arXiv subjects

Wen-Jie Xie

Publications and source records attributed to Wen-Jie Xie.

At least 19 recordsLinked to original sources

arXiv2026

Bayesian Inference of fine-features of dense matter EOS from future high-precision data of neutron star radii

Future high-precision X-ray and gravitational wave observatories are expected to measure the radii of neutron stars (NSs) with an accuracy better than about 0.1 km. However, it remains unclear what particular aspects of the Equation of State (EOS) and to what precision they will be better constrained. Within a Bayesian framework using a meta-model EOS and mock high-precision NS data, the posterior probability distribution functions (PDFs) of NS matter EOS parameters for both hadronic and quark phases and the transition between them were recently studied. We report here a few highlights of these studies.

astro-ph.HE↗

arXiv2026

Trace anomaly and isospin splitting in inverse-mapped relativistic mean-field theory

Trace anomaly and sound speed provide EOS-level probes of dense-matter nonconformality, but do not by themselves identify the microscopic channels responsible for the response. We study this question with a uniform-matter inverse-mapped relativistic mean-field ensemble constrained by chiral effective field theory, heavy-ion flow information, and neutron-star mass-radius data. The ensemble reproduces the flow-based trace trend in symmetric nuclear matter, while beta-equilibrated matter approaches the neutron-star trace bands more slowly. The resulting splitting, $Δ_{\SNM}-Δ_{\betaeq}$, remains positive over $2--5\nzero$ and is most strongly correlated with the density derivative of the isovector-vector coupling, with bootstrap-stable Spearman coefficients $r_s\simeq0.91--0.92$ at $2--3\nzero$. Its correlation with the beta-equilibrium proton fraction is much weaker. The sound-speed splitting changes sign near $3.38\nzero$, and the derivative term $-\ddΔ/\dd\ln\varepsilon$ becomes sensitive to both scalar-vector and isovector responses above $4\nzero$. Data-combination and controlled-isovector tests show that this channel separation is resolved only when laboratory and astrophysical projections are combined. Thus, within the present inverse-mapped RMF space, the SNM--beta trace splitting acts as a thermodynamic probe of the high-density symmetry sector rather than as a unique signal of exotic degrees of freedom. A finite-nucleus-calibrated extension will be needed to test how much of this channel diagnostic survives in predictive covariant density functionals.

nucl-th↗

arXiv2026

Finite-nucleus-protected high-density extension of covariant density functionals constrained by multimessenger data

We construct a finite-nucleus-protected high-density extension of covariant density functionals by modifying only the isoscalar-vector channel outside the finite-nucleus calibration domain. The extension introduces three parameters controlling the strength, onset, and width of the high-density deformation, while the scalar and isovector channels are kept unchanged. A Bayesian analysis using heavy-ion flow constraints, massive-pulsar information, NICER mass-radius measurements, and the GW170817 tidal constraint shows that the original \ddme interaction is strongly disfavored relative to its protected high-density extension, with $\ln K=\ln(Z_{\rm ext}/Z_{\rm base})=26.67$, where $Z$ denotes the Bayesian evidence, after imposing a causal/stability filter on the reshaped EOS. In contrast, \ddpc serves as a reference functional for which the same extension is not required by the present data, giving $\ln K=-0.44$. The result supports the interpretation that the proposed extension is not an unconstrained phenomenological patch: Bayesian evidence selects it only when demanded by the combined high-density data, while finite-nucleus observables remain unchanged within numerical precision.

nucl-th↗

arXiv2026

Synchrotron polarization of anisotropic electron distribution in GRB prompt emission

In gamma-ray bursts (GRBs), the electron pitch angle ($α$) is usually assumed to be isotropically distributed. However, recent numerical simulations indicate that only the high-energy electrons (with Lorentz factors $γ>γ_{iso}$) are distributed isotropically, whereas the low-energy electrons (with $γ<γ_{iso}$) follow an energy-dependent anisotropic distribution during magnetic reconnection. The mean value of $\sin^2 α$ approximately follows the relation $\langle \sin^2 α\rangle \propto γ^{m}$ for $γ<γ_{iso}$. In principle, polarization measurements may help us constrain the pitch-angle distribution of electrons in GRBs, since different pitch-angle distributions produce distinct synchrotron polarization signatures. The polarization of GRBs produced by isotropically distributed electrons has been extensively studied. In this paper, we investigate synchrotron polarization produced by anisotropically distributed electrons within a globally toroidal magnetic field in GRB prompt emission. Our results show that the synchrotron PDs in the $γ$-ray and X-ray bands produced by anisotropically distributed electrons are systematically lower than those produced by isotropically distributed electrons, while the PD in the optical band could be either lower or higher than that of isotropically distributed electrons, depending primarily on the value of the energy slope $m$. In addition, we compared our numerical results with observational data, and the comparison suggests that an anisotropic distribution of electrons may offer a potential explanation for the PD and spectral data of some GRBs.

