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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, 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 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., Comment: 19 pages with 15 figures

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 ($\alpha_S, \alpha_V, \alpha_{TV}$) 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 $1\sigma$ level, the constrained coupling constants at density $1.5n_0$ ($2.5n_0$) are $\alpha_S = 3.1^{+0.1}_{-0.05} (1.55^{+0.85}_{-0.2}) \times 10^{-4} \mathrm{MeV}^{-2}$, $\alpha_V = 2.3^{+0.1}_{-0.0} (1.3^{+0.55}_{-0.1}) \times 10^{-4} \mathrm{MeV}^{-2}$, and $\alpha_{TV} = 2.05^{+0}_{-0.4} (2.05^{+0}_{-0.5})\times 10^{-5} \mathrm{MeV}^{-2}$. At larger densities, we find the lower limit of $\alpha_{TV}$ is not well constrained, so that more extensive calculations with larger number of free parameters are necessary.

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 $E_{\rm{sym}}(\rho)$, respectively, from mean values of NS radii consistent with existing observations and an expected accuracy $\Delta R$ ranging from about 1.0 km to 0.1 km. We found that (1) the $\Delta R$ has little effect on inferring the stiffness of SNM at suprasaturation densities, (2) smaller $\Delta R$ reveals more accurately not only the PDFs but also pairwise correlations among parameters characterizing high-density $E_{\rm{sym}}(\rho)$, (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 $\Delta R$ 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 $E_{\rm{sym}}(\rho)$ above about 3 times the saturation density $\rho_0$ 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 $(2-3)\rho_0$., Comment: 34 pages with additional results, discussions and appendices. Phys. Rev. D in press

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.

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 $\xi$ is between 0.244 and 0.342 at 95\% confidence level and its upper boundary is significantly smaller than the maximum $\xi$ 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., Comment: Additional results and discussions added. Phys. Rev. D in press

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., Comment: Added a section on Effects of Prior Ranges. Nuclear Physics A in press

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., Comment: 14 pages, 5 figures

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., Comment: 17 pages, 14 figures

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., Comment: 12 pages, 5 figures

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., Comment: 13 pages including 6 figures

The statistical properties including community structure of the international trade networks of all commodities as a whole have been studied extensively. However, the international trade networks of individual commodities often behave differently. Due to the importance of pesticides in agricultural production and food security, we investigate the evolving community structure in the international pesticide trade networks (iPTNs) of five categories from 2007 to 2018. We unveil the community structures in the undirected and directed iPTNs exhibits regional patterns. However, the regional patterns are very different for undirected and directed networks and for different categories of pesticide. Moreover, the community structure is stabler in the directed iPTNs than in the undirected iPTNs. We also extract the intrinsic community blocks for the directed international trade networks of each pesticide category. It is found that the largest intrinsic community block is the stablest that appears in every pesticide category and contains important economies (Belgium, Germany, Spain, France, United Kingdom, Italy, Netherlands, and Portugal) in Europe. Other important and stable intrinsic community blocks are Canada and the United States in North America, Argentina and Brazil in South America, and Australia and New Zealand in Oceania. These findings imply the importance of geographic distance and the complementarity of important adjacent economies in the international trade of pesticides., Comment: 31 pages including 22 figures

Transport models are the main method to obtain physics information from low to relativistic-energy heavy-ion collisions. The Transport Model Evaluation Project (TMEP) has been pursued to test the robustness of transport model predictions in reaching consistent conclusions from the same type of physical model. Calculations under controlled conditions of physical input and set-up were performed with various participating codes. These included both calculations of nuclear matter in a box with periodic boundary conditions, and more realistic calculations of heavy-ion collisions. In this intermediate review, we summarize and discuss the present status of the project. We also provide condensed descriptions of the 26 participating codes, which contributed to some part of the project. These include the major codes in use today. We review the main results of the studies completed so far. They show, that in box calculations the differences between the codes can be well understood and a convergence of the results can be reached. These studies also highlight the systematic differences between the two families of transport codes, known as BUU and QMD type codes. However, when the codes were compared in full heavy-ion collisions using different physical models, as recently for pion production, they still yielded substantially different results. This calls for further comparisons of heavy-ion collisions with controlled models and of box comparisons of important ingredients, like momentum-dependent fields, which are currently underway. We often indicate improved strategies in performing transport simulations and thus provide guidance to code developers. Results of transport simulations of heavy-ion collisions from a given code will have more significance if the code can be validated against benchmark calculations such as the ones summarized in this review., Comment: 114 pages, 14 figures, 479 references, accepted for publication in Progress of Particle and Nuclear Phsics

