IUCAA Preprints

Permanent URI for this communityhttp://localhost:4000/handle/11007/149

Browse

Author: search.filters.author.Gupta, RanjanSubject: search.filters.subject.ISM

Search Results

Now showing 1 - 2 of 2
  • No Thumbnail Available
    Item
    Interstellar Extinction by Spheroidal Dust Grains
    (2005-06-01) Gupta, Ranjan
    Observations of interstellar extinction and polarization indicate that the interstellar medium consists of aligned non-spherical dust grains which show variation in the interstellar extinction curve for wavelengths ranging from NIR to UV. To model the extinction and polarization, one cannot use the conventional Mie theory which assumes the grains as solid spheres. We have used a T-matrix based method for computing the extinction efficien- cies of spheroidal silicate and graphite grains of different shapes (axial ratios) and sizes and used these efficiencies to evaluate the interstellar extinction curve in the wavelength range 3.4 − 0.1 m. A best fit linear combination of silicate and graphite grains of not very large axial ratio, fits the observed extinction curve reasonably well. We calculate the volume extinction factor Vc, which is an important parameter from the point of view of the cosmic abundance, for the spheroidal grain models that reproduce the interstellar extinction curve. We find that the shape of the grains do not affect the volume extinction factor. Finally we have also studied the extinction and linear polarization efficiencies for aligned spheroids. The results show that the shape of grains affects the linear polarization efficiencies considerably for various orientation angles of the spheroids.
  • No Thumbnail Available
    Item
    3D Automated Classification Scheme for the TAUVEX data pipeline
    (2007-11-28) Bora, Archana; Gupta, Ranjan; Singh, Harinder P.; et al.
    In order to develop a pipeline for automated classi cation of stars to be observed by the TAUVEX ultraviolet space Telescope, we employ an arti cial 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 classi ed 229 stars from the IUE low resolution catalog to within 3-4 spectral sub-class using two di erent 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 classi ed the stars, but also provided satisfactory estimates for interstellar extinction. The ANN based classi cation 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.