arXiv subjects

Tuhin Malik

Publications and source records attributed to Tuhin Malik.

At least 37 records · Page 2Linked to original sources

arXiv2024

Impact of the Scalar Isovector $δ$-meson on the description of nuclear matter and neutron star properties

The implications of including the scalar isovector $δ$-meson in a relativistic mean-field description of nuclear matter are discussed. A Bayesian inference approach is used to determine the parameters that define the isovector properties of the model. The properties of nuclear matter and neutron stars are discussed. The inclusion of the $δ$-meson has only a small effect on the maximum mass of the neutron star (NS) and on the speed of sound in its interior, but it has a strong effect on the radius and the tidal deformability of low and medium mass stars. This is mainly due to the effect of the $δ$-meson on the symmetry energy and its slope and curvature at saturation, increasing the range of possible values of these three properties, and in particular allowing positive values of the symmetry energy curvature. Due to the effect of the $δ$-meson on the symmetry energy, the proton content of the star is also strongly affected. The inclusion of the $δ$-meson in the relativistic mean-field description of nuclear matter extends the phase space spanned by the model, allowing for a more flexible density dependence of the symmetry energy compatible with experimental, observational, and ab initio constraints.

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arXiv2024

Constraining the high-density behavior of nuclear symmetry energy with direct Urca processes

The density dependence of the symmetry energy in relativistic mean-field models with density dependent couplings is discussed in terms of the possible opening of nucleonic direct Urca processes inside neutron stars, which induce a very rapid cooling of the star. The modification of the parametrization of the isospin channel of two models, DD2 and DDMEX, keeping the same isoscalar properties is considered and the implications are discussed. Within the models discussed it is not possible the onset of nucleonic direct Urca processes in stars with a mass below $\sim1.6\,M_\odot$ if chiral effective field theory constraints for neutron matter are imposed. A Bayesian inference calculation confirms the low probability that nucleonic direct Urca processes occur inside stars with masses below 1.8$M_\odot$, considering the isoscalar channel of the equation of state described by DD2 or DDMEX and the same symmetry energy at saturation. The lowest masses allowing direct Urca processes are associated with a slope of the symmetry energy above $60$ MeV and most likely a positive symmetry energy incompressibility. It is shown that the parametrization of the isospin channel proposed destroys the correlation between symmetry energy slope and incompressibility previously identified in several works.

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arXiv2024

CompactObject: An open-source Python package for full-scope neutron star equation of state inference

The CompactObject package is an open-source software framework developed to constrain the neutron star equation of state (EOS) through Bayesian statistical inference. It integrates astrophysical observational constraints from X-ray timing, gravitational wave events, and radio measurements, as well as nuclear experimental constraints derived from perturbative Quantum Chromodynamics (pQCD) and Chiral Effective Field Theory ($χ$EFT). The package supports a diverse range of EOS models, including meta-model like and several physics-motivated EOS models. It comprises three independent components: an EOS generator module that currently provides seven EOS choices, a Tolman-Oppenheimer-Volkoff (TOV) equation solver, that allows the determination of the Mass Radius and Tidal deformability as observables, and a comprehensive Bayesian inference workflow module, including a complete pipeline for implementing EOS Bayesian inference. Each component can be used independently in different scientific research contexts, such as nuclear physics and astrophysics. In addition, CompactObject is designed to work in synergy with existing software such as CompOSE, allowing the use of the CompOSE EOS database to extend the EOS options available.

astro-ph.HE↗

arXiv2024

Bayesian evaluation of hadron-quark phase transition models through neutron star observables in light of nuclear and astrophysics data

We investigate the role of hybrid and nucleonic equations of state (EOSs) within neutron star (NS) interiors using Bayesian inference to evaluate their alignment with recent observational data from NICER and LIGO-Virgo (LV) collaborations. We find that smooth hybrid EOSs are slightly favoured in explaining NS mass-radius relations, particularly for pulsars such as PSR J0030+0451 and PSR J0740+6620. However, this preference is not definitive, as gravitational wave (GW) data does not significantly differentiate between our hybrid and nucleonic models. Our analysis also reveals tensions between older NICER data and recent measurements for PSR J0437-4715, highlighting the need for more flexible EOS models. Through two sampling approaches - one fixing the hadronic EOS set and the other without fixing the same, we demonstrate that the hybrid EOS model can incorporate stiffer EOSs, resulting in a better agreement with NICER data but leading to higher tidal deformability, which is less consistent with GW observations. In some recent publications a parameter $d_c$, related to the trace anomaly and its derivative, is used to indicate the presence of deconfined quark matter. We find that our hadronic model, which does not include phase transition to deconfined matter, under the influence of imposed constraints, is able to predict values below 0.2 for $d_c$ at around five times saturation density. The hybrid model goes below this threshold at lower densities under the same conditions.

