arXiv subjects

Hong Shen

Publications and source records attributed to Hong Shen.

At least 163 records · Page 9Linked to original sources

arXiv2017

Single-$Ξ^-$ hypernuclei with quark mean field model

The single-$Ξ^-$ hypernuclei are studied using a quark mean field model. At the quark level, the $Ξ^-$ hyperon is composed of one $d$ quark and two $s$ quarks, which are confined by the harmonic oscillator potentials. In the case of hadrons, the baryons interact with each other by exchanging $σ, ~ω$, and $ρ$ mesons between quarks in different baryons. The single-$Ξ^-$ binding energies of $Ξ$ hypernuclei are investigated from $\ce{_{Ξ^{-}}^{12}Be}$ to $\ce{^{208}_{Ξ^-}Tl}$ using different parameter sets, which are determined by the ground-state properties of several stable nuclei and the empirical values of the single-$Λ$ and $Ξ$ potentials at the nuclear saturation density. For the bound states of $\ce{Ξ^{-}{+}^{14}N}$ (i.e., $\ce{^{15}_{Ξ^-}C}$) system named as KISO event in KEK-E373 experiment, it is found that the $Ξ^-$ binding energies are around $5.61-5.89$ MeV for $1s$ state and $0.94-1.21$ MeV for $1p$ state with QMF-NK1S, QMF-NK2S, and QMF-NK3S parameter sets, whose single $Ξ$ potentials are $-12$ MeV. These results and those from cluster models with the Gaussian expansion method concerning on the $\ce{Ξ^{-}{+}^{12}Be}$ show that in the KISO event, the $Ξ^-$ hyperon may occupy the $1p$ state. Furthermore, the $Ξ^-$ binding energies are achieved around $27$ MeV for the $\ce{Ξ^{-}{+}^{207}Pb}$ (i.e., $\ce{^{208}_{Ξ^-}Tl}$) system. The energies were nearly comparable to the single-$Λ$ binding energy of $\ce{^{208}_ΛPb}$ observed by experiments. It demonstrates that the $Λ$ and $Ξ^-$ hyperons seem to appear simultaneously in a neutron star.

nucl-th↗

arXiv2017

Finite-size effects on the hadron-quark phase transition in neutron stars

We study the finite-size effects, like the surface and Coulomb energies, on the hadron-quark mixed phase in neutron stars. The equilibrium conditions for coexisting hadronic and quark phases are derived by minimizing the total energy including the surface and Coulomb contributions, which are different from the Gibbs conditions without finite-size effects. We employ the relativistic mean-field model to describe the hadronic phase, while the Nambu-Jona-Lasinio model with vector interactions is used for the quark phase. It is found that finite-size effects can significantly reduce the region of the mixed phase, and the results lie between those of the Gibbs and Maxwell constructions. We show that a massive star may contain a mixed-phase core and its size depends on the surface tension of the hadron-quark interface and the vector coupling between quarks. The repulsive vector interaction in the Nambu-Jona-Lasinio model can stiffen the equation of state of quark matter, and therefore, delay the phase transition and increase the maximum mass of neutron stars.

nucl-th↗

arXiv2017

Point Sweep Coverage on Path

An important application of wireless sensor networks is the deployment of mobile sensors to periodically monitor (cover) a set of points of interest (PoIs). The problem of Point Sweep Coverage is to deploy fewest sensors to periodically cover the set of PoIs. For PoIs in a Eulerian graph, this problem is known NP-Hard even if all sensors are with uniform velocity. In this paper, we study the problem when PoIs are on a line and prove that the decision version of the problem is NP-Complete if the sensors are with different velocities. We first formulate the problem of Max-PoI sweep coverage on path (MPSCP) to find the maximum number of PoIs covered by a given set of sensors, and then show it is NP-Hard. We also extend it to the weighted case, Max-Weight sweep coverage on path (MWSCP) problem to maximum the sum of the weight of PoIs covered. For sensors with uniform velocity, we give a polynomial-time optimal solution to MWSCP. For sensors with constant kinds of velocities, we present a $\frac{1}{2}$-approximation algorithm. For the general case of arbitrary velocities, we propose two algorithms. One is a $\frac{1}{2α}$-approximation algorithm family scheme, where integer $α\ge2$ is the tradeoff factor to balance the time complexity and approximation ratio. The other is a $\frac{1}{2}(1-1/e)$-approximation algorithm by randomized analysis.

