AR-2019-2020

Anisotropic MHRDE model in BD theory of gravi- tation In this work, in the framework of the Brans-Dicke gravitation theory, we propose to study the spa- tially homogeneous, anisotropic and axially sym- metric model filled with dark matter and dark en- ergy. Here, we consider modified holographic Ricci dark energy proposed by Chen and Jing as a fea- sible state of darkness. To achieve a solution, we consider the time-dependent deceleration param- eter, which contributes to the average scale fac- tor of a ( t ) = exp ( 1 β √ 2 βt + α ), where α > 0 and β > 0 are arbitrary constants. We have derived field equations of Brans-Dicke theory of gravitation with the help of an axially symmetric anisotropic Bianchi-type spacetime. We have determined the cosmological parameters, namely, deceleration pa- rameter, matter energy density, anisotropic dark energy density, BD scalar field skewness parame- ter, EoS parameter, and jerk parameter. Here, the various phenomena like the Big Bang, expanding the universe, and shift from anisotropy to isotropy are observed in the model. A comprehensive phys- ical debate of these dynamic parameters is pro- vided through a graphical representation. We ob- serve that it is a quintessence model that exhibits a smooth transition from decelerated stage to an accelerated phase of the universe. This situation is in complete agreement with the modern cosmology scenario. Some physical and geometric behaviours are also discussed and discovered to be in excellent agreement with SNe Ia Supernova’s latest observa- tions. This work has been done in collaboration with Archana Dixit, and Shilpi Singhal Prince P.R. Investigations into solar flare effects using wavelet- based local intermittency measure The present study analyzes the efficiency of local intermittency measure based on wavelet transforms in identifying solar flare effects on magnetograms. If we observe the flare-time features in geomag- netic components, most often, disturbances associ- ated with other solar phenomena will enhance or mask the solar flare signatures. Similarly, diur- nal and high-latitude geomagnetic variabilities will suppress solar flare effects on magnetograms. The measurements of amplitudes taken directly from temporal variations of weak geomagnetic compo- nents have certain limitations regarding the iden- tification of the proper base and peak values from which the deviation due to solar flare has to be measured. In such situations, local intermittency measure based on cross-wavelet analysis can be em- ployed, which could remarkably identify the flare effects, even if the signatures are weak or masked by other disturbance effects. The present study shows that local intermittency measure based on wavelet analysis could act as an alternate quantifi- cation technique for analyzing solar flare effects on geomagnetic activity. This work has been done in collaboration with Sumesh Gopinath. A comparison of machine-learning techniques for the prediction of the auroral electrojet index The modern machine-learning models are a section of artificially intelligent machines used to imple- ment complex models, which can learn and im- prove from experience with respect to certain class of jobs, without being specifically programmed. In the present analysis, a comparative study is made of the popular machine-learning techniques regard- ing the prediction of auroral activity as reflected by the auroral electrojet AE index during geomagnet- ically disturbed periods. The study also explores the suitability of the online sequential version of the best machine-learning algorithm, which has the po- tential for real-time forecast of the AE index from short-time input datasets with extremely fast con- vergence than batch-training methods. The study discusses the need for the correct choice of the in- put dataset, that can be used for predicting the AE index from several combinations of input datasets which include coupling functions, geomagnetic in- dices and solar wind parameters. The study reveals that extreme learning machine and its online se- quential version are promising models, which could predict the AE index extremely fast with a high de- gree of accuracy even during disturbance periods. The study also shows that the choice of the polar cap PC index as an input parameter is extremely important for an accurate prediction of the AE in- dex. This work has been done in collaboration with Sumesh Gopinath. Anisur Rahaman Chiral Schwinger model with Faddeevian anomaly and its BRST quantization We consider chiral Schwinger model with Faddee- vian anomaly, and carry out the quantization of