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arXiv2024

Nambu-Jona-Lasinio description of hadronic matter from a Bayesian approach

A microscopic nuclear matter formalism with explicit chiral symmetry based on the Nambu Jona-Lasinio model is considered to describe nuclear matter. To reproduce nuclear matter properties adequately at the saturation density, four-point and eight-point interactions are introduced. Within a Bayesian inference approach, the parameters of the model are determined by imposing nuclear matter, both experimental and from {\it ab-initio} calculations, and neutron star observational constraints. Nuclear matter properties are well reproduced with an effective mass of 0.75 to 0.8 nucleon mass at the saturation density. At 90% confidence level, the radius of a $1.4 ~\rm M_\odot$ star varies between 11.48 km and 13.20 km, masses as large as $\sim 2.2 ~\rm M_\odot$ are predicted and the radius of a 2 M$_\odot$ star is above 10.5 km. High-density perturbative QCD (pQCD) results exclude equations of state that predict larger maximum masses and radii. The speed of sound increases monotonically with density and reaches values as large as $\sqrt{0.7}c$-$\sqrt{0.8}c$ in the center of massive stars. Several properties such as the polytropic index or the renormalized trace anomaly, that have been proposed to identify the deconfined phase transition, are analyzed. Interestingly, the radius of the obtained posterior that also meets pQCD constraints aligns closely with the mass-radius measurement of the recent PSR J0437-4715, which contrasts with other relativistic mean field model results.

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arXiv2024

Astrophysics and Nuclear Physics Informed Interactions in Dense Matter: Inclusion of PSR J0437-4715

We investigate how vector-isoscalar and vector-isovector interactions can be determined within the density regime of neutron stars (NSs), while fulfilling nuclear and astrophysics constrains. We make use of the Chiral Mean Field (CMF) model, a SU(3) nonlinear realization of the sigma model within the mean-field approximation, for the first time within a Bayesian analysis framework. We show that neutron-matter $χ$EFT constraints at low density are only satisfied if the vector-isovector mixed interaction term is included, e.g., a $ω^2ρ^2$ term. We also show the behavior of the model with respect to the conformal limit. We demonstrate that the CMF model is able to predict a value for the parameter $d_c$ related to the trace anomaly and its derivative takes values below 0.2 above four times saturation density within a hadronic version of the model that does not include hyperons or a phase transition to deconfined matter. We compare these effects with results from other (non-chiral) Relativistic Mean Field models to assess how different approaches to incorporating the same physical constraints affect predictions of NS properties and dense matter equations of state. We also include data from the gravitation wave event GW230529 detected by the LIGO-Virgo-Kagra collaboration and the most recent radius measurement of PSR J0437-4715 from the NASA NICER mission. Our analysis reveals that this new NICER measurement leads to an average reduction of approximately $\sim 0.1$ km radius in the posterior of the NS mass-radius relationship.

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arXiv2024

Feasibility of dark matter admixed neutron star based on recent observational constraints

The equation of state (EOS) for neutron stars is modeled using the Relativistic Mean Field (RMF) approach with a mesonic nonlinear (NL) interaction, a modified sigma cut potential (NL-$σ$ cut), and the influences of dark matter in the NL (NL DM). Using a Bayesian analysis framework, we evaluate the plausibility and impact of each scenario. Experimental constraints on the general properties of finite nuclei and heavy ion collisions, along with astrophysical observational data on neutron star radii and tidal deformation, have been taken into account. It was shown that all models, including the PREX-II data, were less favored, indicating that this experimental data seemed to be in tension with the other constraints included in the inference procedure, and were incompatible with chiral effective field theoretical calculations of pure neutron matter. Considering the models with no PREX-II constraints, we find the model NL-$σ$ cut with the largest Bayes evidence, indicating that the constraints considered favor the stiffening of the EOS at large densities. Conversely, the neutron star with a dark matter component is the least favorable case in light of recent observational constraints, among different scenarios considered here. The $f$ and $p$ modes were calculated within the Cowling approximation, and it can be seen that $f$ modes are sensitive to the EOS. An analysis of the slopes of the mass-radius curves and $f$-mode mass curves has indicated that these quantities may help distinguish the different scenarios.We also analyzed the impact of new PSR J0437-4715 measurements on neutron star mass-radius estimates, noting a $\sim$ 0.2 km reduction in the 90\% CI upper boundary across all models and a significant Bayes evidence decrease, indicating potential conflicts with previous data or the necessity for more adaptable models.

