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N. K. Patra

Publications and source records attributed to N. K. Patra.

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Sensitivity of Neutron Star Observables to Transition Density in Hybrid Equation-of-State Models

We investigate how the transition density \(ρ_{tr}\) affects hybrid constructions of the neutron-star equation of state (EoS) in which a nucleonic description at low densities is matched to a model-agnostic high-density extension based on a speed-of-sound parametrization. Using four representative nucleonic models--Taylor expansion, \(\frac{n}{3}\) expansion, Skyrme, and relativistic mean-field--built from identical nuclear matter parameters, we isolate the impact of the low-density EoS and the transition density on neutron star observables. We find that, within the present smooth-matching prescription, neutron star properties such as radii and tidal deformabilities retain significant sensitivity to the choice of low-density EoS for commonly adopted transition densities around \(ρ_{tr} \approx 2ρ_0\), even when the same high-density parametrization is employed. This residual dependence arises from differences in the matching conditions at \(ρ_{tr}\), which propagate into the high-density extension, so different low-density inputs lead to different effective high-density EoSs. These findings are robust across two distinct speed-of-sound parametrizations. Quantitatively, the model spread in radius and tidal deformability at $1.4\,M_\odot$ exceeds the current observational uncertainty by factors of $\sim 1.8$ and $\sim 1.4$ at $ρ_{\mathrm{tr}} \approx 2ρ_0$, whereas these factors reduce to $\sim 1.05$ and $\sim 0.4$ at $ρ_{\mathrm{tr}} = ρ_0$. Lowering the transition density, therefore, systematically diminishes the spread among models and leads to more consistent predictions. Our results demonstrate that the widely used choice \(ρ_{tr} \approx 2ρ_0\) does not guarantee model independence in hybrid EoS constructions, and should be treated as an explicit source of systematic uncertainty when inferring dense matter properties from neutron star observations.

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

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.

gr-qc

Learning the relations between neutron star and nuclear matter properties with symbolic regression

The equation of state (EOS) of dense matter in neutron stars (NSs) remains uncertain, particularly at supra-nuclear densities where complex nuclear interactions and the potential presence of exotic matter, like hyperons, come into play. The complex relationships existing between nuclear matter and neutron star properties are investigated. The focus is on their nonlinearities and interdependencies. In our analysis, we apply a machine learning algorithm known as symbolic regression, paired with principal component analysis, to datasets generated from Bayesian inference over relativistic mean-field models. A systematic Principal Component Analysis has allowed to break down the percentage contribution of each element or feature in the relationships obtained. This study examines two main models (datasets): the NL model, which includes nucleonic degrees of freedom; and the NL-hyp model, which includes hyperons in addition to nucleons. Our analysis confirms a robust correlation between the tidal deformability of a 1.4 \(M_\odot\) neutron star and $β$-equilibrium pressure at twice the nuclear saturation density. This correlation remains once hyperons are included. The contribution of the different nuclear matter properties at saturation to the radius and tidal deformability was calculated. It was shown that the isovector properties have the largest impact, with a contribution of about 90\%. We also studied the relationship between the proton fraction at different densities and various symmetry energy parameters defined at saturation density. For the hyperon data set, we took into account the effects of the negatively charged hyperon $Ξ$ in order to recover the relationships. Our study reveals the individual impact of various symmetry energy parameters on proton fractions at different densities.