The isospin dependence of in-medium nuclear effective interactions is a fundamental issue in nuclear physics and has broad ramifications in astrophysics. Its uncertainties, especially the difference of neutron-proton interactions in the isosinglet and isotriplet channels, affect significantly the density and momentum dependence of the isovector single-nucleon potential and nucleon-nucleon short-range correlation in neutron-rich matter. Consequently, the neutron-proton effective mass splitting and the density dependence of nuclear symmetry energy are still rather uncertain. Heavy-ion reactions especially those involving rare isotopes is a useful tool for probing the isospin dependence of nuclear effective interactions through (1) the neutron-skin in coordinate and proton-skin in momentum of the initial state of colliding nuclei, (2) the density and momentum dependence of especially the isovector nuclear mean-field as well as (3) the isospin dependence of in-medium nucleon-nucleon cross sections. Observations of neutron stars especially since GW1710817 have also helped us significantly in understanding the isospin dependence of nuclear effective interactions. {\it We summarize here a review talk on these issues given at the 2021 International Workshop on multi-facets of EOS and Clustering. For details we refer the readers to the original publications and references therein}., Comment: Proc. of the International Workshop on Multi-facets of EoS and Clustering, Caen, France, Nov. 23-26th, 2021

New observational data of neutron stars since GW170817 have helped improve our knowledge about nuclear symmetry energy especially at high densities. We have learned particularly: (1) The slope parameter $L$ of nuclear symmetry energy at saturation density $\rho_0$ of nuclear matter from 24 new analyses is about $L\approx 57.7\pm 19$ MeV at 68\% confidence level consistent with its fiducial value, (2) The curvature $K_{\rm{sym}}$ from 16 new analyses is about $K_{\rm{sym}}\approx -107\pm 88$ MeV, (3) The magnitude of nuclear symmetry energy at $2\rho_0$, i.e. $E_{\rm{sym}}(2\rho_0)\approx 51\pm 13$ MeV at 68\% confidence level, has been extracted from 9 new analyses of neutron star observables consistent with results from earlier analyses of heavy-ion reactions and the latest predictions of the state-of-the-art nuclear many-body theories, (4) while the available data from canonical neutron stars do not provide tight constraints on nuclear symmetry energy at densities above about $2\rho_0$, the lower radius boundary $R_{2.01}=12.2$ km from NICER's very recent observation of PSR J0740+6620 of mass $2.08\pm 0.07$ $M_{\odot}$ and radius $R=12.2-16.3$ km at 68\% confidence level sets a tight lower limit for nuclear symmetry energy at densities above $2\rho_0$, (5) Bayesian inferences of nuclear symmetry energy using models encapsulating a first-order hadron-quark phase transition from observables of canonical neutron stars indicate that the phase transition shift appreciably both the $L$ and $K_{\rm{sym}}$ to higher values but with larger uncertaintie , (6) The high-density behavior of nuclear symmetry energy affects significantly the minimum frequency necessary to rotationally support GW190814's secondary component of mass (2.50-2.67) $M_{\odot}$ as the fastest and most massive pulsar discovered so far., Comment: Published version with added discussions and references

Both the incompressibility \Ka of a finite nucleus of mass A and that ($K_{\infty}$) of infinite nuclear matter are fundamentally important for many critical issues in nuclear physics and astrophysics. While some consensus has been reached about the $K_{\infty}$, accurate theoretical predictions and experimental extractions of $K_{\tau}$ characterizing the isospin dependence of \Ka have been very difficult. We propose a differential approach to extract the \Kt and \Ki independently from the \Ka data of any two nuclei in a given isotope chain. Applying this new method to the \Ka data from isoscalar giant monopole resonances (ISGMR) in even-even Pb, Sn, Cd and Ca isotopes taken by U. Garg {\it et al.} at the Research Center for Nuclear Physics (RCNP), Osaka University, Japan, we find that the $^{106}$Cd-$^{116}$Cd and $^{112}$Sn-$^{124}$Sn pairs having the largest differences in isospin asymmetries in their respective isotope chains measured so far provide consistently the most accurate up-to-date \Kt value of $K_{\tau}=-616\pm 59$ MeV and $K_{\tau}=-623\pm 86$ MeV, respectively, largely independent of the remaining uncertainties of the surface and Coulomb terms in expanding the $K_{\rm A}$, while the $K_{\infty}$ values extracted from different isotopes chains are all well within the current uncertainty range of the community consensus for $K_{\infty}$. Moreover, the size and origin of the "Soft Sn Puzzle" is studied with respect to the "Stiff Pb Phenomenon". It is found that the latter is favored due to a much larger (by $\sim 380$ MeV) \Kt for Pb isotopes than for Sn isotopes, while the \Ki from analyzing the \Ka data of Sn isotopes is only about 5 MeV less than that from analyzing the Pb data., Comment: More discussions added. Phys. Rev. C in press

