Bayesian Inference of Neutron Star Properties in $f(Q)$ Gravity Using NICER Observations

Fuente: arXiv
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Autores principales: Pradhan, Sneha, Patra, N. K., Zhou, Kai, Sahoo, P. K.
Formato: Preprint
Publicado: 2026
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author Pradhan, Sneha
Patra, N. K.
Zhou, Kai
Sahoo, P. K.
author_facet Pradhan, Sneha
Patra, N. K.
Zhou, Kai
Sahoo, P. K.
contents In this work, we investigate neutron stars (NSs) in the strong field regime within the framework of symmetric teleparallel $f(Q)$ gravity, considering three representative models: linear, logarithmic, and exponential. While Bayesian studies of NS observations are well established in general relativity and curvature based modified gravity theories, such analyses in $f(Q)$ gravity remain largely unexplored. For the first time we perform a Bayesian inference analysis by confronting theoretical NS mass-radius predictions with NICER observations of PSR J0030+0451, PSR J0740+6620, PSR J0437+4715, and PSR J0614+3329 in the background of nonmetricity based gravity. The dense matter equation of state is fixed to DDME2 in order to isolate the effects of modified gravity on NS structure. Our results show that the exponential $f(Q)$ model is statistically preferred over the linear and logarithmic cases, as confirmed by Bayes factor comparisons, and exhibits well-constrained. For this model, we obtain a radius and tidal deformability at $1.4\,M_\odot$ of $R_{1.4} = 11.27^{+0.53}_{-0.36}\,\mathrm{km}$ and $Λ_{1.4} = 156.95^{+84.02}_{-41.73}$, respectively, consistent with current observational constraints. Remarkably, all three constrained models predict maximum neutron star masses reaching $M_{\max} \simeq 2.98\,M_{\odot}$, with the $95\%$ confidence regions extending into the lower mass gap ($\sim 2.5$--$5\,M_{\odot}$). This mass-gap prediction emerges naturally from the Bayesian-constrained parameter space. These results highlight the potential of NSs as powerful probes of symmetric teleparallel gravity in the strong field regime.
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id arxiv_https___arxiv_org_abs_2601_16227
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Bayesian Inference of Neutron Star Properties in $f(Q)$ Gravity Using NICER Observations
Pradhan, Sneha
Patra, N. K.
Zhou, Kai
Sahoo, P. K.
General Relativity and Quantum Cosmology
In this work, we investigate neutron stars (NSs) in the strong field regime within the framework of symmetric teleparallel $f(Q)$ gravity, considering three representative models: linear, logarithmic, and exponential. While Bayesian studies of NS observations are well established in general relativity and curvature based modified gravity theories, such analyses in $f(Q)$ gravity remain largely unexplored. For the first time we perform a Bayesian inference analysis by confronting theoretical NS mass-radius predictions with NICER observations of PSR J0030+0451, PSR J0740+6620, PSR J0437+4715, and PSR J0614+3329 in the background of nonmetricity based gravity. The dense matter equation of state is fixed to DDME2 in order to isolate the effects of modified gravity on NS structure. Our results show that the exponential $f(Q)$ model is statistically preferred over the linear and logarithmic cases, as confirmed by Bayes factor comparisons, and exhibits well-constrained. For this model, we obtain a radius and tidal deformability at $1.4\,M_\odot$ of $R_{1.4} = 11.27^{+0.53}_{-0.36}\,\mathrm{km}$ and $Λ_{1.4} = 156.95^{+84.02}_{-41.73}$, respectively, consistent with current observational constraints. Remarkably, all three constrained models predict maximum neutron star masses reaching $M_{\max} \simeq 2.98\,M_{\odot}$, with the $95\%$ confidence regions extending into the lower mass gap ($\sim 2.5$--$5\,M_{\odot}$). This mass-gap prediction emerges naturally from the Bayesian-constrained parameter space. These results highlight the potential of NSs as powerful probes of symmetric teleparallel gravity in the strong field regime.
title Bayesian Inference of Neutron Star Properties in $f(Q)$ Gravity Using NICER Observations
topic General Relativity and Quantum Cosmology
url https://arxiv.org/abs/2601.16227