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This article investigates the presence of a static spherically symmetric solution in the metric f(R) gravity. Consequently, we have examined the presence of horizons for the extreme and hyperextreme Schwarzschild-de Sitter solution. Further, we have investigated the orbital motion of a time-like particle around the Schwarzschild-dS solution by forming the constraints for the existence of circular orbits and have subsequently developed an approximation to the innermost stable circular orbit (ISCO)., Comment: 10 pages, 8 figures

NASA's all-sky survey mission, the Transiting Exoplanet Survey Satellite (TESS), is specifically engineered to detect exoplanets that transit bright stars. Thus far, TESS has successfully identified approximately 400 transiting exoplanets, in addition to roughly 6000 candidate exoplanets pending confirmation. In this study, we present the results of our ongoing project, the Validation of Transiting Exoplanets using Statistical Tools (VaTEST). Our dedicated effort is focused on the confirmation and characterization of new exoplanets through the application of statistical validation tools. Through a combination of ground-based telescope data, high-resolution imaging, and the utilization of the statistical validation tool known as \texttt{TRICERATOPS}, we have successfully discovered eight potential super-Earths. These planets bear the designations: TOI-238b (1.61$^{+0.09} _{-0.10}$ R$_\oplus$), TOI-771b (1.42$^{+0.11} _{-0.09}$ R$_\oplus$), TOI-871b (1.66$^{+0.11} _{-0.11}$ R$_\oplus$), TOI-1467b (1.83$^{+0.16} _{-0.15}$ R$_\oplus$), TOI-1739b (1.69$^{+0.10} _{-0.08}$ R$_\oplus$), TOI-2068b (1.82$^{+0.16} _{-0.15}$ R$_\oplus$), TOI-4559b (1.42$^{+0.13} _{-0.11}$ R$_\oplus$), and TOI-5799b (1.62$^{+0.19} _{-0.13}$ R$_\oplus$). Among all these planets, six of them fall within the region known as 'keystone planets,' which makes them particularly interesting for study. Based on the location of TOI-771b and TOI-4559b below the radius valley we characterized them as likely super-Earths, though radial velocity mass measurements for these planets will provide more details about their characterization. It is noteworthy that planets within the size range investigated herein are absent from our own solar system, making their study crucial for gaining insights into the evolutionary stages between Earth and Neptune., Comment: Accepted: Publications of the Astronomical Society of Australia

In this project, we have implemented our basic understanding of Pulsar Astronomy to calculate the Time Period of Vela Pulsar. Our choice of pulsar rests on the fact that it is the brightest object in the high-energy gamma-ray sky. The simplistic data set consisting of only voltage signals makes our preliminary attempt as closely accurate as possible. The observations had been made at 326.5 MHz through a cylindrically paraboloid telescope at Ooty. A higher frequency creates a much lower delay in the arrival time of pulses and makes our calculations even more accurate. Being an already widely studied celestial body, it gives us the opportunity to compare our findings and make necessary modifications.

NASA's Transiting Exoplanet Survey Satellite (TESS) is an all-sky survey mission designed to find transiting exoplanets orbiting nearby bright stars. It has identified more than 329 transiting exoplanets, and almost 6,000 candidates remain unvalidated. In this manuscript, we discuss the findings from the ongoing VaTEST (Validation of Transiting Exoplanets using Statistical Tools) project, which aims to validate new exoplanets for further characterization. We validated 11 new exoplanets by examining the light curves of 24 candidates using the LATTE and TESS-Plot tools and computing the False Positive Probabilities using the statistical validation tool TRICERATOPS. These include planets suitable for atmospheric characterization using transmission spectroscopy (TOI-2194b), emission spectroscopy (TOI-3082b and TOI-5704b) and for both transmission and emission spectroscopy (TOI-672b, TOI- 1694b, and TOI-2443b); One super-Earth (TOI-2194b) orbiting a bright (V = 8.42 mag), metal-poor ([Fe/H] = -0.3720 $\pm$ 0.1) star; one short-period Neptune-like planet (TOI-5704) in the Hot Neptune Desert. In total, we validated 1 super-Earth, 7 sub-Neptunes, 1 Neptune-like, and 2 sub-Saturn or super-Neptune-like exoplanets. Additionally, we identify five likely planet candidates (TOI-323, TOI- 1180, TOI-2200, TOI-2408 and TOI-3913) which can be further studied to establish their planetary nature., Comment: Accepted for Publication in Astronomical Journal, 28 Pages, 7 Figures