[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 statistical framework. An explicitly isospin-dependent parametric EOS for the $npe\mu$ matter in NSs at $\beta$ equilibrium is connected through the Maxwell construction to the QM EOS described by the constant speed of sound (CSS) model of Alford, Han and Prakash. [Results:] (1) The most probable values of the hadron-quark transition density $\rho_t/\rho_0$ and the relative energy density jump there $\De\ep/\ep_t$ are $\rho_t/\rho_0=1.6^{+1.2}_{-0.4}$ and $\De\ep/\ep_t=0.4^{+0.20}_{-0.15}$ at 68\% confidence level, respectively. The corresponding probability distribution of QM fraction in a 1.4 M$_{\odot}$ NS peaks around 0.9 in a 10 km sphere. Strongly correlated to the PDFs of $\rho_t$ and $\De\ep/\ep_t$, the PDF of the QM speed of sound squared $\cQMsq/c^2$ peaks at $0.95^{+0.05}_{-0.35}$, and the total probability of being less than 1/3 is very small. (2) The correlations between PDFs of hadronic and QM EOS parameters are very weak. [Conclusions:] The available astrophysical data considered together with all known EOS constraints from theories and terrestrial nuclear experiments prefer the formation of a large volume of QM even in canonical NSs., Comment: Added Fig.5 and the associated discussions/references regarding effects of the Seidov condition for first-order phase transition. Physical Review C in press

The neutron skin thickness $\Delta r_{np}$ in heavy nuclei has been known as one of the most sensitive terrestrial probes of the nuclear symmetry energy around $\frac{2}{3}$ of the saturation density $\rho_0$ of nuclear matter. Existing neutron skin data mostly from hadronic observables suffer from large uncertainties and their extraction from experiments are often strongly model dependent. While waiting eagerly for the promised model-independent and high-precision neutron skin data for $^{208}$Pb and $^{48}$Ca from the parity-violating electron scattering experiments (PREX-II and CREX at JLab as well as MREX at MESA), within the Bayesian statistical framework using the Skyrme-Hartree-Fock model we infer the posterior probability distribution functions (PDFs) of the slope parameter $L$ of the nuclear symmetry energy at $\rho_0$ from imagined $\Delta r_{np}(^{208}$Pb$)=0.15$, 0.20, and 0.30 fm as well as $\Delta r_{np}(^{48}$Ca$)=0.12$, 0.15, and 0.25 fm, with different $1\sigma$ error bars. The results are compared with the PDFs of $L$ inferred using the same approach from the available $\Delta r_{np}$ data for Sn isotopes from hadronic probes. They are also compared with results from a recent Bayesian analysis of the radius and tidal deformability data of canonical neutron stars from GW170817 and NICER. The neutron skin data for Sn isotopes gives $L=45.5^{+26.5}_{-21.6}$ MeV surrounding its mean value or $L=53.4^{+18.6}_{-29.5}$ MeV surrounding its maximum {\it a posteriori} value, respectively, with the latter smaller than but consistent with the $L=66_{-20}^{+12}$ MeV from the neutron star data within their 68\% confidence intervals. In order to provide additionally useful information on $L$ extracted from the $\Delta r_{np}$ of Sn isotopes, the experimental error bar of $\Delta r_{np}(^{208}$Pb) should be at least smaller than 0.06 fm aimed by some current experiments., Comment: 11 pages, 6 figures, accepted by Physical Review C

We put a stringent constraint on the isovector nuclear interactions in the Skyrme-Hartree-Fock model from the centroid energy $E_{-1}$ of the isovector giant dipole resonance in $^{208}$Pb as well as its electric polarizability $\alpha_D$. Using the Bayesian analysis method, $E_{-1}$ and $\alpha_D$ are found to be mostly determined by the nuclear symmetry energy $E_{sym}$ at about $\rho^\star=0.05$ fm$^{-3}$ and the isovector nucleon effective mass $m_v^\star$ at the saturation density. At $90\%$ confidence level, we obtain $E_{sym}(\rho^\star) = 16.4 ^{+1.0}_{-0.9}$ MeV and $m_v^\star/m = 0.79 ^{+0.06}_{-0.06}$., Comment: 5 pages, 5 figures