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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.

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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.

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arXiv2024

Analysis of Neutron Star $f-$mode Oscillations in General Relativity with Spectral Representation of Nuclear Equations of State

We study quasinormal $f-$mode oscillations in neutron star(NS) interiors within the linearized General Relativistic formalism. We utilize approximately 9000 nuclear Equations of State (EOS) using spectral representation techniques, incorporating constraints on nuclear saturation properties, chiral Effective Field Theory ($χ$EFT) for pure neutron matter, and perturbative Quantum Chromodynamics (pQCD) for densities pertinent to NS cores. The median values of f-mode frequency, $ν_f$ (damping time, $τ_f$) for NS with masses ranging from 1.4 - 2.0 $M_\odot$ lie between 1.80 - 2.20 kHz (0.13 - 0.22 s) for our entire EOS set. Our study reveals a weak correlation between $f-$mode frequencies and individual nuclear saturation properties, prompting the necessity for more intricate methodologies to unveil multi-parameter relationships. We observe a robust linear relationship between the radii and $f-$mode frequencies for different NS masses. Leveraging this correlation alongside NICER observations of PSR J0740+6620 and PSR J0030+0451, we establish constraints that exhibit partial and minimal overlap for observational data from Riley et al. and Miller et al. respectively with our nucleonic EOS dataset. Moreover, NICER data aligns closely with radius and frequency values for a few hadron-quark hybrid EOS models. This indicates the need to consider additional exotic particles such as deconfined quarks at suprasaturation densities. We conclude that future observations of the radius or $f-$mode frequency for more than one NS mass, particularly at the extremes of viable NS mass scale, would either rule out nucleon-only EOS or provide definitive evidence in its favour.

astro-ph.HE↗

arXiv2024

Unified neutron star equations of state calibrated to nuclear properties

Recently, in Malik23, a dataset of several EoS for purely nucleonic stellar matter based on a non-linear RMF model prescription, and constrained to properties of nuclear matter, to state-of-the-art chiral effective field theory calculations for low-density neutron matter, and to astrophysical data, were proposed. In this work, twenty one unified neutron star EoS were chosen from that dataset, in such a way that a large range of values of the slope of the symmetry energy at saturation is covered. Several quantities are calculated and discussed, such as the the proton fraction and the direct Urca behavior, the density dependence of the speed of sound and the trace anomaly, the crust-core transition properties, the compatibility with astrophysical observations, and the neutron matter properties from $χ$EFT calculations and pQCD constraints. We construct unified EoS, where the outer crust is given by the BSk22 functional, and the inner crust is calculated from a CLD approximation. The core is purely nucleonic, made of protons, neutrons, electrons and muons, under charge neutrality and in $β-$equilibrium conditions. The correlation of the slope of the symmetry energy at saturation with the crust-core transition density and proton fraction is analysed, and equations that translate these relations are proposed. Moreover, the spectral representation for all the EOS according to the format proposed in Lindblom10 is given, which is a convenient representation to study quasi-periodic oscillations with realistic EOS. It is shown that several of these EoS have in the center of the most massive NS a speed of sound squared of the order of $\lesssim 0.5$. Most of the EoS predict a maximum central density of the order of about 6 times the nuclear saturation density. Three of the EoS satisfy all of the constraints imposed. All these EoS will be made available in the CompOSE platform.

