activity
20172026
most citedGW170817: constraining the nuclear matter equation of state from the neutron star tidal deformability

267 citations · 919 across the 56 of their papers we have counts for

collaborators
Showing 2023Show all

7 papers · 1 filter

astro-ph.HE2023★ 1 cited

Analysis of Neutron Star mode Oscillations in General Relativity with Spectral Representation of Nuclear Equations of State

Debanjan Guha Roy, Tuhin Malik, Swastik Bhattacharya +1

We study quasinormal mode oscillations in neutron star(NS) interiors within the linearized General Relativistic formalism. We utilize approximately 9000 nuclear Equations of St…

hep-ph2023★ 1 cited

Exploring robust correlations between fermionic dark matter model parameters and neutron star properties: A two-fluid perspective

Prashant Thakur, Tuhin Malik, Arpan Das +2

The current observational properties of neutron stars have not definitively ruled out the possibility of dark matter. In this study, we primarily focus on exploring correlations be…

gr-qc2023★ 4 cited

Unveiling a universal relationship between the f(R) parameter and neutron star properties

K. Nobleson, Sarmistha Banik, Tuhin Malik

In recent years, modified gravity theories have gained significant attention as potential replacements for the general theory of relativity. Neutron stars, which are dense compact…

nucl-th2023★ 6 cited

Neutron star equation of state: identifying hadronic matter characteristics

Constança Providência, Tuhin Malik, Milena Bastos Albino +1

The general behavior of the nuclear equation of state (EOS), relevant for the description of neutron stars (NS), is studied within a relativistic mean field description of nuclear…

nucl-th2023★ 2 cited

Robust universal relations in neutron star asteroseismology

Deepak Kumar, Tuhin Malik, Hiranmaya Mishra +1

The non-radial oscillations of the neutron stars (NSs) have been suggested as a useful tool to probe the composition of neutron star matter (NSM). With this scope in mind, we consi…

nucl-th2023★ 24 cited

Decoding Neutron Star Observations: Revealing Composition through Bayesian Neural Networks

Valéria Carvalho, Márcio Ferreira, Tuhin Malik +1

We exploit the great potential offered by Bayesian Neural Networks (BNNs) to directly decipher the internal composition of neutron stars (NSs) based on their macroscopic properties…

nucl-th2023

High-Density behavior of symmetry energy and speed of sound in the dense matter within an effective chiral model

Prashant Thakur, N. K. Patra, T. K. Jha +1

With an effective chiral model, we investigate how the mesonic cross couplings and affect the density content of the symmetry energy and its higher-order slope paramete…