Direct mapping of tidal deformability to the iso-scalar and iso-vector nuclear matter parameters

Abstract

Background: The equations of state (EoSs) which determine the properties of neutron stars (NSs) are often characterized by the iso-scalar and iso-vector nuclear matter parameters (NMPs). Recent attempts to relate the radius and tidal deformability of a NS to the individual NMPs have been inconclusive. These properties display strong correlations with the pressure of NS matter which depends on several NMPs. The knowledge of minimal NMPs that determine the NS properties will be necessary to address any connection between NS properties (e.g., tidal deformability) and that of finite nuclei. Purpose: To identify the important NMPs required to describe the tidal deformability of neutron star for astrophysically relevant range of their gravitational masses (1.2 -- 1.8 M${}_{\odot }$) as encountered in the binary neutron star merger events. Method: We construct a large set of EoSs using four iso-scalar and five iso-vector NMPs. These EOSs are employed to perform a systematic analysis to isolate the NMPs that predominantly determine the tidal deformability, over a wide range of NS mass. The tidal deformability is then directly mapped to these NMPs. Results: The tidal deformability of the NS with mass 1.2-1.8 M${}_{\odot }$ can be determined within 10$\%$ directly in terms of four nuclear matter parameters, namely, the incompressibility $K_0$ and skewness $Q_0$ of symmetric nuclear matter, and the slope $L_0$ and curvature parameter $K_{\mathrm{sym},0}$ of symmetry energy. Conclusion: A function that quickly estimates the value of tidal deformability in terms of minimal nuclear matter parameters is developed. Our method can also be extended to other NS observables.

5 pages, 5 figures

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Cited by in corpus (7)

• The Science of the Einstein Telescope
• Implications of comprehensive nuclear and astrophysics data on the equations of state of neutron star matter
• Inferring the Equation of State from Neutron Star Observables via Machine Learning
• Unraveling the global behavior of equation of state by explicit finite nuclei constraints
• Bayesian Analysis of the Neutron Star Equation of State and Model Comparison: Insights from PSR J0437+4715, PSR J0614+3329, and Other Multi-Physics Data
• Neutron-star seismology with realistic, finite-temperature nuclear matter
• Limitations in constraining neutron star radii and nuclear properties from inspiral gravitational wave detections