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arXiv2024

Realizing the potential of deep neural network for analyzing neutron star observables and dense matter equation of state

The difficulty in describing the equation of state (EoS) for nuclear matter at densities above the saturation density ($ρ_0$) has led to the emergence of a multitude of models based on different assumptions and techniques. These EoSs, when used to describe a neutron star (NS), lead to differing values of observables. An outstanding goal in astrophysics is to constrain the dense matter EoS by exploiting astrophysical and gravitational wave measurements. Nuclear matter parameters appear as Taylor coefficients in the expansion of the EoS around the saturation density of symmetric and asymmetric nuclear matter and provide a physically-motivated representation of the EoS. In this paper, we introduce a deep learning-based methodology to predict key neutron stars observables such as the NS mass, NS radius, and tidal deformability from a set of nuclear matter parameters. Using generated mock data, we confirm that the neural network model is able to accurately capture the underlying physics of finite nuclei and replicate inter-correlations between the symmetry energy slope, its curvature, and the tidal deformability arising from a set of physical constraints. We also test our network with mock data generated by a different class of physics model, which was not part of the training, to explore the limitations of model dependency in the results. We also study the validity of our trained model using Bayesian inference and show that the performance of our model is on par with physics-based models with the added benefit of much lower computational cost.

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arXiv2024

Towards Uncovering Dark Matter Effects on Neutron Star Properties: A Machine Learning Approach

In recent years, researchers have become increasingly interested in understanding how dark matter affects neutron stars, helping them to better understand complex astrophysical phenomena. In this paper, we delve deeper into this problem by using advanced machine learning techniques to find potential connections between dark matter and various neutron star characteristics. We employ Random Forest classifiers to analyze neutron star (NS) properties and investigate whether these stars exhibit characteristics indicative of dark matter admixture. Our dataset includes 32,000 sequences of simulated NS properties, each described by mass, radius, and tidal deformability, inferred using recent observations and theoretical models. We explore a two-fluid model for the NS, incorporating separate equations of state for nucleonic and dark matter, with the latter considering a fermionic dark matter scenario. Our classifiers are trained and validated in a variety of feature sets, including the tidal deformability for various masses. Based on confusion matrices, these classifiers can identify NS with admixed dark matter with approximately 17% probability of misclassification. In particular, we find that additional tidal deformability data do not significantly improve the precision of our predictions. This article also delves into the potential of specific NS properties as indicators of the presence of dark matter. Radius measurements, especially at extreme mass values, emerge as particularly promising features. The insights gained from our study will guide future observational strategies and enhance dark matter detection capabilities. According to this study, neutron stars at 1.4 and 2.07 solar masses have radii that strongly suggest dark matter in neutron stars more likely than just hadronic composition, based on NICER data from pulsars PSR J0030+0451 and PSR J0740+6620.

hep-ph↗

arXiv2023

Decoding Neutron Star Observations: Revealing Composition through Bayesian Neural Networks

We exploit the great potential offered by Bayesian Neural Networks (BNNs) to directly decipher the internal composition of neutron stars (NSs) based on their macroscopic properties. By analyzing a set of simulated observations, namely NS radius and tidal deformability, we leverage BNNs as effective tools for inferring the proton fraction and sound speed within NS interiors. To achieve this, several BNNs models were developed upon a dataset of $\sim$ 25K nuclear EoS within a relativistic mean-field framework, obtained through Bayesian inference that adheres to minimal low-density constraints. Unlike conventional neural networks, BNNs possess an exceptional quality: they provide a prediction uncertainty measure. To simulate the inherent imperfections present in real-world observations, we have generated four distinct training and testing datasets that replicate specific observational uncertainties. Our initial results demonstrate that BNNs successfully recover the composition with reasonable levels of uncertainty. Furthermore, using mock data prepared with the DD2, a different class of relativistic mean-field model utilized during training, the BNN model effectively retrieves the proton fraction and speed of sound for neutron star matter.

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arXiv2023

Exploring robust correlations between fermionic dark matter model parameters and neutron star properties: A two-fluid perspective