cs.DS↗

arXiv2017

Approximation Algorithms for Minimizing Maximum Sensor Movement for Line Barrier Coverage in the Plane

Given a line barrier and a set of mobile sensors distributed in the plane, the Minimizing Maximum Sensor Movement problem (MMSM) for \textcolor{black}{line barrier coverage} is to compute relocation positions for the sensors in the plane such that the barrier is entirely covered by the monitoring area of the sensors while the maximum relocation movement (distance) is minimized. Its weaker version, decision MMSM is to determine whether the barrier can be covered by the sensors within a given relocation distance bound $D\in\mathbb{Z}^{+}$. This paper presents three approximation algorithms for decision MMSM. The first is a simple greedy approach, which runs in time $O(n\log n)$ and achieves a maximum movement $D^{*}+2r_{max}$, where $n$ is the number of the sensors, $D^{*}$ is the maximum movement of an optimal solution and $r_{max}$ is the maximum radii of the sensors. The second and the third algorithms improve the maximum movement to $D^{*}+r_{max}$ , running in time $O(n^{7}L)$ and $O(R^{2}\sqrt{\frac{M}{\log R}})$ by applying linear programming (LP) rounding and maximal matching tchniques respecitvely, where $R=\sum2r_{i}$, which is $O(n)$ in practical scenarios of uniform sensing radius for all sensors, and $M\leq n\max r_{i}$. Applying the above algorithms for $O(\log(d_{max}))$ time in binary search immediately yields solutions to MMSM with the same performance guarantee. In addition, we also give a factor-2 approximation algorithm which can be used to improve the performance of the first three algorithms when $r_{max}>D^{*}$. As shown in \cite{dobrev2015complexity}, the 2-D MMSM problem admits no FPTAS as it is strongly NP-complete, so our algorithms arguably achieve the best possible ratio.

cs.DS↗

arXiv2017

Efficient Approximation Algorithms for Multi-Antennae Largest Weight Data Retrieval

In a mobile network, wireless data broadcast over $m$ channels (frequencies) is a powerful means for distributed dissemination of data to clients who access the channels through multi-antennae equipped on their mobile devices. The $δ$-antennae largest weight data retrieval ($δ$ALWDR) problem is to compute a schedule for downloading a subset of data items that has a maximum total weight using $δ$ antennae in a given time interval. In this paper, we propose a ratio $1-\frac{1}{e}-ε$ approximation algorithm for the $δ$-antennae largest weight data retrieval ($δ$ALWDR) problem that has the same ratio as the known result but a significantly improved time complexity of $O(2^{\frac{1}ε}\frac{1}εm^{7}T^{3.5}L)$ from $O(ε^{3.5}m^{\frac{3.5}ε}T^{3.5}L)$ when $δ=1$ \cite{lu2014data}. To our knowledge, our algorithm represents the first ratio $1-\frac{1}{e}-ε$ approximation solution to $δ$ALWDR for the general case of arbitrary $δ$. To achieve this, we first give a ratio $1-\frac{1}{e}$ algorithm for the $γ$-separated $δ$ALWDR ($δ$A$γ$LWDR) with runtime $O(m^{7}T^{3.5}L)$, under the assumption that every data item appears at most once in each segment of $δ$A$γ$LWDR, for any input of maximum length $L$ on $m$ channels in $T$ time slots. Then, we show that we can retain the same ratio for $δ$A$γ$LWDR without this assumption at the cost of increased time complexity to $O(2^γm^{7}T^{3.5}L)$. This result immediately yields an approximation solution of same ratio and time complexity for $δ$ALWDR, presenting a significant improvement of the known time complexity of ratio $1-\frac{1}{e}-ε$ approximation to the problem.

cs.DS↗

arXiv2017

Quark mean field model with pion and gluon corrections for $Λ,~Ξ^0$ hypernuclei and neutron stars