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 from 1.4 M$_{\odot}$ to 2.0 M$_{\odot}$. Using the posterior probability distribution functions (PDFs) of EOS parameters inferred from GW170817 and NICER radius data for canonical NSs as references, we investigate how future radius measurements of massive NS will improve our knowledge about the EOS of super-dense neutron-rich nuclear matter, especially its symmetry energy term, compared to what people have already learned from analyzing the GW170817 and NICER data. While the EOS of symmetric nuclear matter (SNM) inferred from the three data sets are approximately the same, the corresponding high-density symmetry energies at densities above about $2\rho_0$ are very different, indicating that the radii of massive NSs carry reliable information about the high-density behavior of nuclear symmetry energy with little influence from the remaining uncertainties of the SNM EOS., Comment: Added the Subsection 3.6. The Astrophysical Journal in press

As a vital strategic resource, oil has an essential influence on the world economy, diplomacy and military development. Using oil trade data to dynamically monitor and warn about international trade risks is an urgent need. Based on the UN Comtrade data from 1988 to 2017, we construct unweighted and weighted global oil trade networks (OTNs). Complex network theories have some advantages in analyzing global oil trade as a system with numerous economies and complicated relationships. This paper establishes a trading-based network model for global oil trade to study the evolving efficiency, criticality and robustness of economies and the relationships between oil trade partners. The results show that for unweighted OTNs, the efficiency of oil flows gradually increases with growing complexity of the OTNs, and the weighted efficiency indicators are more capable of highlighting the impact of major events on the OTNs. The identified critical economies and trade relationships have more important strategic significance in the real market. The simulated deliberate attacks corresponding to national bankruptcy, trade blockade, and economic sanctions have a more significant impact on the robustness than random attacks. When the economies are promoting high-quality economic development, and continuously enhancing positions in the OTN, more attention needs be paid to the identified critical economies and trade relationships. To conclude, some suggestions for application are given according to the results., Comment: 19 pages, 9 figures

Within the Bayesian statistical framework we infer the incompressibility $K_0$, skewness $J_0$ and kurtosis $Z_0$ parameters of symmetric nuclear matter (SNM) at its saturation density $\rho_0$ using the constraining bands on the pressure in cold SNM in the density range of 1.3$\rho_0$ to 4.5$\rho_0$ from transport model analyses of kaon production and nuclear collective flow in relativistic heavy-ion collisions. As the default option assuming the $K_0$, $J_0$ and $Z_0$ have Gaussian prior probability distribution functions (PDFs) with the means and variances of $235\pm 30$, $-200\pm 200$ and $-146\pm 1728$ MeV, their posterior most probable values are narrowed down to 192$^{+12}_{-16}$ MeV, -180$^{+100}_{-110}$ MeV and 200$^{+250}_{-250}$ at 68\% confidence level, respectively. The results are largely independent of the prior PDFs of $J_0$ and $Z_0$ used. However, if one adopts the strong belief that the incompressibility $K_0$ has a uniform prior PDF within its absolute boundary of 220-260 MeV as one can find easily in the literature, the posterior most probable values of $K_0$, $J_0$ and $Z_0$ shift to $K_0=220^{+6}_{-0}$ MeV, $J_0=-390^{+60}_{-70}$ MeV and $Z_0=600^{+200}_{-200}$ MeV, respectively. While the posterior PDFs of the SNM EOS parameters depend somewhat on the prior PDF of $K_0$ used, the results from using different prior PDFs are qualitatively consistent. The uncertainties of all three parameters are significantly reduced especially for the $J_0$ and $Z_0$ parameters compared to their current values., Comment: Significantly more materials added. Journal of Physics G in press

Within the minimum model of neutron stars (NS) consisting of neutrons, protons and electrons, a new approach is proposed for inferring the symmetry energy of super-dense neutron-rich nucleonic matter above twice the saturation density $\rho_0$ of nuclear matter directly from integrating iteratively barotropic pressures in both neutron stars and heavy-ion reactions. Simultaneously, the proton fraction of NSs at $\beta$ equilibrium is extracted as a function of baryon density from the same procedure. An application of this approach using the NS pressure from GW170817 and the pressure in cold symmetric nuclear matter (SNM) extracted earlier by analyzing nuclear collective flow data in relativistic heavy-ion collisions provides a useful constraining band for the symmetry energy above $2\rho_0$., Comment: More discussions and references added. Phys. Lett. B in press