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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

We perform a comprehensive Bayesian analysis to constrain the neutron star (NS) equation of state (EoS) using a wide range of terrestrial and astrophysical data. The terrestrial inputs include quantities related to symmetric nuclear matter (SNM) and symmetry energy up to two times saturation density ($ρ_0\sim$0.16 fm$^{-3}$), derived from finite nuclei and heavy-ion collisions (HICs). The astrophysical constraints incorporate NS radii and tidal deformabilities from recent NICER observations and GW170817, respectively. We consider five different EoS models: Taylor, $n/3$, Skyrme, RMF, and sound speed(CS), are analyzed by sequentially updating the priors with (i) $χ$EFT based pure neutron matter, (ii) terrestrial, empirical and earlier astrophysical data, (iii) case (ii) including NICER radii of PSR J0437+4715 and J0614+3329, (iv) all data combined, and (v) excluding empirical nuclear inputs. We also perform Bayesian model comparison which favors the Skyrme model under all combined data (scenario (iv)), yielding tight constraints on symmetry energy parameters: $L_0 = 56 \pm 3$~MeV, $K_{\mathrm{sym}0} = -132 \pm 15$~MeV and also on SNM parameters: $K_0 = 265 \pm 12$~MeV, $Q_0 = -366 \pm 43$~MeV. The mass-radius and mass-tidal deformability posterior distributions are also well constrained. The radius and tidal deformability of a $1.4\,M_\odot$ neutron star are found to be $R_{1.4} = 11.85 \pm 0.11$~km and $Λ_{1.4} = 354 \pm 25$, respectively.

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Decoding Dark Matter Admixed Neutron Stars: From Static Structure to Rotational Deformation

In this study, we investigate the impacts of dark matter (DM) on the properties of both static and rotating neutron stars utilizing a self-interacting DM model, motivated by the neutron decay anomaly. DM-admixed NSs are modeled by assuming chemical equilibrium between ordinary matter and the dark sector, treating a single-fluid Tolman-Oppenheimer-Volkoff (TOV) framework. By treating the DM interaction strength ($G$) as a free parameter, we explore its influence on NS properties, considering a broad range of equations of state (EoSs). Using the mass-radius constraints from NICER pulsar measurements, we constrain the DM interaction strength for each EoS via a likelihood analysis. Extending this model to rotating NSs, we analyze how centrifugal forces associated with increasing angular velocity ($Ω$) enhance both mass and radius, causing deformation. We assess the impact of DM on rotational deformation by calculating the eccentricity, highlighting the interplay between DM and rotational forces. Since both DM and rotation simultaneously influence NS properties, we compute the relative changes in mass and radius across varying $G$ and $Ω$ values to quantify their combined effects.

astro-ph.HE

Inferring the Equation of State from Neutron Star Observables via Machine Learning

We have conducted an extensive study using a diverse set of equations of state (EoSs) to uncover strong relationships between neutron star (NS) observables and the underlying EoS parameters using symbolic regression method. These EoS models, derived from a mix of agnostic and physics-based approaches, considered neutron stars composed of nucleons, hyperons, and other exotic degrees of freedom in beta equilibrium. The maximum mass of a NS is found to be strongly correlated with the pressure and baryon density at an energy density of approximately 800 MeV.fm$^{-3}$. We have also demonstrated that the EoS can be expressed as a function of radius and tidal deformability within the NS mass range 1-2$M_\odot$. These insights offer a promising and efficient framework to decode the dense matter EoS directly from the accurate knowledge of NS observables.

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Calibrating global behaviour of equation of state by combining nuclear and astrophysics inputs in a machine learning approach

We implemented symbolic regression techniques to identify suitable analytical functions that map various properties of neutron stars (NSs), obtained by solving the Tolman-Oppenheimer-Volkoff (TOV) equations, to a few key parameters of the equation of state (EoS). These symbolic regression models (SRMs) are then employed to perform Bayesian inference with a comprehensive dataset from nuclear physics experiments and astrophysical observations. The posterior distributions of EoS parameters obtained from Bayesian inference using SRMs closely match those obtained directly from the solutions of TOV equations. Our SRM-based approach is approximately 100 times faster, enabling efficient Bayesian analyses across different combinations of data to explore their sensitivity to various EoS parameters within a reasonably short time.

