This repository contains some highly ambitious projects as a part of hunting for Celestial Bodies in the interstellar medium using sophisticated algorithms of Machine Learning and Neural Networks
Project Number 1: Pulsar_star_prediction:
Pulsars are a rare type of Neutron star that produce radio emission detectable here on Earth. They are of considerable scientific interest as probes of space-time, the inter-stellar medium, and states of matter. Machine learning tools are now being used to automatically label pulsar candidates to facilitate rapid analysis. Classification systems in particular are being widely adopted,which treat the candidate data sets as binary classification problems.
Project Number 2: Predicting_star_type:
The purpose of making this multiclass classification is to prove that the stars follows a certain graph in the celestial Space ,specifically called Hertzsprung-Russell Diagram or simply HR-Diagram so that we can classify stars of various spectral class namely (O,B,A,F,G,K,M) by plotting its features based on that graph.
Project Number 3: Potential_asteroid_collison:
Near-Earth Objects which are asteroids that have been nudged by the gravitational attraction of nearby planets into orbits that allow them to enter the Earth's neighbourhood. Most of the rocky asteroids are formed in the warmer inner solar system between the orbits of Mars and Jupiter. The scientific interest in Asteroids is due largely to their status as the relatively unchanged remnant debris from the solar system formation process some 4.6 billion years ago. Today's Asteroids are the bits and pieces left over from the initial agglomeration of the inner planets that include Mercury, Venus, Earth, and Mars.
As the primitive, leftover building blocks of the solar system formation process, Asteroids offer clues to the chemical mixture from which the planets formed some 4.6 billion years ago. If we wish to know the composition of the primordial mixture from which the planets formed, then we must determine the chemical constituents of the leftover debris from this formation process of the Asteroids.
Project Number 4: High_energy_gamma_particles:
To predict registration of high energy gamma particles in a ground-based atmospheric Cherenkov gamma telescope uses the imaging technique. Cherenkov gamma telescope to observe high energy gamma rays, taking advantage of the radiation emitted by charged particles produced inside the electromagnetic showers initiated by the gammas, and developing in the atmosphere. This Cherenkov radiation (of visible to UV wavelengths) leaks through the atmosphere and gets recorded in the detector, allowing reconstruction of the shower parameters. The available information consists of pulses left by the incoming Cherenkov photons on the photomultiplier tubes, arranged in a plane, the camera. Depending on the energy of the primary gamma, a total of few hundreds to some 10000 Cherenkov photons get collected, in patterns (called the shower image), allowing to discriminate statistically those caused by primary gammas (signal) from the images of hadronic showers initiated by cosmic rays in the upper atmosphere (background).
Typically, the image of a shower after some pre-processing is an elongated cluster. Its long axis is oriented towards the camera centre if the shower axis is parallel to the telescope's optical axis, i.e. if the telescope axis is directed towards a point source. A principal component analysis is performed in the camera plane, which results in a correlation axis and defines an ellipse. If the depositions were distributed as a bivariate Gaussian, this would be an equidensity ellipse. The characteristic parameters of this ellipse are among the image parameters that can be used for discrimination. The energy depositions are typically asymmetric along the major axis, and this asymmetry can also be used in discrimination. There are, in addition, further discriminating characteristics, like the extent of the cluster in the image plane, or the total sum of depositions. The program was run with parameters allowing to observe events with energies down to below 50 GeV.