astro-ph.HE↗

arXiv2026

Inverse-mapped density-dependent relativistic mean-field inference of the neutron-star equation of state with multi-messenger constraints

We perform a Bayesian inference of the equation of state (EOS) of cold dense matter within a density-dependent relativistic mean-field (DD-RMF) model. An explicit inverse-mapping procedure reconstructs the density-dependent couplings from a physically interpretable ten-dimensional parameter set while enforcing thermodynamic consistency together with stability and causality conditions. The EOS is constrained by complementary multi-messenger data including chiral effective field theory calculations at low density, heavy-ion collision flow information at intermediate densities, NICER mass-radius posteriors, and the existence of approximately two-solar-mass pulsars. The combined constraints strongly restrict both isoscalar and isovector sectors. In particular, the chiral effective field theory band favors a relatively soft symmetry-energy slope around 38 MeV, corresponding to a compact canonical neutron-star radius of about 11.6 km. To reconcile the intermediate-density softness suggested by heavy-ion data with the high-density stiffness required by massive pulsars, the posterior prefers a moderately large Dirac effective mass at saturation together with correlated high-density limits of the scalar and vector couplings. The resulting sound-speed profile remains causal and shows significant stiffening above the conformal limit at several times nuclear saturation density, indicating strongly interacting matter in neutron-star cores. Evidence diagnostics indicate strong compatibility among the adopted constraints within the present DD-RMF framework.

nucl-th↗

arXiv2026

Bayesian Inference of Hybrid Star Properties from Future High-Precision Measurements of Their Radii

Future high-precision X-ray and gravitational-wave observations of neutron stars (NSs) are expected to constrain NS radii with uncertainties as small as $σ\simeq 0.1$~km. Such unprecedented precision offers a unique opportunity to extract new information about the nature and equation of state (EOS) of supradense matter in NS cores. Using mock radius data with uncertainties ranging from $σ= 1.0$ to $0.1$~km, together with a flexible meta-model NS EOS that allows for a first-order hadron-quark phase transition, we perform a Bayesian statistical analysis to assess the impact of radius measurements on EOS constraints. We find that high-precision radius measurements, particularly for massive NSs, significantly tighten constraints on the hadron-quark transition density $ρ_t$, the quark matter mass fraction in NS cores, and several parameters characterizing the EOS of supranuclear hadronic matter, although the degree of improvement depends on the assumed prior range of $ρ_t$. In contrast, even with the highest precision considered, NS radii -- including those of massive stars -- remain largely insensitive to the stiffness of quark matter, independent of the measurement accuracy or the prior range adopted for $ρ_t$.

astro-ph.HE↗

arXiv2026

Bayesian constraints on quark stars from multi-messenger observations

We perform a systematic Bayesian analysis of quark star equations of state under current multimessenger constraints, investigating the impact of prior assumptions and extreme-mass observations. Quark matter is modeled within an interacting MIT bag framework that consistently accommodates color-superconducting phases (2SC, 2SC+s, and CFL) and perturbative QCD corrections. We find that quark star models exhibit a distinct advantage in naturally accommodating the ultra-low mass object HESS J1731-347, a configuration that is challenging for standard neutron star models. In the high-mass regime, the interpretation of the secondary component of GW190814 is shown to be strongly prior-dependent: only broad priors allow for the substantial stiffness required to support such a massive object ($\sim$2.6 M$_\odot$), while more restrictive priors favor a softer equation of state consistent with standard pulsar populations. Microscopically, we demonstrate that current data tightly constrain the effective bag constant and the overall stiffness, but cannot distinguish between different color-superconducting phases. Furthermore, we validate a reduction of the model to two effective parameters without loss of information. Our results indicate that if quark stars exist, their sound speeds consistently exceeds the conformal limit ($c_s^2>1/3$) at stellar densities.

astro-ph.HE↗

arXiv2025

Evolutions of in-medium baryon-baryon scattering cross sections and stiffness of dense nuclear matter from Bayesian analyses of FOPI proton flow excitation functions

