arXiv subjects

Sukanta Das

Publications and source records attributed to Sukanta Das.

23 records · Page 2Linked to original sources

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↗

arXiv2016

On Number Conservation of Non-uniform Cellular Automata

This paper studies the number conservation property of 1-dimensional non-uniform cellular automata (CAs). In a non-uniform cellular automaton (CA), different cells may follow different rules. The present work considers that the cells follow Wolfram's CAs rules. A characterization tool, named Reachability tree is used to discover the number conservation property of non-uniform CAs. Then a decision algorithm is reported to conclude whether a given non-uniform CA with $n$ cells is number conserving or not. Finally, a synthesis scheme is developed to get an $n$-cell number conserving non-uniform CA.

cs.FL↗

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

Asynchronous Cellular Automata and Pattern Classification

This paper designs an efficient two-class pattern classifier utilizing asynchronous cellular automata (ACAs). The two-state three-neighborhood one-dimensional ACAs that converge to fixed points from arbitrary seeds are used here for pattern classification. To design the classifier, we first identify a set of ACAs that always converge to fixed points from any seeds with following properties - (1) each ACA should have at least two but not huge number of fixed point attractors, and (2) the convergence time of these ACAs are not to be exponential. In order to address the first issue, we propose a graph, coined as fixed point graph of an ACA that facilitates in counting the fixed points. We further perform an experimental study to estimate the convergence time of ACAs, and find that there are some convergent ACAs which demand exponential convergence time. Finally, we find that there are 71 (out of 256) ACAs which can be effective candidates as pattern classifier. We use each of the candidate ACAs on some standard data sets, and observe the effectiveness of each ACAs as pattern classifier. It is observed that the proposed classifier is very competitive and performs reliably better than many standard existing algorithms.

nlin.CG↗

arXiv2013

Analysis and synthesis of nonlinear reversible cellular automata in linear time

Cellular automata (CA) have been found as an attractive modeling tool for various applications, such as, pattern recognition, image processing, data compression, encryption, and specially for VLSI design & test. For such applications, mostly a special class of CA, called as linear/additive CA, have been utilized. Since linear/additive CA refer a limited number of candidate CA, while searching for solution to a problem, the best result may not be expected. The nonlinear CA can be a better alternative to linear/additive CA for achieving desired solutions in different applications. However, the nonlinear CA are yet to be characterized to fit the design for modeling an application. This work targets characterization of the nonlinear CA to utilize the huge search space of nonlinear CA while developing applications in VLSI domain. An analytical framework is developed to explore the properties of CA rules. The characterization is directed to deal with the reversibility, as the reversible CA are primarily targeted for VLSI applications. The reported characterization enables us to design two algorithms of linear time complexities -- one for identification and nother for synthesis of nonlinear reversible CA. Finally, the CA rules are classified into 6 classes for developing further efficient synthesis algorithm.

cs.FL↗