Properties of $Λ,~Ξ^0$ hypernuclei and neutron stars are investigated in quark mean field model with pion and gluon corrections. Firstly, $u, ~d$, and $s$ quarks are confined by relativistic harmonic oscillator potentials to generate the baryons, like nucleon, $Λ, ~Σ$, and $Ξ$ hyperons. The effects of pion-quark coupling and one-gluon exchange are considered perturbatively. Then, the baryons interact with each other through exchanging $σ, ~ω,$ and $ρ$ mesons between quarks in hypernuclei and nuclear matter. The strengths of confinement potentials for $u, ~d,$ and $s$ quarks are determined by the masses and radii of free baryons. The coupling constants between the quarks and mesons are fixed by the ground-state properties of several nuclei and single-hyperon potentials at nuclear saturation density, which arises three parameter sets for the coupling constants between mesons and quarks, named QMF-NK1S, QMF-NK2S, and QMF-NK3S. Compared to the results of previous quark mean field model without pion and gluon corrections, it is found that properties of $Λ$ hypernuclei, i.e. the single $Λ$ energies, are more consistent with the experimental observables. Properties of $Ξ^0$ hypernuclei are also calculated and compared with the results in previous quark mean field model. With these three parameter sets, the neutron stars containing hyperons are investigated through solving the Tolman-Oppenheimer-Volkoff equation. Maximum masses of neutron stars approach $2.1M_\odot$ with hyperons and corresponding radii are around $13$ km.

nucl-th↗

arXiv2017

Neutron stars within relativistic central variational method

The properties of neutron stars are investigated within the relativistic central variational method by using a realistic nucleon-nucleon ($NN$) interaction. The strong repulsion of realistic $NN$ interactions at short distances is treated by a Jastrow central correlation function, whose form is completely determined through minimization of the total energy of the nuclear many-body system. The relativistic Hartree-Fock wave functions are chosen as the trial wave function. In this framework, the equation of state of the neutron star matter in $β$ equilibrium is obtained self-consistently. We further determine the properties of neutron stars via the Tolman-Oppenheimer-Volkoff equation using Bonn A, B, and C potentials. The maximum masses of neutron stars with these realistic potentials are around $2.18 M_\odot$ and their corresponding radii are around $11$ km. These results are in accordance with the calculations of the relativistic Brueckner-Hartree-Fock theory with the same potentials. Furthermore, we also find that the splitting of proton-neutron effective masses will be reversed at high density in the neutron star matter, which are caused by the contribution of short-range correlation on kinetic energy.

nucl-th↗

arXiv2016

The phase transition in hot $Λ$ hypernuclei within relativistic Thomas-Fermi approximation

A self-consistent description for hot $Λ$ hypernuclei in hypothetical big boxes is developed within the relativistic Thomas-Fermi approximation in order to investigate directly the liquid-gas phase coexistence in strangeness finite nuclear systems. We use the relativistic mean-field model for nuclear interactions. The temperature dependence of $Λ$ hyperon density, $Λ$ hyperon radius, excitation energies, specific heat, and the binding energies of $Λ$ hypernuclei from $^{16}_Λ$O to $^{208}_Λ$Pb in phase transition region are calculated by using the subtraction procedure in order to separate the hypernucleus from the surrounding baryon gas. The $Λ$ central density is very sensitive to the temperature. The radii of $Λ$ hyperon at high temperature become very large. In the relativistic Thomas-Fermi approximation with the subtraction procedure, the properties of hypernuclei are independent of the size of the box in which the calculation is performed. The level density parameters of hypernuclei in the present work are confirmed to be almost constant at low temperature. It is also found that the single-$Λ$ binding energies of $Λ$ hypernuclei are largely reduced with increasing temperature.

nucl-th↗

arXiv2016

The properties of nuclear matter with lattice $NN$ potential in relativistic Brueckner-Hartree-Fock theory

