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Independent Research – Rotating Neutron Star Modelling

Caden Phillips | Independent Computational Astrophysics Project

Overview

This independent research investigates rotating neutron stars using two numerical relativity frameworks: RNS and LORENE. Both solvers enable the calculation of rapidly rotating, relativistic stellar equilibria for specified central densities and angular velocities. The aim was to explore correlations between mass, radius, frequency, and central density using self-written code that automates model generation and data visualisation.

Methods

A suite of C++ routines was developed to perform parameter sweeps over rotation frequency and central density, automating the generation of stellar configurations via RNS and LORENE. These scripts executed each solver, extracted key output variables (mass, equatorial and polar radius, central density, moment of inertia), and stored results in structured output files.

A companion Python analysis pipeline was implemented to parse, combine, and visualise the resulting datasets. Using matplotlib and numpy, the data were represented in both 2D and 3D parameter spaces to identify dependencies between quantities and highlight relativistic rotational trends.

Results

2D relationships between RNS parameters
2D relationships between RNS parameters showing dependencies between mass, radius, frequency, and central density.

The six-panel figure summarises 2D parameter relationships extracted from the RNS output. Clear correlations appear between mass, radius, and central density, demonstrating the expected relativistic behaviour of compact stars under rapid rotation.

3D relationships between RNS parameters
3D relationship between RNS parameters – frequency versus radius versus mass, coloured by central density.

The 3D projection highlights how increasing rotation frequency leads to larger equatorial radii and reduced central densities at fixed mass — consistent with centrifugal flattening. The colour mapping visually tracks this gradient, reinforcing the trends identified in the 2D analysis.

Summary

This project demonstrates the workflow for automating relativistic stellar modelling using RNS and LORENE, combining compiled simulation pipelines in C++ with data post-processing in Python. The output visualisations provide an effective framework for exploring how stellar rotation influences equilibrium structure, offering a foundation for future work incorporating equation-of-state variation or gravitational-wave–relevant parameters.