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Machine learning algorithms play an impressive role in modern technology and address automation problems in many fields as these techniques can be used to identify features with high sensitivity, which humans or other programming techniques aren’t capable of detecting. In addition, the growth of the availability of the data demands the need of faster, accurate, and more reliable automating methods of extracting information, reforming, and preprocessing, and analyzing them in the world of science. The development of machine learning techniques to automate complex manual programs is a time relevant research in astrophysics as it’s a field where, experts are dealing with large sets of data every day. In this study, an automated classification was built for 6 types of star classes Beta Cephei, Delta Scuti, Gamma Doradus, Red Giants, RR Lyrae and RV Tarui with widely varying properties, features extracted from training dataset of stellar light curves obtained from Kepler mission. The Random Forest classification model was used as the Machine Learning model and both periodic and non-periodic features extracted from light curves were used as the inputs to the model. Our implementation achieved an accuracy of 86.5%, an average precision level of 0.86, an average recall value of 0.87, and average F1-Score of 0.86 for the testing dataset obtained from the Kepler mission.

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We report the analysis of high temporal resolution ground- and space-based photometric observations of SZ Lyncis, a binary star one of whose components is a high amplitude δ Scuti. UBVR photometric observations were obtained from Mt. Abu Infrared Observatory and Fairborn Observatory; archival observations from the WASP project were also included. Furthermore, the continuous, high-quality light curve from the TESS project was extensively used for the analysis. The well resolved light curve from TESS reveals the presence of 23 frequencies with four independent modes, 13 harmonics of the main pulsation frequency of 8.296943 ± 0.000002 d−1, and their combinations. The frequency 8.296 d−1 is identified as the fundamental radial mode by amplitude ratio method and using the estimated pulsation constant. The frequencies 14.535, 32.620, and 4.584 d−1 are newly discovered for SZ Lyn. Out of these three, 14.535 and 32.620 d−1 are identified as non-radial lower order p modes and 4.584 d−1 could be an indication of a g mode in a δ Scuti star. As a result of frequency determination and mode identification, the physical parameters of SZ Lyn were revised by optimizations of stellar pulsation models with the observed frequencies. The theoretical models correspond to 7500 K ≤ Teff ≤ 7800 K and log(g) = 3.81 ± 0.06. The mass of SZ Lyn was estimated to be close to 1.7–2.0 M⊙ using evolutionary sequences. The period–density relation estimates a mean density (ρ) of 0.1054 ± 0.0016 g cm−3.

A CALLISTO system was set up at the Arthur C Clarke Institute and connected to the e-CALLISTO global network which observes the solar radio bursts in 24 hours. CALLISTO is the foremostobservation facility to investigate celestial objects in radio region in Sri Lanka. The system consists of the CALLISTO spectrometer and controlling software,logarithmic periodic antenna and pre-amplifier. CALLISTO spectrometer is able to detect solar radio bursts in the frequency range of 45MHz to870MHz with a channel resolution of 62.5kHz.The log-periodic antenna was designed for7dBi gain and achieved the voltage standing wave ratio, less than 1.5 which is acquired by the overall impedance ofthe antenna, 49.3. The linear polarized antenna is pointing to zenith and the dipoles directed to north-south direction. The system detects solar radio emissions originated by solar flares and corona mass ejections. The radio bursts occurs as emission stripes in the radio spectra and classify from type I to V mainly on drift rate and band width. The system observed a type III solar radio burst on 5 th July 2013 and a type II burst on 25 th October 2013 which was originated by X1.7solar flare. The type II bursts characterize with narrow bandwidth and drift slowly from higher to lower frequencies while the main features of type III bursts are high drift rate and broad bandwidth.