We study the properties of nuclear matter with lattice nucleon-nucleon ($NN$) potential in the relativistic Brueckner-Hartree-Fock (RBHF) theory. To use this potential in such a microscopic many-body theory, we firstly have to construct a one-boson-exchange potential (OBEP) based on the latest lattice $NN$ potential. Three mesons, pion, $σ$ meson, and $ω$ meson, are considered. Their coupling constants and cut-off momenta are determined by fitting the on-shell behaviors and phase shifts of the lattice force, respectively. Therefore, we obtain two parameter sets of the OBEP potential (named as LOBEP1 and LOBEP2) with these two fitting ways. We calculate the properties of symmetric and pure neutron matter with LOBEP1 and LOBEP2. In non-relativistic Brueckner-Hartree-Fock case, the binding energies of symmetric nuclear matter are around $-3$ and $-5$ MeV at saturation densities, while it becomes $-8$ and $-12$ MeV in relativistic framework with $^1S_0,~^3S_1,$ and $^3D_1$ channels using our two parameter sets. For the pure neutron matter, the equations of state in non-relativistic and relativistic cases are very similar due to only consideration $^1S_0$ channel with isospin $T=1$ case.

nucl-th↗

arXiv2016

The quark mean field model with pion and gluon corrections

The properties of nuclear matter and finite nuclei are studied within the quark mean field (QMF) model by taking the effects of pion and gluon into account at the quark level. The nucleon is described as the combination of three constituent quarks confined by a harmonic oscillator potential. To satisfy the spirit of QCD theory, the contributions of pion and gluon on the nucleon structure are treated in second-order perturbation theory. For the nuclear many-body system, nucleons interact with each other by exchanging mesons between quarks. With different constituent quark mass, $m_q$, we determine three parameter sets about the coupling constants between mesons and quarks, named as QMF-NK1, QMF-NK2, and QMF-NK3 by fitting the ground-state properties of several closed-shell nuclei. It is found that all of the three parameter sets can give satisfactory description on properties of nuclear matter and finite nuclei, meanwhile they can also predict the larger neutron star mass around $2.3M_\odot$ without the hyperon degrees of freedom.

nucl-th↗

arXiv2016

Diversified Top-k Similarity Search in Large Attributed Networks

Given a large network and a query node, finding its top-k similar nodes is a primitive operation in many graph-based applications. Recently enhancing search results with diversification have received much attention. In this paper, we explore an novel problem of searching for top-k diversified similar nodes in attributed networks, with the motivation that modeling diversification in an attributed network should consider both the emergence of network links and the attribute features of nodes such as user profile information. We formulate this practical problem as two optimization problems: the Attributed Coverage Diversification (ACD) problem and the r-Dissimilar Attributed Coverage Diversification (r-DACD) problem. Based on the submodularity and the monotonicity of ACD, we propose an efficient greedy algorithm achieving a tight approximation guarantee of 1-1/e. Unlike the expension based methods only considering nodes' neighborhood, ACD generalize the definition of diversification to nodes' own features. To capture diversification in topological structure of networks, the r-DACD problem introduce a dissimilarity constraint. We refer to this problem as the Dissimilarity Constrained Non-monotone Submodular Maximization (DCNSM) problem. We prove that there is no constant-factor approximation for DCNSM, and also present an efficient greedy algorithms achieving $1/ρ$ approximation, where $ρ\leΔ$, $Δ$ is the maximum degree of its dissimilarity based graph. To the best of our knowledge, it is the first approximation algorithm for the Submodular Maximization problem with a distance constraint. The experimental results on real-world attributed network datasets demonstrate the effectiveness of our methods, and confirm that adding dissimilarity constraint can significantly enhance the performance of diversification.

cs.IR↗

arXiv2015

A Complete Equation of State for Astrophysical Simulations

We construct a complete equation of state (EOS) covering a wide range of temperature, proton fraction, and baryon density for the use of astrophysical simulations. We employ the relativistic mean-field (RMF) theory to describe nuclear interactions and adopt the Thomas-Fermi approximation to describe the nonuniform nuclear matter. The uniform matter and nonuniform matter are studied consistently using the same RMF theory.

nucl-th↗

arXiv2015

Impacts of the Nuclear Symmetry Energy on Neutron Star Crusts

Using the relativistic mean-field theory, we adopt two different methods, namely, the coexisting phase method and the self-consistent Thomas-Fermi approximation, to study the impacts of the nuclear symmetry energy on properties of neutron star crusts within a wide range of densities. It is found that the nuclear symmetry energy and its density slope play an important role in determining the pasta phases and the crust-core transition.

