluster ($M_{ecl,min}$), star formation rates and mass spectrum indices of embedded clusters (viz. $β$). It is found that for z $\sim$ 0 - 2, $α_{2,IGIMF}$ becomes steeper (i.e. bottom heavy), for z $\sim$ 2 - 4, $α_{2,IGIMF}$ becomes flatter (i.e. top heavy ) and from z $\sim$ 4 onwards $α_{2,IGIMF}$ becomes again steeper. The effects are faster for higher values of $β$. $α_{2,IGIMF}$ is flatter also for higher values of $M_{ecl,min}$. All these effects might be counted for the joint effect of increasing temperature of the ambient medium as well as varying SFR with increasing redshift.

astro-ph.GA↗

arXiv2014

Charged star in (2+1)-dimensional gravity

We obtain a new class of exact solutions for the Einstein-Maxwell system in static spherically symmetric charged star in (2+1)-dimensional gravity. In order to obtain the analytical solutions we treat the matter distribution anisotropic in nature admitting linear or nonlinear equation of state and the electric field intensity was specified. By choosing a suitable choice of mass function m(r), it is possible to integrate the system in closed form. All the solution, which are obtained in both linear and nonlinear cases are regular at the center and well behaved in the stellar interior.

gr-qc↗

arXiv2014

Formation of dwarf ellipticals and dwarf irregular galaxies by interaction of giant galaxies under environmental influence

A model is proposed for the formation of gas-rich dwarf irregular galaxies and gas-poor, rotating dwarf elliptical galaxies following the interaction between two giant galaxies as a function of space density. The formation of dwarf galaxies is considered to depend on a random variable, the tidal index theta, an environmental parameter defined by Karachentsev et al. (2004), such that for theta less than zero, the formation of dwarf irregular galaxy is assured whereas for theta greater than zero, the formation of dwarf ellipticals is preferred. It is found that for particular ranges of the interactive parameters the model predictions are in good agreement with the observed number density of the different galaxy types as a function of space density in four clusters of galaxies. This supports the fact that galaxy interactions do not all necessarily give rise to the formation of either dwarf irregulars or dwarf ellipticals. It is also shown that the formation of dwarf irregulars at high densities is much lower than that of dwarf ellipticals, and that the formation of the latter reaches a maximum at a particular space density, unlike the former. This suggests that at high densities many dwarf irregulars are stripped of their gaseous envelopes to become dwarf elliptical.

astro-ph.GA↗

arXiv2014

Use of spatial cross correlation function to study formation mechanism of massive elliptical galaxies

Spatial clustering nature of galaxies have been studied previously through auto correlation function. The same type of cross correlation function has been used to investigate parametric clustering nature of galaxies e.g. with respect to masses and sizes of galaxies. Here formation and evolution of several components of nearby massive early type galaxies have been envisaged through cross correlations, in the mass-size parametric plane, with high redshift early type galaxies (hereafter ETG).It is found that the inner most components of nearby ETGs have significant correlation with ETGs in the highest redshift range called red nuggets whereas intermediate components are highly correlated with ETGs in the redshift range with z value greater than 0.5 and less than 0.75. The outer most part has no correlation in any range, suggesting a scenario through in situ accretion. The above formation scenario is consistent with the previous results obtained for NGC5128 (Chattopadhyay et al. (2009), Chattopadhyay et al. (2013)) and to some extent for nearby elliptical galaxies (Huang et al. (2013)) after considering a sample of ETGs at high redshift with stellar masses greater than or equal to 108.73 M-Sun. So the present work indicates a three phase formation of massive nearby elliptical galaxies instead of two as discussed in previous works.

stat.AP↗

arXiv2012

A six-parameter space to describe galaxy diversification

Galaxy diversification proceeds by transforming events like accretion, interaction or mergers. These explain the formation and evolution of galaxies that can now be described with many observables. Multivariate analyses are the obvious tools to tackle the datasets and understand the differences between different kinds of objects. However, depending on the method used, redundancies, incompatibilities or subjective choices of the parameters can void the usefulness of such analyses. The behaviour of the available parameters should be analysed before an objective reduction of dimensionality and subsequent clustering analyses can be undertaken, especially in an evolutionary context. We study a sample of 424 early-type galaxies described by 25 parameters, ten of which are Lick indices, to identify the most structuring parameters and determine an evolutionary classification of these objects. Four independent statistical methods are used to investigate the discriminant properties of the observables and the partitioning of the 424 galaxies: Principal Component Analysis, K-means cluster analysis, Minimum Contradiction Analysis and Cladistics. (abridged)

astro-ph.CO↗