The current observational properties of neutron stars have not definitively ruled out the possibility of dark matter. In this study, we primarily focus on exploring correlations between the dark matter model parameters and different neutron star properties using a rich set of EOSs. We adopt a two-fluid approach to calculate the properties of neutron stars. For the nuclear matter EOS, we employ several realistic EOS derived from the relativistic mean field model (RMF), each exhibiting varying stiffness and composition. In parallel, we look into the dark matter EOS, considering fermionic matter with repulsive interaction described by a relativistic mean field Lagrangian. A reasonable range of parameters is sampled meticulously. Interestingly, our results reveal a promising correlation between the dark matter model parameters and stellar properties, particularly when we ignore the uncertainties in the nuclear matter EOS. However, when introducing uncertainties in the nuclear sector, the correlation weakens, suggesting that the task of conclusively constraining any particular dark matter model might be challenging using global properties alone, such as mass, radius, and tidal deformability. Notably, we find that dark-matter admixed stars tend to have higher central baryonic density, potentially allowing for non-nucleonic degrees of freedom or direct Urca processes in stars with lower masses. There is also a tantalizing hint regarding the detection of stars with the same mass but different surface temperatures, which may indicate the presence of dark matter. With our robust and extensive dataset, we delve deeper and demonstrate that even in the presence of dark matter, the semi-universal C-Love relation remains intact.

hep-ph↗

arXiv2023

Unveiling a universal relationship between the f(R) parameter and neutron star properties

In recent years, modified gravity theories have gained significant attention as potential replacements for the general theory of relativity. Neutron stars, which are dense compact objects, provide ideal astrophysical laboratories for testing these theories. However, understanding the properties of neutron stars within the framework of modified gravity theories requires careful consideration of the presently known uncertainty of equations of state (EoS) that describe the behavior of matter at extreme densities. In this study, we investigate three realistic EoS generated using a relativistic mean field framework, which covers the currently known uncertainties in the stiffness of neutron star matter. We then employ a Bayesian approach to statistically analyze the posterior distribution of the free parameter $α$ of the $f(R)$ gravity model, specifically $f(R) = R + αR^2$. By using this approach, we are able to account for our limited understanding of the interiors of neutron stars as well as the uncertainties associated with the modified gravity theory. We impose observational constraints on our analysis, including the maximum mass, and the radius of a neutron star with a mass of $1.4 M_{\odot}$ and $2.08 M_{\odot}$, which are obtained from X-ray NICER observations. By considering these constraints, we are able to robustly investigate the relationship between the $f(R)$ gravity model parameter $α$ and the maximum mass of neutron stars. Our results reveal a universality relationship between the $f(R)$ gravity model parameter $α$ and the maximum mass of neutron stars. This relationship provides insights into the behavior of neutron stars in modified gravity theories and helps us understand the degeneracies arising from our current limited knowledge of the interiors of neutron stars and the free parameter $α$ of the modified gravity theory.

gr-qc↗

arXiv2023

Neutron star equation of state: identifying hadronic matter characteristics

The general behavior of the nuclear equation of state (EOS), relevant for the description of neutron stars (NS), is studied within a relativistic mean field description of nuclear matter. Different formulations, both with density dependent couplings and with non-linear mesonic terms, are considered and their predictions compared and discussed. A special attention is drawn to the effect on the neutron star properties of the inclusion of exotic degrees of freedom as hyperons. Properties such as the speed of sound, the trace anomaly, the proton fraction and the onset of direct Urca processes inside neutron stars are discussed. The knowledge of the general behavior of the hadronic equation of state and the implication it has on the neutron star properties will allow to identify signatures of a deconfinement phase transition discussed in other studies.

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arXiv2023

Robust universal relations in neutron star asteroseismology

The non-radial oscillations of the neutron stars (NSs) have been suggested as a useful tool to probe the composition of neutron star matter (NSM). With this scope in mind, we consider a large number of equations of states (EOSs) that are consistent with nuclear matter properties and pure neutron matter EOS based on a chiral effective field theory (chEFT) calculation for the low densities and perturbative QCD EOS at very high densities. This ensemble of EOSs is also consistent with astronomical observations, gravitational waves in GW170817, mass and radius measurements from Neutron star Interior Composition ExploreR (NICER). We analyze the robustness of known universal relations (URs) among the quadrupolar $f$ mode frequencies, masses and radii with such a large number of EOSs and we find a new UR that results from a strong correlation between the $f$ mode frequencies and the radii of NSs. Such a correlation is very useful in accurately determining the radius from a measurement of $f$ mode frequencies in the near future. We also show that the quadrupolar $f$ mode frequencies of NS of masses 2.0 M$_\odot$ and above lie in the range $\sim$ 2-3 kHz in this ensemble of physically realistic EOSs. A NS of mass 2M$_{\odot}$ with a low $f$ mode frequency may indicate the existence of non-nucleonic degrees of freedom.

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