Within a Bayesian statistical framework using a Gaussian Process (GP) emulator for an isospin-dependent Boltzmann-Uehling-Uhlenbeck (IBUU) transport model simulator of heavy-ion reactions with momentum-independent Skyrme interactions, we infer from the proton directed and elliptical flow in mid-central Au+Au reactions at beam energies from 150 to 1200 MeV/nucleon taken by the FOPI Collaboration the posterior Probability Distribution Functions (PDFs) of the in-medium baryon-baryon scattering cross section (BBSCS) modification factor $X$ (with respect to their free-space values) and the stiffness parameter $K$ of dense nuclear matter. We find that the most probable value of $X$ evolves from around 0.7 to 1.0 as the beam energy $E_{beam}/A$ increases. On the other hand, the posterior PDF($K$) may have dual peaks having roughly the same height or extended shoulders at high $K$ values. More quantitatively, the posterior PDF($K$) changes from having a major peak around 220 MeV characterizing a soft EOS in the reaction at $E_{beam}/A$=150 MeV to one that peaks around 320 MeV indicating a stiff EOS in the reactions at $E_{beam}/A$ higher than about 600 MeV. The transition from soft to stiff happens in mid-central Au+Au reactions at beam energies around 250 MeV/nucleon in which $K=220$ MeV and $K=320$ MeV are approximately equally probable. Altogether, the FOPI proton flow excitation function data indicate a gradual hardening of hot and dense nuclear matter as its density and temperature increase in reactions with higher beam energies.

nucl-th↗

arXiv2025

Structural robustness of the international food supply network under external shocks and its determinants

The stability of the global food supply network is critical for ensuring food security. This study constructs an aggregated international food supply network based on the trade data of four staple crops and evaluates its structural robustness through network integrity under accumulating external shocks. Network integrity is typically quantified in network science by the relative size of the largest connected component, and we propose a new robustness metric that incorporates both the broadness p and severity q of external shocks. Our findings reveal that the robustness of the network has gradually increased over the past decades, punctuated by temporary declines that can be explained by major historical events. While the aggregated network remains robust under moderate disruptions, extreme shocks targeting key suppliers such as the United States and India can trigger systemic collapse. When the shock broadness p is less than about 0.3 and the shock severity q is close to 1, the structural robustness curves S(p,q) decrease linearly with respect to the shock broadness p, suggesting that the most critical economies have relatively even influence on network integrity. Comparing the robustness curves of the four individual staple foods, we find that the soybean supply network is the least robust. Furthermore, regression and machine learning analyses show that increaseing food (particularly rice and soybean) production enhances network robustness, while rising food prices significantly weaken it.

econ.GN↗

arXiv2024

Astrophysical constraints on nuclear EOSs and coupling constants in RMF models

Utilizing various astrophysical constraints on neutron star structures, we carry out a Bayesian analysis on the density-dependent behaviors of coupling constants in RMF models as well as the nuclear matter properties at supranuclear densities. The effective nucleon interactions in the isoscalar-scalar, isoscalar-vector, and isovector-vector channels are considered, where the corresponding coupling constants ($α_S, α_V, α_{TV}$) are fixed by dividing entire density range into three regions with six independent parameters. In this work we focus on constraining the density-dependent point-coupling constants at supranuclear densities, while the coupling constants at subsaturation densities are derived from the covariant density functional DD-ME2. For those consistent with astrophysical observations, the coupling constants generally decrease with density and approach to small positive values at large enough densities, which qualitatively agrees with various RMF models. The posterior probability density functions and their correlations of the coupling constants and various nuclear matter properties are examined as well. At $1σ$ level, the constrained coupling constants at density $1.5n_0$ ($2.5n_0$) are $α_S = 3.1^{+0.1}_{-0.05} (1.55^{+0.85}_{-0.2}) \times 10^{-4} \mathrm{MeV}^{-2}$, $α_V = 2.3^{+0.1}_{-0.0} (1.3^{+0.55}_{-0.1}) \times 10^{-4} \mathrm{MeV}^{-2}$, and $α_{TV} = 2.05^{+0}_{-0.4} (2.05^{+0}_{-0.5})\times 10^{-5} \mathrm{MeV}^{-2}$. At larger densities, we find the lower limit of $α_{TV}$ is not well constrained, so that more extensive calculations with larger number of free parameters are necessary.

nucl-th↗

arXiv2024

Bayesian Inference of Fine-Features of Nuclear Equation of State from Future Neutron Star Radius Measurements to 0.1km Accuracy