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Bayesian and Principal Component Analyses of Neutron Star Properties

A Bayesian method is used in this extensive work to generate a large set of minimally constrained equations of state (EOSs) for matters in neutron stars (NS). These EOSs are analyzed for their correlations with key NS properties, such as the tidal deformability, radius, and maximum mass, within the mass range of $1.2-2M_\odot$. The observed connections between the pressure of $β$-equilibrated matter and the properties of neutron stars at different densities offer significant insights into the behavior of NS matter in a nearly model-independent manner. The study also examines the influence of various factors on the correlation of symmetry energy parameters, such as slope and curvature parameters at saturation density ($ρ_0=0.16 ~\text{fm}^{-3}$) with the tidal deformability and radius of neutron stars. This study investigates the robustness of the observed correlations by considering the distributions and interdependence of symmetry energy parameters. Furthermore, the utilization of Principal Component Analysis (PCA) is employed to unveil the complicated relationship between various nuclear matter parameters and properties of neutron stars. This analysis highlights the importance of employing multivariate analysis techniques in order to comprehend the variety in tidal deformability and radius observed across distinct masses of NS. This comprehensive study aims to establish a connection between the parameters of nuclear matter and the properties of neutron stars, providing significant insights into the behavior of NS matter across different circumstances.

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Establishing connection between neutron star properties and nuclear matter parameters through a comprehensive multivariate analysis

We have attempted to mitigate the challenge of connecting the neutron star (NS) properties with the nuclear matter parameters that describe equations of state (EoSs). The efforts to correlate various neutron star properties with individual nuclear matter parameters have been inconclusive. A Principal Component Analysis is employed as a tool to uncover the connection between multiple nuclear matter parameters and the tidal deformability as well as the radius of neutron stars within the mass range of $1.2-1.8M_\odot$. The essential EOSs for neutron star matter at low densities have been derived using both uncorrelated uniform distributions and minimally constrained joint posterior distributions of nuclear matter parameters. For higher densities ($ρ> 0.32$fm$^{-3}$), the EOSs have been established through a suitable parameterization of the speed of sound, which consistently maintains causality and gradually approaches the conformal limit. Our analysis reveals that in order to account for over 90\% of the variability in NS properties, it is crucial to consider two or more principal components, emphasizing the significance of employing multivariate analysis. To explain the variability in tidal deformability needs a greater number of principal components compared to those for the radius at a given NS mass. The contributions from iso-vector nuclear matter parameters to the tidal deformability and radius of NS decrease by $\sim$ 25\% with the increase in mass of NS from 1.2$M_\odot$ to 1.8$M_\odot$.

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Systematic analysis of the impacts of symmetry energy parameters on neutron star properties

The impacts of various symmetry energy parameters on the properties of neutron stars (NSs) have been recently investigated, and the outcomes are at variance, as summarized in Table III of Phys. Rev. D 106, 063005 (2022). We have systematically analyzed the correlations of slope and curvature parameters of symmetry energy at the saturation density ($ρ_0=0.16 \text{fm}^{-3}$) with the tidal deformability and stellar radius of non-spinning neutron stars in the mass range of $1.2 - 1.6 M_\odot$ using a large set of minimally constrained equations of state (EoSs). The EoSs at low densities correspond to the nucleonic matter and are constrained by empirical ranges of a few low-order nuclear matter parameters from the finite nuclei data and the pure neutron matter EoS from chiral effective field theory. The EoSs at high densities ($ρ> 1.5 - 2ρ_0$) are obtained by a parametric form for the speed of sound that satisfies the causality condition. Several factors affecting the correlations between the NS properties and the individual symmetry energy parameters usually encountered in the literature are considered. These correlations are quite sensitive to the choice of the distributions of symmetry energy parameters and their interdependence. But, variations of NS properties with the pressure of $β-$ equilibrated matter at twice the saturation density remain quite robust which maybe due to the fact that the pressure depends on the combination of multiple nuclear matter parameters that describe the symmetric nuclear matter as well as the density dependence of the symmetry energy. Our results are practically insensitive to the behavior of EoS at high densities.

