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Computational study demonstrates accurate radius recovery in simulated neutron stars using profile likelihood, highlighting a faster alternative to Bayesian inference.
In recent years, NICER data have been extensively used to determine neutron star masses and radii via pulse profile modeling. Pulse profile modeling is implemented with the X-PSI package, and the best-fit parameters are typically obtained using Bayesian inference. Using simulated data, we demonstrate the first ever application of frequentist inference to determine the neutron star radius, where the nuisance parameters are treated using profile likelihood. We find that the profile likelihood technique can recover the true radius to <1σ. The uncertainty in the estimated radius is also comparable to that obtained from Bayesian analysis while being computationally much faster. Therefore, this work serves as a proof-of-principle application of frequentist inference to estimate neutron star radii using pulse profile modeling and complements the Bayesian inference technique currently used. We have also made our analysis codes for frequentist inference using X-PSI publicly available.
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Ramakrishnan et al. (2026) studied this question.
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