We present here a validation of sub-Saturn exoplanet TOI-181b orbiting a K spectral type star TOI-181 (Mass: 0.822 $\pm$ 0.04 M$_{\odot}$, Radius: 0.745 $\pm$ 0.02 R$_{\odot}$, Temperature: 4994 $\pm$ 50 K) as a part of Validation of Transiting Exoplanets using Statistical Tools (VaTEST) project. TOI-181b is a planet with radius 6.95 $\pm$ 0.08 R$_{\oplus}$, mass 46.16 $\pm$ 2.71 M$_{\oplus}$, orbiting in a slightly eccentric orbit with eccentricity 0.15 $\pm$ 0.06 and semi-major axis of 0.054 $\pm$ 0.004 AU, with an orbital period of 4.5320 $\pm$ 0.000002 days. The transit photometry data was collected using Transiting Exoplanet Survey Satellite (TESS) and spectroscopic data for radial velocity analysis was collected using The European Southern Observatory's (ESO) High Accuracy Radial Velocity Planet Searcher (HARPS) telescope. Based on the radial velocity best-fit model we measured RV semi-amplitude to be 20.56 $\pm$ 2.37 m s$^{-1}$. Additionally, we used \texttt{VESPA} and \texttt{TRICERATOPS} to compute the False Positive Probability (FPP), and the findings were FPP values of $1.68\times10^{-14}$ and $3.81\times10^{-04}$, respectively, which are significantly lower than the 1% threshold. The finding of TOI-181b is significant in the perspective of future work on the formation and migration history of analogous planetary systems since warm sub-Saturns are uncommon in the known sample of exoplanets., Comment: 13 pages, 10 figures, submitted to MNRAS, Structural changes are made, New results

In this article, we have examined the existence of a static spherically symmetric solution in the Scalar Tensor Vector Gravity (STVG) and investigated its horizon distances to develop boundary limitations for our test particle. We have computed the Kretschmann invariant of the metric to study the singularities and verify that it reduces to general relativity's Kretschmann invariant as $\alpha\rightarrow0$. Further, we investigated the orbital motion of a time-like and light-like test particle around the static solution by developing an effective potential and the radius of the innermost stable circular orbit (ISCO)., Comment: 7 pages, 6 figures

In this paper, we construct the rotating Janis-Newman-Winicour (JNW) naked singularity spacetime using Newman-Janis Algorithm (NJA). We analyse NJA with and without complexification methods and find that the energy conditions do satisfied when we skip the complexification step. We study the shadows cast by rotating JNW naked singularity and compare them with the shadows cast by the Kerr black hole. We find that the shadow of the rotating naked singularity can be distinguished from the shadow of the Kerr black hole. While we analyse the precession of timelike bound orbits in rotating JNW spacetime, we find that it can have a negative (or opposite) precession, which is not present in the Kerr black hole case. These novel signatures of the shadow and orbital precession in rotating JNW naked singularity spacetime could be important in the context of the recent observation of the shadow of the M87 galactic center and the stellar dynamics of `S-stars' around Milkyway galactic center., Comment: 14 pages, 13 figures

In a quest towards an intelligent decision-making machine, the ability to make plausible predictions is the central pillar of its intelligence. A predicting algorithm's central idea is to understand the governing physical rules and make plausible and apt predictions based on the same governing laws. Extending the study towards the astrophysical phenomenon puts the model's ability to test since the model has to understand various parameters that govern the dynamics of the event and understand the spatial and temporal evolution by applying the plausible laws. This work presents a deep learning model to predict plausible future events that maintain spatial and temporal coherence. We have trained over two broad classes, the evolution of Sa, Sb, S0, and Sd galaxy mergers and evolution of gravitational lenses with a higher redshift of the foreground galaxy having $15M_{\odot}$. We extended our work towards developing a direct measure of the performance metric for any prediction algorithm. We thereby introduce a novel metric, Correctness Factor (CF), which directly outputs how accurate a prediction is., Comment: 21 pages including appendix, 28 figures, link to code within the article

Many pulsar folding algorithms are currently deployed to generate strong SNRs for the total intensity profiles. But they require large observation times to improve the SNR effectively. New approaches to de-noise the pulsar total intensity data have sprung up over the years, powered by Machine learning and Deep learning algorithms. In the current work, efforts are made to implement the currently proposed supervised machine learning models, such as ensembling techniques like Decision Tree Regressor, Random Forest Regressor, Adaboost Regressor, Gradient Boosting Regressor (GBR), K-Nearest Neighbours(KNN), and Support Vector Regressor (SVR) to find out the best possible algorithm which can work over a variety of pulsars from the EPN database of pulsars. All the data used in this work is extracted from the European Pulsar Network (EPN) database of pulsar profiles. The training dataset is obtained by post-processing the pulsar profile data from the EPN database hand testing is performed on a preselected portion of the original data. The results are obtained by testing the above algorithms for 10 different pulsars, including some historically significant ones, and the predicted profiles are plotted. We find that Gradient boosting regressor works the best in denoising pulsar data, followed closely by KNN regressor. This work also emphasizes that there is a reduction in the number of periods of folding by 35-40\% when a combination of machine learning models with the existing pulsar folding techniques like Fast Folding Algorithm(FFA) is employed, which in turn can further reduce the pulsar observation times for the telescopes hunting for pulsars today., Comment: The type of analysis does not work for new pulsar data anymore

In recent years, improvements in Deep Learning (DL) techniques towards Gravitational Wave (GW) astronomy have led to a significant rise in the development of various classification algorithms that have been successfully employed to extract GWs of binary blackhole merger events from noisy time-series data. However, the success of these models is constrained by the length of time-sample and the class of GW source: binary blackhole and neutron star binaries to some extent. In this work, we intended to advance the boundaries of DL techniques using Convolutional Neural Networks, to go beyond binary classification and predict the physical parameters of the events. We aim to propose an alternative method that can be employed for realtime detection and parameter prediction. The DL model we present has been trained on 12s of data to predict the GW source parameters if detected. During training, the maximum accuracy attained was 90.93%, with a validation accuracy of 89.97%., Comment: 15 pages