arXiv subjects

Sk Md Adil Imam

Publications and source records attributed to Sk Md Adil Imam.

12 recordsLinked to original sources

arXiv2026

Massive cold hybrid stars in a modified Polyakov-Nambu-Jona-Lasinio model

We propose a modified Polyakov-loop Nambu--Jona-Lasinio (mPNJL) model in which the Polyakov potential is given by an explicit dependence on the quark chemical potential, allowing it to remain finite at zero temperature and thus to describe the confinement-deconfinement transition in cold dense matter. Combining this modified quark sector with hadronic equations of state via a Maxwell construction, we find that, depending on the model parameters, the equation of state can exhibit either two phase transitions, from hadronic matter to confined quark matter and subsequently to deconfined quark matter, or a single transition directly from hadronic to deconfined quark matter or from hadronic to confined quark matter. Stable massive cold hybrid stars with only confined and/or deconfined quark phase are obtained. We systematically examine how the parameters of the modified Polyakov potential and the quark vector interactions control the location of these transitions, and find that repulsive vector interactions are essential to obtain a stable quark core. Hybrid stars with confined and/or a deconfined core can reach maximum masses above $2M_\odot$, provided a sufficiently stiff hadronic equation of state is used at low density. In the core of the maximum-mass configurations, the speed of sound shows variations at finite baryon densities, with c$_s^2(μ)$ departing from the asymptotic conformal value c$_s^2$ = 1/3 in confined core stars. These variations serve as a diagnostic of the equation-of-state stiffness while remaining fully consistent with causality and thermodynamic stability. This work establishes the qualitative role of each model parameter in shaping hybrid-star structure.

hep-ph↗

arXiv2026

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.

nucl-th↗

arXiv2026

How Loud Must a Neutron-Star Merger Be to Reveal Its Equation of State?

The tidal response of neutron stars during binary inspiral encodes the equation of state (EOS) of dense matter in the gravitational-wave signal. Quantifying the signal-to-noise ratio (SNR) required to distinguish competing EOS models with third-generation detectors is therefore essential. We perform Bayesian nested-sampling parameter estimation on simulated binary neutron star signals observed by an Einstein Telescope plus two Cosmic Explorer detector network and compute the evidence difference between correct- and incorrect-EOS recovery models over a broad range of SNR. Across two tidal-deformability contrasts, a swap of the true and recovery EOS, and two binary mass points, we find a common scaling, $Δ\log Z = A\,\mathrm{SNR}^{n}$ with $n \simeq 1.74$--$1.95$, where the EOS contrast and binary properties determine only the prefactor $A$. This behavior follows from an Occam-factor argument, yielding $Δ\log Z \propto (Δ\tildeΛ\,\mathrm{SNR})^{2}$. Calibrating this relation on three configurations predicts, before the run, the SNR required for decisive EOS discrimination in the fourth to within $0.3\%$. These results establish a quantitative framework for assessing the EOS-discrimination reach of third-generation gravitational-wave detector networks.

gr-qc↗

arXiv2026

Tests of scalar polarizations with multi-messenger events

Gravitational wave (GW) observations provide a unique opportunity to test Einstein's General Relativity (GR) in the strong-field regime. While GR predicts only two tensor polarization modes, generic metric theories allow up to six independent modes. We perform a parameterized test of GR using the parameterized post-Einsteinian (PPE) framework applied to GW170817, incorporating for the first time the polarization angle constraints from the gamma-ray burst afterglow alongside other electromagnetic (EM) counterpart information. We extend the GR waveform by adding a scalar breathing mode and modifications to the tensor modes, introducing three non-GR parameters. We perform Bayesian inference for both quadrupole $\ell = |m|= 2$ and dipole $\ell = |m|= 1$ angular harmonics, with two frequency evolution models. For $\ell = |m| = 2$, we find that within the extended PPE framework the scalar amplitude deviates from zero at the $2$--$3σ$ level, leading to a modest preference for modified gravity. However, due to penalization of extra parameters, Bayesian model comparison still favors pure GR over the extended PPE waveform model, with a log Bayes factor of $Δ\log \mathcal{Z} = 4.67 \pm 0.32$. The EM constraint on the polarization angle places very tight bounds on non-GR parameters; for instance, in the case $\ell = |m| = 2$, the bound on the scalar (tensor) amplitude modification parameter improves by roughly $60\%$ $(30\%)$, highlighting the impact that long-term follow up of GW events can have on tests of gravity.

