From the 1 of 14 linked papers with an AI index.
14 papers
Relativistic Oblique Shocks at Finite Temperature: Detachment Angle, Shock Polars, and the Turning Parameter
Rushikesh Ashok Sonkusale, Anshuman Verma, Ritam Mallick
Oblique shocks are ubiquitous in high-energy astrophysical environments, yet a systematic analytical treatment of how finite upstream temperature influences the maximum deflection…
Constraining the High-Density Equation of State with Present and Future NICER Observations Using Physics-Informed Regularized Machine Learning
Utkarsh Atul Deshmukh, Asim Kumar Saha, Ritam Mallick
The paper introduces a physics‑informed conditional invertible neural network that directly maps NICER neutron‑star mass‑radius measurements to central energy density and pressure,…
Neutron stars with an agnostic Dark sector: Core and Halo configurations from a two-fluid approach
Asit karan, Asim Kumar Saha, Tuhin Malik +2
The study of dark matter admixed neutron stars has the potential to advance our understanding of dark matter particle candidates. However, the large parameter space of dark matter…
Distinct Signatures of the Nature of Phase Transition in Binary Neutron Star Mergers
Sagnik Chatterjee, Shamim Haque, Kamal Krishna Nath +2
Binary neutron-star mergers offer crucial insights into the matter properties of neutron stars. We present the possible imprints in the gravitational wave signal from the nature of…
Dynamical response of twin stars to perturbations
Shamim Haque, Luciano Rezzolla, Ritam Mallick
If a strong first-order phase transition takes place at sufficiently high rest-mass densities in the equation of state (EOS) modelling compact stars, a new branch will appear in th…
A geometric physics-informed machine learning inference for the neutron star maximum mass and the inverse problem
Rounak Mukherjee, Ritam Mallick
The existence of a distinct mass boundary between the heaviest neutron stars and the lightest black holes remains in question. It is an artefact of our ignorance of the properties…