The radius $R_{1.4}$ of neutron stars (NSs) with a mass of 1.4 M$_{\odot}$ has been extracted consistently in many recent studies in the literature. Using representative $R_{1.4}$ data, we infer high-density nuclear symmetry energy $E_{\rm{sym}}(\rho)$ and the associated nucleon specific energy $E_0(\rho)$ in symmetric nuclear matter (SNM) within a Bayesian statistical approach using an explicitly isospin-dependent parametric Equation of State (EOS) for nucleonic matter. We found that: (1) The available astrophysical data can already improve significantly our current knowledge about the EOS in the density range of $\rho_0-2.5\rho_0$. In particular, the symmetry energy at twice the saturation density $\rho_0$ of nuclear matter is determined to be $E_{\mathrm{sym}}(2\rho_0)$ =39.2$_{-8.2}^{+12.1}$ MeV at 68\% confidence level. (2) A precise measurement of the $R_{1.4}$ alone with a 4\% 1$\sigma$ statistical error but no systematic error will not improve much the constraints on the EOS of dense neutron-rich nucleonic matter compared to what we extracted from using the available radius data. (3) The $R_{1.4}$ radius data and other general conditions, such as the observed NS maximum mass and causality condition introduce strong correlations for the high-order EOS parameters. Consequently, the high-density behavior of $E_{\rm{sym}}(\rho)$ inferred depends strongly on how the high-density SNM EOS $E_0(\rho)$ is parameterized, and vice versa. (4) The value of the observed maximum NS mass and whether it is used as a sharp cut-off for the minimum maximum mass or through a Gaussian distribution affect significantly the lower boundaries of both the $E_0(\rho)$ and $E_{\rm{sym}}(\rho)$ only at densities higher than about $2.5\rho_0$., Comment: Discussions added. The Astrophysical Journal (2019) in press

User activity fluctuations reflect the performance of online society. We investigate the statistical properties of 1-min user activity time series of simultaneously online users inhabited in 95 independent virtual worlds. The number of online users exhibits clear intraday and weekly patterns due to human's circadian rhythms and week cycles. Statistical analysis shows that the distribution of absolute activity fluctuations has a power-law tail for 44 virtual worlds with an average tail exponent close to 2.15. The partition function approach unveils that the absolute activity fluctuations possess multifractal features for all the 95 virtual worlds. For the sample of 44 virtual worlds with power-law tailed distributions of the absolute activity fluctuations, the width of singularity $\Delta\alpha$ is negatively correlated with the maximum activity ($p$-value=0.070) and the time to the maximum activity ($p$-value=0.010). The negative correlations are not observed for neither the other 51 virtual worlds nor the whole sample of the 95 virtual worlds. In addition, numerical experiments indicate that both temporal structure and large fluctuations have influence on the multifractal spectrum. We also find that the temporal structure has stronger impact on the singularity width than large fluctuations., Comment: 9 pages including 8 figures

Complex network is not only a powerful tool for the analysis of complex system, but also a promising way to analyze time series. The algorithm of horizontal visibility graph (HVG) maps time series into graphs, whose degree distributions are numerically and analytically investigated for certain time series. We derive the degree distributions of HVGs through an iterative construction process of HVGs. The degree distributions of the HVG and the directed HVG for random series are derived to be exponential, which confirms the analytical results from other methods. We also obtained the analytical expressions of degree distributions of HVGs and in-degree and out-degree distributions of directed HVGs transformed from multifractal binomial measures, which agree excellently with numerical simulations., Comment: 7 pages, 4 figures

It is of great significance to identify the characteristics of time series to qualify their similarity. We define six types of triadic time-series motifs and investigate the motif occurrence profiles extracted from logistic map, chaotic logistic map, chaotic Henon map, chaotic Ikeda map, hyperchaotic generalized Henon map and hyperchaotic folded-tower map. Based on the similarity of motif profiles, we further propose to estimate the similarity coefficients between different time series and classify these time series with high accuracy. We further apply the motif analysis method to the UCR Time Series Classification Archive and provide evidence of good classification ability for some data sets. Our analysis shows that the proposed triadic time series motif analysis performs better than the classic dynamic time wrapping method in classifying time series for certain data sets investigated in this work., Comment: 10 pages, 6 figures

