The general behavior of the nuclear equation of state (EOS), relevant for the description of neutron stars (NS), is studied within a Bayesian approach applied to a set of models based on a density dependent relativistic mean field description of nuclear matter. The EOS is subjected to a minimal number of constraints based on nuclear saturation properties and the low density pure neutron matter EOS obtained from a precise next-to-next-to-next-to-leading order (N$^{3}$LO) calculation in chiral effective field theory ($χ$EFT). The posterior distributions of the model parameters obtained under these minimal constraints are employed to construct the distributions of various nuclear matter properties and NS properties such as radii, tidal deformabilites, central energy densities and speeds of sound etc. We found that 90% confidence interval (CI) for allowed NS mass - radius relationship and tidal deformabilites are compatible with GW170817 and recent NICER observations, without invoking the exotic degrees of freedom. A central speed-of-sound of the order of $\sqrt{2/3}$ $c$ is obtained. The maximum neutron star mass allowed by the model is 2.5 $M_\odot$.
The compatibility of the QCD sum rules and effective hadronic models predictions are examined. For this purpose we have considered the results for the nucleon self-energy in a dense hadronic environment provided by two independent QCD sum-rules calculations. They are immersed in a theory of hadronic fields giving rise to non-linear interactions, whose vertices are parameterized in different ways. Although all of them reproduce the self-energy used as input, very different descriptions of nuclear observables are obtained. Only under very definite circumstances we have found an acceptable agreem…
We present a Bayesian analysis to constrain the equation of state of dense nucleonic matter by exploiting the available data from symmetric nuclear matter at saturation and from observations of compact X-ray sources and from the gravitational wave event GW170817. For the first time, such analysis is performed by using a class of models, the relativistic mean field models, which allow to consistently construct an equation of state in a wide range of densities, isospin asymmetries and temperatures. The selected class of models contains five nuclear physics empirical parameters at saturation for …
Using an explicitly isospin-dependent parametric Equation of State (EOS) for the core of neutron stars (NSs) within the Bayesian statistical approach, we infer the EOS parameters of super-dense neutron-rich nuclear matter from three sets of imagined mass-radius correlation data representing typical predictions by various nuclear many-body theories, i.e, the radius stays the same, decreases or increases with increasing NS mass within $\pm 15\%$ between 1.4 M$_{\odot}$ and 2.0 M$_{\odot}$. The corresponding average density increases quickly, slowly or slightly decreases as the NS mass increases …
Bayesian Inference of Dense-Matter Equations of State from Small-Radius Compact Stars with Twin-Star Scenarios
School of Physics, Nankai University（南开大学物理学院）；Shenzhen Research Institute of Nankai University（南开大学深圳研究院）；Department of Physics, Faculty of Science, Tianjin University（天津大学理学院物理系）
本文通过贝叶斯方法研究致密物质方程 of state，探讨小半径致密星体是否能被双星情景所容纳，通过约束参数发现相变特征及对潮汐变形性的影响。
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 d…
Constraining the equation of state of cold dense matter in compact stars is a major science goal for observing programmes being conducted using X-ray, radio, and gravitational wave telescopes. We discuss Bayesian hierarchical inference of parametrised dense matter equations of state. In particular we generalise and examine two inference paradigms from the literature: (i) direct posterior equation of state parameter estimation, conditioned on observations of a set of rotating compact stars; and (ii) indirect parameter estimation, via transformation of an intermediary joint posterior distributio…
Neutron star structure and nuclear matter properties from a general Walecka-type model with Bayesian analysis
School of Frontier Sciences, Nanjing University（前沿科学学院，南京大学）；School of Fundamental Physics and Mathematical Sciences, Hangzhou Institute for Advanced Study, UCAS（基础物理与数学学院，杭州高等研究院，中国科学院大学）
Evolutions of in-medium baryon-baryon scattering cross sections and stiffness of dense nuclear matter from Bayesian analyses of FOPI proton flow excitation functions
