Browsing by Author "Prasad, Jayanti"

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Characterizing Foreground for redshifted 21-cm radiation: 150 MHz GMRT observations
(2013-09-05) Ghosh, Abhik; Prasad, Jayanti; Bharadwaj, Somnath; Ali, Saiyad; Chengalur, Jayaram N.
Cosmological parameter estimation using particle swarm optimization (PSO)
(2011-08-30) Prasad, Jayanti; Souradeep, Tarun
Obtaining the set of cosmological parameters consistent with observational data is an important exercise in current cosmological research. It involves ﬁnding the global maximum of the likelihood function in the multi-dimensional parameter space. Currently sampling based methods, which are in general stochastic in nature, like Markov-Chain Monte Carlo(MCMC), are being commonly used for parameter estimation. The beauty of stochastic methods is that the computational cost grows, at the most, linearly in place of exponentially (as in grid based approaches) with the dimensionality of the search space. MCMC methods sample the full joint probability distribution (posterior) from which one and two dimensional probability distributions, best ﬁt (average) values of parameters and then error bars can be computed. In the present work we demonstrate the application of another stochastic method, named Particle Swarm Optimization (PSO), that is widely used in the ﬁeld of engineering and artiﬁcial intelligence, for cosmological parameter estimation from WMAP seven years data. We ﬁnd that there is a good agreement between the values of the best ﬁt parameters obtained from PSO and publicly available code COSMOMC. However, there is a slight disagreement between error bars mainly due to the fact that errors are computed diﬀerently in PSO. Apart from presenting the results of our exercise, we also discuss the merits of PSO and explain its usefulness in more extensive search in higher dimensional parameter space.
Estimating cosmological parameters using particle swarm optimization (PSO)
(2011-08-11) Prasad, Jayanti
FLAGCAL: A flagging and calibration package for radio interferometric data
(2011-11-28) Prasad, Jayanti; Chengalur, Jayaram
We describe a flagging and calibration pipeline intended for making quick look images from GMRT data. The package identifies and flags cor-rupted visibilities, computes calibration solutions and interpolates these onto the target source. These flagged calibrated visibilities can be directly imaged using any standard imaging package. The pipeline is written in “C” with the most compute intensive algorithms being parallelized using OpenMP.