To more precisely constrain the Equation of State (EOS) of supradense neutron-rich nuclear matter, future high-precision X-ray and gravitational wave observatories are proposed to measure the radii of neutron stars (NSs) with an accuracy better than about 0.1 km. However, it remains unclear what particular aspects (other than the stiffness generally spoken of in the literature) of the EOS and to what precision they will be better constrained. In this work, within a Bayesian framework using a meta-model EOS for NSs, we infer the posterior probability distribution functions (PDFs) of incompressibility $K_{0}$ and skewness $J_{0}$ of symmetric nuclear matter (SNM) as well as the slope $L$, curvature $K_{\rm{sym}}$, and skewness $J_{\rm{sym}}$ characterizing the density dependence of nuclear symmetry energy $E_{\rm{sym}}(ρ)$, respectively, from mean values of NS radii consistent with existing observations and an expected accuracy $ΔR$ ranging from about 1.0 km to 0.1 km. We found that (1) the $ΔR$ has little effect on inferring the stiffness of SNM at suprasaturation densities, (2) smaller $ΔR$ reveals more accurately not only the PDFs but also pairwise correlations among parameters characterizing high-density $E_{\rm{sym}}(ρ)$, (3) a double-peak feature of the PDF($K_{\rm{sym}}$) corresponding to the strong $K_{\rm{sym}}-J_{\rm{sym}}$ and $K_{\rm{sym}}-L$ anti-correlations is revealed when $ΔR$ is less than about 0.2 km, and the locations of the two peaks are sensitive to the maximum value of $J_{\rm{sym}}$ reflecting the stiffness of $E_{\rm{sym}}(ρ)$ above about 3 times the saturation density $ρ_0$ of SNM, (4) the high-precision radius measurement for canonical NSs is more useful than that for massive ones for constraining the EOS of nucleonic matter around $(2-3)ρ_0$.

astro-ph.HE↗

arXiv2024

Impact of The Newly Revised Gravitational Redshift of X-ray Burster GS 1826-24 on The Equation of State of Supradense Neutron-Rich Matter

Thanks to the recent advancement in producing rare isotopes and measuring their masses with unprecedented precision, the updated nuclear masses around the waiting-point nucleus $^{64}$Ge in the rapid-proton capture process have led to a significant revision of the surface gravitational redshift of the neutron star (NS) in GS 1826-24 by re-fitting its X-ray burst light curve ({\it X. Zhou et al., Nature Physics {\bf 19}, 1091 (2023)}) using Modules for Experiments in Stellar Astrophysics (MESA). The resulting NS compactness $ξ$ is between 0.244 and 0.342 at 95\% confidence level and its upper boundary is significantly smaller than the maximum $ξ$ previously known. Incorporating this new data within a comprehensive Bayesian statistical framework, we investigate its impact on the Equation of State (EOS) of supradense neutron-rich matter and the required spin frequency for GW190814's minor $m_2$ with mass $2.59\pm 0.05$M$_{\odot}$ to be a rotationally stable pulsar. We found that the EOS of high-density symmetric nuclear matter (SNM) has to be softened significantly while the symmetry energy at supersaturation densities stiffened compared to our prior knowledge from earlier analyses using data from both astrophysical observations and terrestrial nuclear experiments. In particular, the skewness $J_0$ characterizing the stiffness of high-density SNM decreases significantly, while the slope $L$, curvature $K_{\rm{sym}}$, and skewness $J_{\rm{sym}}$ of nuclear symmetry energy all increase appreciably compared to their fiducial values. We also found that the most probable spin rate for the $m_2$ to be a stable pulsar is very close to its mass-shedding limit once the revised redshift data from GS 1826-24 is considered, making the $m_2$ unlikely the most massive NS observed so far.

astro-ph.HE↗

arXiv2024

Resilience of international oil trade networks under extreme event shock-recovery simulations

With the frequent occurrence of black swan events, global energy security situation has become increasingly complex and severe. Assessing the resilience of the international oil trade network (iOTN) is crucial for evaluating its ability to withstand extreme shocks and recover thereafter, ensuring energy security. We overcomes the limitations of discrete historical data by developing a simulation model for extreme event shock-recovery in the iOTNs. We introduce network efficiency indicator to measure oil resource allocation efficiency and evaluate network performance. Then, construct a resilience index to explore the resilience of the iOTNs from dimensions of resistance and recoverability. Our findings indicate that extreme events can lead to sharp declines in performance of the iOTNs, especially when economies with significant trading positions and relations suffer shocks. The upward trend in recoverability and resilience reflects the self-organizing nature of the iOTNs, demonstrating its capacity for optimizing its own structure and functionality. Unlike traditional energy security research based solely on discrete historical data or resistance indicators, our model evaluates resilience from multiple dimensions, offering insights for global energy governance systems while providing diverse perspectives for various economies to mitigate risks and uphold energy security.