gr-qc↗

arXiv2026

NucleiML: A machine learning framework of ground-state properties of finite nuclei for accelerated Bayesian exploration

The global behavior of the nuclear equation of state (EoS) is commonly studied using data from finite nuclei (FN), heavy-ion collisions, and astrophysical observations of neutron stars (NS). The constraints derived from FN such as binding energies and charge radii play the most crucial role in shaping the EoS up to saturation density. The computational cost associated with explicitly incorporating these constraints presents a significant challenge especially when the aim is to explore the model uncertainties rather than optimizing a single model. We address this by introducing NucleiML (NML), a machine learning framework trained on ground-state properties of a few finite nuclei generated by a relativistic mean-field model. NML allows us to integrate FN and NS properties within a Bayesian inference framework in an efficient manner. The results demonstrate reasonable accuracy and a speedup of $\sim 10^4$ times for calculation of FN properties for a single parameter set, yielding roughly $\sim 10^3 \times$ speed up in the Bayesian framework. The present study makes the case for extending the work to a larger set of nuclei, potentially enabling future studies of NS properties to incorporate the whole nuclear chart.

nucl-th↗

arXiv2025

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.

nucl-th↗

arXiv2024

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.

nucl-th↗

arXiv2024

Implications of comprehensive nuclear and astrophysics data on the equations of state of neutron star matter

The equations of state (EoSs) governing neutron star (NS) matter obtained for both non-relativistic and relativistic mean-field models are systematically confronted with a diverse set of terrestrial data and astrophysical observations within the Bayesian framework. The terrestrial data, spans from bulk properties of finite nuclei to the heavy-ion collisions, constrain the symmetric nuclear matter EoS and the symmetry energy up to twice the saturation density ($ρ_0$= 0.16 fm$^{-3}$). The astrophysical observations encompass the NS radius, the tidal deformability, and the lower bound on maximum mass. Three distinct posterior distributions of EoSs are generated by gradually updating the priors with different constraints: (i) only the maximum NS mass, (ii) incorporating additional terrestrial data, (iii) combining both the terrestrial data and astrophysical observations. These EoS distributions are then compared using the Kullback-Liebler divergence which highlights the significant constraints imposed on the EoSs by the currently available lower bound of NS maximum mass and terrestrial data. The remaining astrophysical observations marginally refine the EoS within the density range $\sim$ 2-3$ρ_0$. It is observed that the relativistic mean field model yields stiffer EoS around the saturation density, but predict smaller values of the speed of sound and proton fraction in the interior of massive stars.

nucl-th↗

arXiv2024

Direct mapping of tidal deformability to the iso-scalar and iso-vector nuclear matter parameters

Background: The equations of state (EoSs) which determine the properties of neutron stars (NSs) are often characterized by the iso-scalar and iso-vector nuclear matter parameters (NMPs). Recent attempts to relate the radius and tidal deformability of a NS to the individual NMPs have been inconclusive. These properties display strong correlations with the pressure of NS matter which depends on several NMPs. The knowledge of minimal NMPs that determine the NS properties will be necessary to address any connection between NS properties (e.g., tidal deformability) and that of finite nuclei. Purpose: To identify the important NMPs required to describe the tidal deformability of neutron star for astrophysically relevant range of their gravitational masses (1.2 -- 1.8 M$_\odot$) as encountered in the binary neutron star merger events. Method: We construct a large set of EoSs using four iso-scalar and five iso-vector NMPs. These EOSs are employed to perform a systematic analysis to isolate the NMPs that predominantly determine the tidal deformability, over a wide range of NS mass. The tidal deformability is then directly mapped to these NMPs. Results: The tidal deformability of the NS with mass 1.2-1.8 M$_\odot$ can be determined within 10$\%$ directly in terms of four nuclear matter parameters, namely, the incompressibility $K_0$ and skewness $Q_0$ of symmetric nuclear matter, and the slope $L_0$ and curvature parameter $K_{\rm sym,0}$ of symmetry energy. Conclusion: A function that quickly estimates the value of tidal deformability in terms of minimal nuclear matter parameters is developed. Our method can also be extended to other NS observables.

nucl-th↗

arXiv2023

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.

nucl-th↗

arXiv2022

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 $\sim 4.5ρ_0$.

nucl-th↗

arXiv2022

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.

nucl-th↗