Professor Ranjan Gupta
Permanent URI for this communityhttp://localhost:4000/handle/11007/1767
Browse
5 results
Search Results
Item Automated star–galaxy segregation using spectral and integrated band data for TAUVEX/ASTROSAT satellite data pipeline(New Astronomy, 2009-10-13) Bora, Archana; Gupta, Ranjan; Singh, Harinder P; et.alWe employ an Artificial Neural Network (ANN) based technique to develop a pipeline for automated segregation of stars from the galaxies to be observed by Tel-Aviv University Ultra-Violet Experiment (TAUVEX). We use synthetic spectra of stars from UVBLUE library and selected International Ultraviolet Explorer (IUE) low-resolution spectra for galaxies in the ultraviolet (UV) region from 1250 to 3220 Å as the training set and IUE low-resolution spectra for both the stars and the galaxies as the test set. All the data sets have been pre-processed to get band integrated fluxes so as to mimic the observations of the TAUVEX UV imager. We also perform the ANN based segregation scheme using the full length spectral features (which will also be useful for the ASTROSAT mission). Our results suggest that, in the case of the non-availability of full spectral features, the limited band integrated features can be used to segregate the two classes of objects; although the band data classification is less accurate than the full spectral data classification.Item A near-infrared stellar spectral library: III. J-band spectra(Bull. Astr. Soc. India, 2007-09-03) Ranade, Arvind C; Ashok, N.M; Singh, Harinder PThis paper is the third in the series of papers published on near- infrared (NIR) stellar spectral library by Ranade et al. (2004 & 2007). The observations were carried out with 1.2 meter Gurushikhar Infrared Telescope (GIRT), at Mt. Abu, India using a NICMOS3 HgCdTe 256 £ 256 NIR array based spectrometer. In paper I (Ranade et al. 2004), H-band spectra of 135 stars at a resolution of » 16 ºA & paper II (Ranade et al. 2007), K band spectra of 114 stars at a resolution of » 22 ºA were presented. The J-band library being released now consists of 126 stars covering spectral types O5{ M8 and luminosity classes I{V. The spectra have a moderate resolution of » 12:5 ºA in the J band and have been continuum shape corrected to their respective e®ective temperatures. The complete set of library in near-infrared (NIR) will serve as a good database for researchers working in the ¯eld of stellar population synthesis. The complete library in J, H & K is available online at: http://vo.iucaa.ernet.in/»voi/NIR Header.htmlItem A 3D Automated Classification Scheme for the TAUVEX data pipeline(Mon. Not. R. Astron. Soc., 2007-02-02) Bora, Archana; Gupta, Ranjan; Singh, Harinder P; et.alIn order to develop a pipeline for automated classification of stars to be observed by the TAUVEX ultraviolet space Telescope, we employ an artificial neural network (ANN) technique for classifying stars by using synthetic spectra in the UV region from 1250°A to 3220°A as the training set and International Ultraviolet Explorer (IUE) low resolution spectra as the test set. Both the data sets have been pre-processed to mimic the observations of the TAUVEX ultraviolet imager. We have successfully classified 229 stars from the IUE low resolution catalog to within 3-4 spectral sub-class using two different simulated training spectra, the TAUVEX spectra of 286 spectral types and UVBLUE spectra of 277 spectral types. Further, we have also been able to obtain the colour excess (i.e. E(B-V) in magnitude units) or the interstellar reddening for those IUE spectra which have known reddening to an accuracy of better than 0.1 magnitudes. It has been shown that even with the limitation of data from just photometric bands, ANNs have not only classified the stars, but also provided satisfactory estimates for interstellar extinction. The ANN based classification scheme has been successfully tested on the simulated TAUVEX data pipeline. It is expected that the same technique can be employed for data validation in the ultraviolet from the virtual observatories. Finally, the interstellar extinction estimated by applying the ANNs on the TAUVEX data base would provide an extensive extinction map for our galaxy and which could in turn be modeled for the dust distribution in the galaxy.Item Filling Gaps in Indo-US Stellar Spectral Library using Principal Component Analysis(Stellar Populations as Building Blocks of Galaxies Proceedings IAU Symposium, 2006-07-12) Singh, Harinder P; Singh, S. Jotin; Gupta, Ranjan; etThe Indo-US coud´e feed stellar spectral library (CFLIB) published recently by Valdes et al. (2004) contains spectra of 1273 stars in the spectral region 3460 to 9464 ˚A at a resolution of 1 ˚A. About 500 stars in this database have gaps ranging from a few ˚A to several tens of ˚A in this wavelength range. We use a variation of Principal Component Analysis (PCA) technique to fill gaps of up to 5˚A in a subset of spectra from the CFLIB. We hope to exploit the full potential of the scheme and attempt to fill larger gaps in stellar spectra in a subsequent study.Item Cross-checking reliability of some available stellar spectral libraries using artificial neural networks(Stellar Populations as Building Blocks of Galaxies Proceedings IAU Symposium, 2006-06-25) Gupta, Ranjan; Singh, S. Jotin; Singh, Harinder PCross-checking the reliability of various stellar spectral databases is an important and desirable exercise. Since number of stars in various databases have no known spectral types and some of the libraries do not have complete coverage resulting in gaps. We use an automated classification scheme based on Artificial Neural Networks (ANN) to cross-classify stars in the Indo-US stellar spectral library (Valdes et al. 2004), JHC (Jacoby, Hunter & Christian 1984), ELODIE spectra (Moultaka et al. 2004) and STELIB (Le Borgne et al. 2003). We have also examined the effects of over-training and over-fitting on the classification efficiency of a Neural Network. It is hoped that such a automated data analysis and validation technique will be useful in the future.