AR-2019-2020

in an expanding Friedmann Robertson Walker (FRW) universe filled with different variants of Chaplygin gases. Assuming that the universe is a closed system bounded by the cosmological hori- zon, we first present the general prescription for the rate of change of total entropy on the boundary. In the subsequent part, we have analyzed the validity of the generalised second law of thermodynamics on the cosmological apparent horizon and the cos- mological event horizon for different Chaplygin gas models of the universe. The analysis is supported with the help of suitable graphs to clarify the status of the GSLT on the cosmological horizons. In the case of the cosmological apparent horizon, we have found that some of these models always obey the GSLT, whereas the validity of GSLT on the cos- mological event horizon of all these models depend on the choice of free parameters in the respective models. This work has been done in collaboration with Samarjit Chakraborty. On the gravitational entropy of accelerating black holes We have examined the validity of a proposed def- inition of gravitational entropy in the context of accelerating black hole solutions of the Einstein field equations, which represent the realistic black hole solutions. We have adopted a phenomenolog- ical approach proposed in Rudjord et al. and ex- panded by Romero et al. in which the Weyl cur- vature hypothesis is tested against the expressions for the gravitational entropy. Considering the C- metric for the accelerating black holes, we have evaluated the gravitational entropy, and the corre- sponding entropy density for four different types of black holes, namely, non-rotating black hole, non- rotating charged black hole, rotating black hole and rotating charged black hole. We end up by discussing the merits of such an analysis and the possible reason of failure in the particular case of rotating charged black hole and comment on the possible resolution of the problem. Mamta Gulati Ram pressure stripping: An analytical approach We take an analytical approach to study ram pres- sure stripping, using simple models for discs and the distribution of halo gas to look at this phe- nomenon in cluster, group and galaxy haloes. We also study variations in galaxy properties and red- shift. In each case, we model the worst-case sce- nario (i.e., the maximum effect resulting from ram pressure). We show that the worst-case scenario is not affected greatly by changes in redshift. We find that gas discs in galaxies with a higher spin parameter are stripped sooner than galaxies with a smaller spin parameter. Galaxies in cluster haloes are stripped of gas more efficiently compared with group and galaxy haloes, because they have a higher infall speed and a higher density of gas in the intra-cluster medium (i.e., as a result of a greater retention of baryons). We comment on the limita- tions of our model, and we look at and illustrate a situation where a significant amount of gas may be retained in the galaxy disc. Finally, we discuss the implications for star formation in galaxies during infall into haloes. This work has been done in col- laboration with Ankit Singh, and Jasjeet S. Bagla. Priya Hasan GAIA: The 3D milky way mapper GAIA (Global Astrometric Interferometer for As- trophysics) is a mission of the European Space Agency (ESA), which will make the largest, most precise three dimensional map of our galaxy by an unparalleled survey of one per cent of the galaxy’s population of 100 billion stars with the precision of micro arcseconds. This article briefly reviews GAIA, the data releases (DR), and the possible im- plications of this mission. We introduce the DR1 and DR2 data releases and the scientific outcomes of DR1 as a forerunner to the DR2 of this one-of-a- kind mission. The DR2 was released on 25 th April 2018 and this study aims to prepare the reader for this great milestone in astronomy. K. P. Harikrishnan Quantifying information loss on chaotic attractors through recurrence networks We propose an entropy measure for the analysis of chaotic attractors through recurrence networks, which are un-weighted and un-directed complex networks constructed from time series of dynam- ical systems using specific criteria. We show that the proposed measure converges to a constant value with increase in the number of data points on the attractor (or the number of nodes on the network)