Network motif analysis is a useful tool for the investigation of complex networks. We study the profiles of tetradic motifs in horizontal visibility graphs (HVGs) converted from multifractal binomial measures, fractional Gaussian noises, and heartbeat rates. The profiles of tetradic motifs contains the spatial information (visibility) and temporal information (relative magnitude) among the data points in the corresponding time series. For multifractal binomial measures, the occurrence frequencies of the tetradic motifs are determined, which converge to a constant vector $(2/3,0,8/99,8/33,1/99,0)$. For fractional Gaussian noises, the motif occurrence frequencies are found to depend nonlinearly on the Hurst exponent and the length of time series. These findings suggest the potential ability of tetradic motif profiles in distinguishing different types of time series. Finally, we apply the tetradic motif analysis to heartbeat rates of healthy subjects, congestive heart failure (CHF) subjects, and atrial fibrillation (AF) subjects. Different subjects can be distinguished from the occurrence frequencies of tetradic motifs., Comment: 9 pages, 5 figures

The formation of the projectile spectator and the fragmentation processes in 107,124Sn + 120Sn collisions at 600 MeV/nucleon are studied with the isospin-dependent quantum molecular dynamics (IQMD) model. The minimum spanning tree algorithm and the ratio of parallel to transverse kinetic quantities are applied to identify the equilibrated projectile spectator during the dynamical evolution. The influence of secondary decay on fragmentation observables is investigated by performing calculations with and without the statistical code GEMINI. The validity of the theoretical approach is examined by comparing the calculated product yields and correlations with the experimental results of the ALADIN Collaboration for the studied reactions., Comment: 7 pages, 4 figures, contribution to the IWM-EC 2018 conference (Catania, Italy), to appear in the proceedings

We introduce the concept of time series motifs for time series analysis. Time series motifs consider not only the spatial information of mutual visibility but also the temporal information of relative magnitude between the data points. We study the profiles of the six triadic time series. The six motif occurrence frequencies are derived for uncorrelated time series, which are approximately linear functions of the length of the time series. The corresponding motif profile thus converges to a constant vector $(0.2,0.2,0.1,0.2,0.1,0.2)$. These analytical results have been verified by numerical simulations. For fractional Gaussian noises, numerical simulations unveil the nonlinear dependence of motif occurrence frequencies on the Hurst exponent. Applications of the time series motif analysis uncover that the motif occurrence frequency distributions are able to capture the different dynamics in the heartbeat rates of healthy subjects, congestive heart failure (CHF) subjects, and atrial fibrillation (AF) subjects and in the price fluctuations of bullish and bearish markets. Our method shows its potential power to classify different types of time series and test the time irreversibility of time series., Comment: 7 pages, 5 figures

Multifractality is ubiquitously observed in complex natural and socioeconomic systems. Multifractal analysis provides powerful tools to understand the complex nonlinear nature of time series in diverse fields. Inspired by its striking analogy with hydrodynamic turbulence, from which the idea of multifractality originated, multifractal analysis of financial markets has bloomed, forming one of the main directions of econophysics. We review the multifractal analysis methods and multifractal models adopted in or invented for financial time series and their subtle properties, which are applicable to time series in other disciplines. We survey the cumulating evidence for the presence of multifractality in financial time series in different markets and at different time periods and discuss the sources of multifractality. The usefulness of multifractal analysis in quantifying market inefficiency, in supporting risk management and in developing other applications is presented. We finally discuss open problems and further directions of multifractal analysis., Comment: A review paper contains 145 pages

In this paper, we investigate the cooling-off effect (opposite to the magnet effect) from two aspects. Firstly, from the viewpoint of dynamics, we study the existence of the cooling-off effect by following the dynamical evolution of some financial variables over a period of time before the stock price hits its limit. Secondly, from the probability perspective, we investigate, with the logit model, the existence of the cooling-off effect through analyzing the high-frequency data of all A-share common stocks traded on the Shanghai Stock Exchange and the Shenzhen Stock Exchange from 2000 to 2011 and inspecting the trading period from the opening phase prior to the moment that the stock price hits its limits. A comparison is made of the properties between up-limit hits and down-limit hits, and the possible difference will also be compared between bullish and bearish market state by dividing the whole period into three alternating bullish periods and three bearish periods. We find that the cooling-off effect emerges for both up-limit hits and down-limit hits, and the cooling-off effect of the down-limit hits is stronger than that of the up-limit hits. The difference of the cooling-off effect between bullish period and bearish period is quite modest. Moreover, we examine the sub-optimal orders effect, and infer that the professional individual investors and institutional investors play a positive role in the cooling-off effects. All these findings indicate that the price limit trading rule exerts a positive effect on maintaining the stability of the Chinese stock markets.