Understanding the dense matter equation of state at extreme conditions is an important open problem. Astrophysical observations of neutron stars promise to solve this, with NICER poised to make precision measurements of mass and radius for several stars using the waveform modelling technique. What has been less clear, however, is how these mass-radius measurements might translate into equation of state constraints and what are the associated equation of state sensitivities. We use Bayesian inference to explore and contrast the constraints that would result from different choices for the equati…
[Purpose:] We infer the posterior probability distribution functions (PDFs) and correlations of nine parameters characterizing the EOS of dense neutron-rich matter encapsulating a first-order hadron-quark phase transition from the radius data of canonical NSs reported by LIGO/VIRGO, NICER and Chandra Collaborations. We also infer the quark matter (QM) mass fraction and its radius in a 1.4 M$_{\odot}$ NS and predict their values in more massive NSs. [Method:] Meta-modelings are used to generate both hadronic and QM EOSs in the Markov-Chain Monte Carlo sampling process within the Bayesian statis…
We suggest a new Bayesian analysis (BA) using disjunct M-R constraints for extracting probability measures for cold, dense matter equations of state (EoS). One of the key issues of such an analysis is the question of a deconfinement transition in compact stars and whether it proceeds as a crossover or rather as a first order transition. We show by postulating results of not yet existing radius measurements for the known pulsars with a mass of $2M_\odot$ that a radius gap of about 3 km would clearly select an EoS with a strong first order phase transition as the most probably one. This would su…
New hard-scattering measurements from the LHC proton-lead run have the potential to provide important constraints on the nuclear parton distributions and thus contributing to a better understanding of the initial state in heavy ion collisions. In order to quantify these constraints, as well as to assess the compatibility with available nuclear data from fixed target experiments and from RHIC, the traditional strategy is to perform a global fit of nuclear PDFs. This procedure is however time consuming and technically challenging, and moreover can only be performed by the PDF fitters themselves.…
Bayesian inferences on covariant density functionals from multimessenger astrophysical data: Influences of parametrizations of density dependent couplings
Institute of Theoretical Physics, Shanxi University（山西大学理论物理研究所）；School of Science, Huzhou University（湖州学院理学院）；School of Physical Science and Technology, Southwest University（西南大学物理科学与技术学院）；Frankfurt Institute for Advanced Studies（法兰克福高等研究院）；Institute of Theoretical Physics, University of Wrocław（弗罗茨瓦夫大学理论物理研究所）；China Institute of Atomic Energy（中国原子能科学研究院）
We suggest a new Bayesian analysis using disjunct mass and radius constraints for extracting probability measures for cold, dense nuclear matter equations of state. One of the key issues of such an analysis is the question of a deconfinement transition in compact stars and whether it proceeds as a crossover or rather as a first order transition. The latter question is relevant for the possible existence of a critical endpoint in the QCD phase diagram under scrutiny in present and upcoming heavy-ion collision experiments.
We systematically compare an event-by-event heavy-ion collision model to data from the Large Hadron Collider. Using a general Bayesian method, we probe multiple model parameters including fundamental quark-gluon plasma properties such as the specific shear viscosity $η/s$, calibrate the model to optimally reproduce experimental data, and extract quantitative constraints for all parameters simultaneously. The method is universal and easily extensible to other data and collision models.
Toward a Unified Understanding of the Dense Matter Equation of State
University of Trieste（的里雅斯特大学）；INFN - Section of Trieste（意大利国家核物理研究所的里雅斯特分部）；University of Houston（休斯顿大学）；Goethe University（法兰克福歌德大学）；Helmholtz Research Academy Hesse for FAIR (HFHF)（黑森亥姆霍兹FAIR研究院）；Nikhef（荷兰国家核与亚原子物理研究所）；Utrecht University（乌得勒支大学）；Duke University（杜克大学）；Ohio University（俄亥俄大学）
