The Astrophysical Journal (Jan 2023)

X-PSI Parameter Recovery for Temperature Map Configurations Inspired by PSR J0030+0451

  • Serena Vinciguerra,
  • Tuomo Salmi,
  • Anna L. Watts,
  • Devarshi Choudhury,
  • Yves Kini,
  • Thomas E. Riley

DOI
https://doi.org/10.3847/1538-4357/acf9a0
Journal volume & issue
Vol. 959, no. 1
p. 55

Abstract

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In the last few years, the NICER collaboration has provided mass and radius inferences, via pulse profile modeling, for two pulsars: PSR J0030+0451 and PSR J0740+6620. Given the importance of these results for constraining the equation of state of dense nuclear matter, it is crucial to validate them and test their robustness. We therefore explore the reliability of these results and their sensitivity to analysis settings and random processes, including noise, focusing on the specific case of PSR J0030+0451. We use X-ray Pulse Simulation and Inference (X-PSI), one of the two main analysis pipelines currently employed by the NICER collaboration for mass and radius inferences. With synthetic data that mimic the PSR J0030+0451 NICER data set, we evaluate the recovery performances of X-PSI under conditions not previously tested, including complex modeling of the thermally emitting neutron star surface. For the test cases explored, our results suggest that X-PSI is capable of recovering the true mass and radius within reasonable credible intervals. This work also reveals the main vulnerabilities of the analysis: a significant dependence on noise and the presence of multimodal structure in the posterior surface. Noise particularly impacts our sensitivity to the analysis settings and widths of the posterior distributions. The multimodal structure in the posterior suggests that biases could be present if the analysis is unable to exhaustively explore the parameter space. Convergence testing, to ensure an adequate coverage of the parameter space and a suitable representation of the posterior distribution, is one possible solution to these challenges.

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