econ.EM↗

arXiv2023

Bayesian inference of in-medium baryon-baryon scattering cross sections from HADES proton flow data

Within a Bayesian statistical framework using a Gaussian Process emulator for an isospin-dependent Boltzmann-Uehling-Uhlenbeck (IBUU) transport model simulator of heavy-ion reactions at intermediate energies, we infer from the HADES proton flow data the posterior probability distribution functions of in-medium baryon-baryon scattering cross section modification factor X with respect to free-space and the corresponding incompressibility K of nuclear matter as well as their correlation function. The mean value of X is found to be $X=1.32^{+0.28}_{-0.40}$ at 68\% confidence level assuming the nuclear incompressibility K will not exceed 400 MeV, providing circumstantial evidence for enhanced baryon-baryon scattering cross sections in hot and dense nuclear matter.

nucl-th↗

arXiv2023

Economy importance and structural robustness of the international pesticide trade networks

Pesticides are a kind of agricultural input, whose use can greatly reduce yield loss, regulate plant growth, effectively liberate agricultural productivity, and improve food security. The availability of pesticides in economies all over the world is ensured by pesticide redistribution through international trade and economies play different roles in this process. In this work, we measure and rank the importance of economies using nine node metrics in an evolutionary way. It is found that the clustering coefficient is correlated negatively with the other eight node metrics, while the other eight node metrics are positively correlated with each other and can be grouped into three communities (betweenness; in-degree, PageRank, authority, and in-closeness; out-degree, hub, and out-closeness). We further investigate the structural robustness of the international pesticide trade networks proxied by the giant component size under three types of shocks to economies (node removal in descending order, randomly, and in ascending order). The results show that, except for the clustering coefficient, the international pesticide trade networks are relatively robust under shocks to economies in ascending orders and randomly, but fragile under shocks to economies in descending order. In contrast, removing nodes with the clustering coefficient in ascending and descending orders gives similar robustness curves. Moreover, the structural robustness related to the giant component size evolves over time and exhibits an inverse U-shaped pattern.

physics.soc-ph↗

arXiv2023

An interpretable machine-learned model for international oil trade network

Energy security and energy trade are the cornerstones of global economic and social development. The structural robustness of the international oil trade network (iOTN) plays an important role in the global economy. We integrate the machine learning optimization algorithm, game theory, and utility theory for learning an oil trade decision-making model which contains the benefit endowment and cost endowment of economies in international oil trades. We have reconstructed the network degree, clustering coefficient, and closeness of the iOTN well to verify the effectiveness of the model. In the end, policy simulations based on game theory and agent-based model are carried out in a more realistic environment. We find that the export-oriented economies are more vulnerable to be affected than import-oriented economies after receiving external shocks. Moreover, the impact of the increase and decrease of trade friction costs on the international oil trade is asymmetrical and there are significant differences between international organizations.

physics.soc-ph↗

arXiv2023

Impact of shocks to economies on the efficiency and robustness of the international pesticide trade networks

Pesticides are important agricultural inputs to increase agricultural productivity and improve food security. The availability of pesticides is partially achieved through international trade. However, economies involved in the international trade of pesticides are impacted by internal and external shocks from time to time, which influence the redistribution efficiency of pesticides all over the world. In this work, we adopt simulations to quantify the efficiency and robustness of the international pesticide trade networks under shocks to economies. Shocks are simulated based on nine node metrics, and three strategies are utilized based on descending, random, and ascending node removal. It is found that the efficiency and robustness of the international trade networks of pesticides increased for all the node metrics except the clustering coefficient. Moreover, the international pesticide trade networks are more fragile when import-oriented economies are affected by shocks.

physics.soc-ph↗

arXiv2022

Quantifying the temporal stability of international fertilizer trade networks

The importance of fertilizers to agricultural production is undeniable, and most economies rely on international trade for fertilizer use. The stability of fertilizer trade networks is fundamental to food security. We use three valid methods to measure the temporal stability of the overall network and different functional sub-networks of the three fertilizer nutrients N, P and K from 1990 to 2018. The international N, P and K trade systems all have a trend of increasing stability with the process of globalization. The large-weight sub-network has relatively high stability, but is more likely to be impacted by extreme events. The small-weight sub-network is less stable, but has a strong self-healing ability and is less affected by shocks. Overall, all the three fertilizer trade networks exhibit a stable core with restorable periphery. The overall network stability of the three fertilizers is close, but the K trade has a significantly higher stability in the core part, and the N trade is the most stable in the non-core part.

physics.soc-ph↗