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High-Density behavior of symmetry energy and speed of sound in the dense matter within an effective chiral model

With an effective chiral model, we investigate how the mesonic cross couplings $σ-ρ$ and $ω-ρ$ affect the density content of the symmetry energy and its higher-order slope parameters. Earlier mentioned cross-couplings are crucial to controlling the density content of symmetry energy. For this purpose, we did a case study for different values of the symmetry energy $J_1$, defined at density 0.1 fm$^{-3}$ in the range (23.4 - 25.2) for a fixed value of the slope of the symmetry energy $L_0 = 60$ MeV at saturation density and investigate its effect on the higher-order coefficients and their influence on the underlying equation of state. We found that the model with $J_1= 24.6$ MeV is more favorable with the pure neutron matter (PNM) constraints obtained from $χ$EFT calculations. In addition, we show that all of our models predict a monotonically increasing speed of sound up to four times the saturation density. The speed of sound decreases/saturates above that point and approaches the conformal limit approximately $\sqrt{1/3}~c$ at the center of the maximum mass star.

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Effect of the $σ$-cut potential on the properties of neutron stars with or without a hyperonic core

Motivated by the recent observation of high-mass pulsars ($M \simeq 2 M_{\odot}$), we employ the $σ$-cut potential on the equation of state (EOS) of high-density matter and the properties of neutron stars within the relativistic mean-field (RMF) model using TM1$^{*}$ parameter set. The $σ$-cut potential is known to reduce the contributions of the $σ$ field, resulting in a stiffer EOS at high densities and hence leading to larger neutron star masses without affecting the properties of nuclear matter at normal saturation density. We also analyzed the effect of the same on pure neutron matter and also on the neutron star matter with and without hyperonic core and compared it with the available theoretical, experimental, and observational data. The corresponding tidal deformability ($Λ_{1.4}$) is also calculated. With the choice of meson-hyperon coupling fixed to hypernuclear potentials, we obtain $\approx 10~\%$ increase in mass by employing the $σ$-cut potential for $f_{s} = 0.6$. Our results are in good agreement with various experimental constraints and observational data, particularly with the GW170817 data.

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Nearly model-independent constraints on dense matter equation of state in a Bayesian approach

We apply Bayesian approach to construct a large number of minimally constrained equations of state (EOSs) and study their correlations with a few selected properties of a neutron star (NS). Our set of minimal constraints includes a few basic properties of saturated nuclear matter and low-density pure neutron matter EOS which is obtained from a precise next-to-next-to-next-to-leading-order (N$^{3}$LO) calculation in chiral effective field theory. The tidal deformability and radius of NS with mass $1-2 M_\odot$ are found to be strongly correlated with the pressure of $β$-equilibrated matter at densities higher than the saturation density ($ρ_0 = 0.16$ fm$^{-3}$) in a nearly model-independent manner. These correlations are employed to parametrize the pressure for $β$-equilibrated matter, around 2$ρ_0$, as a function of neutron star mass and the corresponding tidal deformability. The maximum mass of neutron star is also found to be strongly correlated with the pressure of $β$-equilibrated matter at densities $\sim 4.5ρ_0$.

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Bayesian reconstruction of nuclear matter parameters from the equation of state of neutron star matter

The nuclear matter parameters (NMPs), those underlie in the construction of the equation of state (EoS) of neutron star matter, are not directly accessible. The Bayesian approach is applied to reconstruct the posterior distributions of NMPs from the EoS of neutron star matter. The constraints on lower-order parameters as imposed by the finite nuclei observables are incorporated through appropriately chosen prior distributions. The calculations are performed with two sets of pseudo data on the EoS whose true models are known. The median values of second or higher order NMPs show sizeable deviations from their true values and associated uncertainties are also larger. The sources of these uncertainties are intrinsic in nature, identified as (i) the correlations among various NMPs and (ii) the variations in the EoS of symmetric nuclear matter, symmetry energy, and the neutron-proton asymmetry in such a way that the neutron star matter EoS remain almost unaffected.

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