54 citations · 369 across the 17 of their papers we have counts for
17 papers
Checking the second law at cosmic scales
Narayan Banerjee, Purba Mukherjee, Diego Pavón
Based on recent data about the history of the Hubble factor, it is argued that the second law of thermodynamics holds at the largest scales accessible to observation. This is consi…
Neural network reconstruction of scalar-tensor cosmology
Konstantinos F. Dialektopoulos, Purba Mukherjee, Jackson Levi Said +1
Neural networks have shown great promise in providing a data-first approach to exploring new physics. In this work, we use the full implementation of late time cosmological data to…
Neural network reconstruction of cosmology using the Pantheon compilation
Konstantinos F. Dialektopoulos, Purba Mukherjee, Jackson Levi Said +1
In this work, we reconstruct the Hubble diagram using various data sets, including correlated ones, in Artificial Neural Networks (ANN). Using ReFANN, that was built for data sets…
Role of Future SNIa Data from Rubin LSST in Reinvestigating Cosmological Models
Rahul Shah, Ayan Mitra, Purba Mukherjee +2
We study how future Type-Ia supernovae (SNIa) standard candles detected by the Vera C. Rubin Observatory (LSST) can constrain some cosmological models. We use a realistic three-yea…
Reconstructing the Hubble parameter with future Gravitational Wave missions using Machine Learning
Purba Mukherjee, Rahul Shah, Arko Bhaumik +1
We study the prospects of Gaussian processes (GP), a machine learning (ML) algorithm, as a tool to reconstruct the Hubble parameter with two upcoming gravitational wave miss…
Examining the validity of the minimal varying speed of light model through cosmological observations: relaxing the null curvature constraint
Purba Mukherjee, Gabriel Rodrigues, Carlos Bengaly
We revisit a consistency test for the speed of light variability, using the latest cosmological observations. This exercise can serve as a new diagnostics for the standard cosmolog…
A thorough investigation of the prospects of eLISA in addressing the Hubble tension: Fisher Forecast, MCMC and Machine Learning
Rahul Shah, Arko Bhaumik, Purba Mukherjee +1
We carry out an in-depth analysis of the capability of the upcoming space-based gravitational wave mission eLISA in addressing the Hubble tension, with a primary focus on observati…
Spatial Curvature and Thermodynamics
Narayan Banerjee, Purba Mukherjee, Diego Pavón
Reasonable parametrizations of the current Hubble data set of the expansion rate of our homogeneous and isotropic universe, after suitable smoothing of these data, strongly suggest…
Neural Network Reconstruction of and its application in Teleparallel Gravity
Purba Mukherjee, Jackson Levi Said, Jurgen Mifsud
In this work, we explore the possibility of using artificial neural networks to impose constraints on teleparallel gravity and its extensions. We use the available Hubble pa…
Non-parametric Reconstruction Of Some Cosmological Parameters
Purba Mukherjee
The present thesis is devoted to the non-parametric reconstruction of some cosmological parameters using diverse observational datasets. The Universe is assumed to be spatially hom…
Constraining the curvature density parameter in cosmology
Purba Mukherjee, Narayan Banerjee
The cosmic curvature density parameter has been constrained in the present work independent of any background cosmological model. The reconstruction is performed adopting the non-p…
Non-parametric reconstruction of interaction in the cosmic dark sector
Purba Mukherjee, Narayan Banerjee
The possibility of a non-gravitational interaction between the dark matter and the dark energy has been reconstructed using some recent datasets. The crucial aspect is that the int…
Assessment of the cosmic distance duality relation using Gaussian Process
Purba Mukherjee, Ankan Mukherjee
Two types of distance measurement are important in cosmological observations, the angular diameter distance and the luminosity distance . In the present work, we carried…
Non-parametric reconstruction of the cosmological \textit{jerk} parameter
Purba Mukherjee, Narayan Banerjee
The cosmological jerk parameter is reconstructed in a non-parametric way from observational data independent of a fiducial cosmological model. From this kinematical quantity, t…
Revisiting a non-parametric reconstruction of the deceleration parameter from combined background and the growth rate data
Purba Mukherjee, Narayan Banerjee
The cosmic deceleration parameter has been reconstructed in a non-parametric way using various combinations of recent observational datasets. The Pantheon compilation of the Su…
Exact Solutions and Accelerating Universe in Modified Brans-Dicke Theories
Purba Mukherjee, Soumya Chakrabarti
Exact solutions are studied in the context of modified Brans-Dicke theory. The non-linearity of the modified Brans-Dicke field equations is treated with the Euler-Duarte-Moreira me…
Holographic dark energy: constraints on the interaction from diverse observational data sets
Purba Mukherjee, Ankan Mukherjee, H. K. Jassal +2
The present work deals with holographic dark energy models with Hubble horizon as the infra-red cut-off. The interaction rate between dark energy and dark matter has been reconstru…