The availability of big data recorded from massively multiplayer online role-playing games (MMORPGs) allows us to gain a deeper understanding of the potential connection between individuals' network positions and their economic outputs. We use a statistical filtering method to construct dependence networks from weighted friendship networks of individuals. We investigate the 30 distinct motif positions in the 13 directed triadic motifs which represent microscopic dependences among individuals. Based on the structural similarity of motif positions, we further classify individuals into different groups. The node position diversity of individuals is found to be positively correlated with their economic outputs. We also find that the economic outputs of leaf nodes are significantly lower than that of the other nodes in the same motif. Our findings shed light on understanding the influence of network structure on economic activities and outputs in socioeconomic system., Comment: 19 pages, 5 figures

Traders in a stock market exchange stock shares and form a stock trading network. Trades at different positions of the stock trading network may contain different information. We construct stock trading networks based on the limit order book data and classify traders into $k$ classes using the $k$-shell decomposition method. We investigate the influences of trading behaviors on the price impact by comparing a closed national market (A-shares) with an international market (B-shares), individuals and institutions, partially filled and filled trades, buyer-initiated and seller-initiated trades, and trades at different positions of a trading network. Institutional traders professionally use some trading strategies to reduce the price impact and individuals at the same positions in the trading network have a higher price impact than institutions. We also find that trades in the core have higher price impacts than those in the peripheral shell., Comment: 6 pages including 3 figures and 1 table

Transport simulations are very valuable for extracting physics information from heavy-ion collision experiments. With the emergence of many different transport codes in recent years, it becomes important to estimate their robustness in extracting physics information from experiments. We report on the results of a transport code comparison project. 18 commonly used transport codes were included in this comparison: 9 Boltzmann-Uehling-Uhlenbeck-type codes and 9 Quantum-Molecular-Dynamics-type codes. These codes have been required to simulate Au+Au collisions using the same physics input for mean fields and for in-medium nucleon-nucleon cross sections, as well as the same initialization set-up, the impact parameter, and other calculational parameters at 100 and 400 AMeV incident energy. Among the codes we compare one-body observables such as rapidity and transverse flow distributions. We also monitor non-observables such as the initialization of the internal states of colliding nuclei and their stability, the collision rates and the Pauli blocking. We find that not completely identical initializations constitute partly for different evolutions. Different strategies to determine the collision probabilities, and to enforce the Pauli blocking, also produce considerably different results. There is a substantial spread in the predictions for the observables, which is much smaller at the higher incident energy. We quantify the uncertainties in the collective flow resulting from the simulation alone as about $30\%$ at 100 AMeV and $13\%$ at 400 AMeV, respectively. We propose further steps within the code comparison project to test the different aspects of transport simulations in a box calculation of infinite nuclear matter. This should, in particular, improve the robustness of transport model predictions at lower incident energies where abundant amounts of data are available., Comment: 26 pages, 13 figures, a manuscript on the heavy-ion collision part of transport code comparison project

We perform a comparative analysis of the Chinese stock market around the occurrence of the 2008 crisis based on the random matrix analysis of high-frequency stock returns of 1228 stocks listed on the Shanghai and Shenzhen stock exchanges. Both raw correlation matrix and partial correlation matrix with respect to the market index in two time periods of one year are investigated. We find that the Chinese stocks have stronger average correlation and partial correlation in 2008 than in 2007 and the average partial correlation is significantly weaker than the average correlation in each period. Accordingly, the largest eigenvalue of the correlation matrix is remarkably greater than that of the partial correlation matrix in each period. Moreover, each largest eigenvalue and its eigenvector reflect an evident market effect, while other deviating eigenvalues do not. We find no evidence that deviating eigenvalues contain industrial sectorial information. Surprisingly, the eigenvectors of the second largest eigenvalues in 2007 and of the third largest eigenvalues in 2008 are able to distinguish the stocks from the two exchanges. We also find that the component magnitudes of the some largest eigenvectors are proportional to the stocks' capitalizations., Comment: 6 pages including 5 figures

People in modern societies form different social networks through numerous means of communication. These communication networks reflect different aspects of human's societal structure. The billing records of calls among mobile phone users enable us to construct a directed calling network (DCN) and its Bonferroni network (SVDCN) in which the preferential communications are statistically validated. Here we perform a comparative investigation of the cliques of the original DCN and its SVDCN constructed from the calling records of more than nine million individuals in Shanghai over a period of 110 days. We find that the statistical properties of the cliques of the two calling networks are qualitatively similar and the clique members in the DCN and the SVDCN exhibit idiosyncratic behaviors quantitatively. Members in large cliques are found to be spatially close to each other. Based on the clique degree profile of each mobile phone user, the most active users in the two calling networks can be classified in to several groups. The users in different groups are found to have different calling behaviors. Our study unveils interesting communication behaviors among mobile phone users that are densely connected to each other., Comment: 18 pages, 10 figures

