Dr. NARESH KUMAR PATRA
Postdoctoral Researcher · The Chinese University of Hong Kong, Shenzhen, China · China
Publications: 28 · Citations: 223 · h-index: 10 · i10-index: 10
Identifiers: orcid.org/0000-0003-0103-5590 · inspirehep.net/authors/1823093 · scholar.google.com/citations?user=DRuyIYwAAAAJ
Publications
- Bayesian reconstruction of nuclear matter parameters from the equation of state of neutron star matter — Phys.Rev.C, 2022 doi:10.1103/physrevc.105.015806
- Nearly model-independent constraints on dense matter equation of state in a Bayesian approach — Phys.Rev.D, 2022 doi:10.1103/physrevd.106.043024
- Systematic analysis of the impacts of symmetry energy parameters on neutron star properties — Phys.Rev.C, 2023 doi:10.1103/physrevc.107.055804
- An Equation of State for Magnetized Neutron Star Matter and Tidal Deformation in Neutron Star Mergers — Astrophys.J., 2020 doi:10.3847/1538-4357/aba8fc
- Inferring the equation of state from neutron star observables via machine learning — Phys.Lett.B, 2025 doi:10.1016/j.physletb.2025.139470
- Establishing connection between neutron star properties and nuclear matter parameters through a comprehensive multivariate analysis — Phys.Rev.D, 2023 doi:10.1103/physrevd.108.123015
- Effect of the σ-cut potential on the properties of neutron stars with or without a hyperonic core — Phys.Rev.C, 2022 doi:10.1103/physrevc.106.055806
- Decoding dark matter admixed neutron stars: From static structure to rotational deformation — Phys.Dark Univ., 2025 doi:10.1016/j.dark.2025.102093
- Calibrating global behavior of equation of state by combining nuclear and astrophysics inputs in a machine learning approach — Phys.Rev.D, 2024 doi:10.1103/physrevd.110.103042
- Calibrating global behaviour of equation of state by combining nuclear and astrophysics inputs in a machine learning approach — Research Square, 2024 doi:10.48550/arxiv.2407.08553
- Bayesian analysis of the neutron star equation of state and model comparison: Insights from PSR J0437+4715, PSR J0614+3329, and other multiphysics data — Phys.Rev.D, 2025 doi:10.1103/2fz9-xlv1
- Bayesian Inference of Neutron Star Properties in f(Q) Gravity Using NICER Observations — The European Physical Journal C, 2026 doi:10.1140/epjc/s10052-026-15962-z
- Reconstruction of Equation of State From Neutron Star Observables via Machine Learning — DAE Symp.Nucl.Phys., 2026
- Decoding the Relationship Between Neutron Star Properties and Nuclear Matter Parameters Using Symbolic Regression — DAE Symp.Nucl.Phys., 2025
- Parameter phase space in accordance with the very precise χEFT N^3LO equation of state — DAE Symp.Nucl.Phys., 2023
- Reconstruction of nuclear matter parameters from neutron star matter equation of state in a Bayesian approach — DAE Symp.Nucl.Phys., 2023
- Model-independent constraints on dense matter EOS in a Bayesian approach — DAE Symp.Nucl.Phys., 2023
- Constraining nuclear symmetry energy with new NICER measurement PSR J0437+4715 and PSR J0614+3329 and Bayesian model comparison — DAE Symp.Nucl.Phys., 2026
- Learning the relations between neutron star and nuclear matter properties with symbolic regression — 2026
- Cross-couplings matters to matter at high densities — DAE Symp.Nucl.Phys., 2019