Many complex systems generate multifractal time series which are long-range cross-correlated. Numerous methods have been proposed to characterize the multifractal nature of these long-range cross correlations. However, several important issues about these methods are not well understood and most methods consider only one moment order. We study the joint multifractal analysis based on partition function with two moment orders, which was initially invented to investigate fluid fields, and derive analytically several important properties. We apply the method numerically to binomial measures with multifractal cross correlations and bivariate fractional Brownian motions without multifractal cross correlations. For binomial multifractal measures, the explicit expressions of mass function, singularity strength and multifractal spectrum of the cross correlations are derived, which agree excellently with the numerical results. We also apply the method to stock market indexes and unveil intriguing multifractality in the cross correlations of index volatilities., Comment: 19 pages, 5 figures

Dynamics of pseudoscalar mesons ($\pi$, $\eta$, $K$ and $\overline{K}$ ) and hyperons ($\Lambda$ and $\Sigma$) produced in heavy-ion collisions near threshold energies has been investigated within the Lanzhou quantum molecular dynamics (LQMD) transport model. The in-medium modifications on particle production in dense nuclear matter are implemented in the model through corrections on the elementary cross sections and by inclusion of the meson (hyperon)-nucleon potentials, in which the isospin effects are considered. It is found that the transportation of particles are influenced with the in-medium corrections. The total number of pions is reduced with an isospin, density and momentum dependent pion-nucleon potential. However, the ratios of charged pions is enhanced with inclusion of the potential. The production of eta in the domain of mid-rapidities and high momenta is sensitive to the $\eta$-nucleon potential, but weakly depends on symmetry energy. The attractive antikaon-nucleon potential enhances the subthreshold $\overline{K}$ production and also influences the structure of phase-space distributions. Dynamics of etas, kaons, antikaons and hyperons is also influenced by the pion potential because of collisions between pions and nucleons (resonances). The impacts of mean-field potentials on particle dynamics are investigated, such as the phase-space distributions from rapidity and transverse momentum spectra, inclusive invariant spectra, collective flows etc., Comment: 18 pages, 13 figures. arXiv admin note: text overlap with arXiv:1310.8072

Humans are heterogenous and the behaviors of individuals could be different from that at the population level. We conduct an in-depth study of the temporal patterns of cellphone conversation activities of 73'339 anonymous cellphone users with the same truncated Weibull distribution of inter-call durations. We find that the individual call events exhibit a pattern of bursts, in which high activity periods are alternated with low activity periods. Surprisingly, the number of events in high activity periods are found to conform to a power-law distribution at the population level, but follow an exponential distribution at the individual level, which is a hallmark of absence of memory in individual call activities. Such exponential distribution is also observed for the number of events in low activity periods. Together with the exponential distributions of inter-call durations within bursts and of the intervals between consecutive bursts, we demonstrate that the individual call activities are driven by two independent Poisson processes, which can be combined within a minimal model in terms of a two-state first-order Markov chain giving very good agreement with the empirical distributions using the parameters estimated from real data for about half of the individuals in our sample. By measuring directly the distributions of call rates across the population, which exhibit power-law tails, we explain the difference with previous population level studies, purporting the existence of power-law distributions, via the "Superposition of Distributions" mechanism: The superposition of many exponential distributions of activities with a power-law distribution of their characteristic scales leads to a power-law distribution of the activities at the population level., Comment: 16 pages, 7 figures

The latest global financial tsunami and its follow-up global economic recession has uncovered the crucial impact of housing markets on financial and economic systems. The Chinese stock market experienced a markedly fall during the global financial tsunami and China's economy has also slowed down by about 2\%-3\% when measured in GDP. Nevertheless, the housing markets in diverse Chinese cities seemed to continue the almost nonstop mania for more than ten years. However, the structure and dynamics of the Chinese housing market are less studied. Here we perform an extensive study of the Chinese housing market by analyzing ten representative key cities based on both linear and nonlinear econophysical and econometric methods. We identify a common collective driving force which accounts for 96.5\% of the house price growth, indicating very high systemic risk in the Chinese housing market. The ten key cities can be categorized into clubs and the house prices of the cities in the same club exhibit an evident convergence. These findings from different methods are basically consistent with each other. The identified city clubs are also consistent with the conventional classification of city tiers. The house prices of the first-tier cities grow the fastest, and those of the third- and fourth-tier cities rise the slowest, which illustrates the possible presence of a ripple effect in the diffusion of house prices in different cities., Comment: 16 Latex pages including 6 figures and 4 tables