nucl-th↗

arXiv2015

Self-consistent Thomas-Fermi Approximation for Equation of State at Subnuclear Densities

The self-consistent Thomas-Fermi approximation is an essential method for studying the non-uniform nuclear matter with relativistic mean-field theory. In this method, the nucleon distribution in the Wigner-Seitz cell is obtained self-consistently. We make a detailed comparison between the present results and previous calculations in the Thomas-Fermi approximation with a parameterized nucleon distribution that has been adopted in the widely used Shen equation of state.

nucl-th↗

arXiv2015

Ultrasensitive and broadband MoS2 photodetector driven by ferroelectrics

Photodetectors based on two dimensional materials have attracted growing interest. However, the sensitivity is still unsatisfactory even under high gate voltage. Here we demonstrate a MoS2 photodetector with a poly(vinylidene fluoride-trifluoroethylene) ferroelectric layer in place of the oxide layer in a traditional field effect transistor. The dark current of the photodetector is strongly suppressed by ferroelectric polarization. A high detectivity 2.21012 Jones) and photoresponsitivity (2570 A W) detector has been achieved under ZERO gate bias at a wavelength of 635 nm. Most strikingly, the band gap of few-layer MoS2 can be tuned by the ultra-high electrostatic field from the ferroelectric polarization. With this characteristic, photoresponse wavelengths of the photodetector are extended into the near infrared (0.85-1.55m). A ferroelectrics optoelectronics hybrid structure is an effective way to achieve high performance 2D electronic optoelectronic devices.

cond-mat.mes-hall↗

arXiv2015

An Accuracy-Assured Privacy-Preserving Recommender System for Internet Commerce

Recommender systems, tool for predicting users' potential preferences by computing history data and users' interests, show an increasing importance in various Internet applications such as online shopping. As a well-known recommendation method, neighbourhood-based collaborative filtering has attracted considerable attention recently. The risk of revealing users' private information during the process of filtering has attracted noticeable research interests. Among the current solutions, the probabilistic techniques have shown a powerful privacy preserving effect. When facing $k$ Nearest Neighbour attack, all the existing methods provide no data utility guarantee, for the introduction of global randomness. In this paper, to overcome the problem of recommendation accuracy loss, we propose a novel approach, Partitioned Probabilistic Neighbour Selection, to ensure a required prediction accuracy while maintaining high security against $k$NN attack. We define the sum of $k$ neighbours' similarity as the accuracy metric alpha, the number of user partitions, across which we select the $k$ neighbours, as the security metric beta. We generalise the $k$ Nearest Neighbour attack to beta k Nearest Neighbours attack. Differing from the existing approach that selects neighbours across the entire candidate list randomly, our method selects neighbours from each exclusive partition of size $k$ with a decreasing probability. Theoretical and experimental analysis show that to provide an accuracy-assured recommendation, our Partitioned Probabilistic Neighbour Selection method yields a better trade-off between the recommendation accuracy and system security.

cs.CR↗

arXiv2015

A Security-assured Accuracy-maximised Privacy Preserving Collaborative Filtering Recommendation Algorithm

The neighbourhood-based Collaborative Filtering is a widely used method in recommender systems. However, the risks of revealing customers' privacy during the process of filtering have attracted noticeable public concern recently. Specifically, $k$NN attack discloses the target user's sensitive information by creating $k$ fake nearest neighbours by non-sensitive information. Among the current solutions against $k$NN attack, the probabilistic methods showed a powerful privacy preserving effect. However, the existing probabilistic methods neither guarantee enough prediction accuracy due to the global randomness, nor provide assured security enforcement against $k$NN attack. To overcome the problems of current probabilistic methods, we propose a novel approach, Partitioned Probabilistic Neighbour Selection, to ensure a required security guarantee while achieving the optimal prediction accuracy against $k$NN attack. In this paper, we define the sum of $k$ neighbours' similarity as the accuracy metric $α$, the number of user partitions, across which we select the $k$ neighbours, as the security metric $β$. Differing from the present methods that globally selected neighbours, our method selects neighbours from each group with exponential differential privacy to decrease the magnitude of noise. Theoretical and experimental analysis show that to achieve the same security guarantee against $k$NN attack, our approach ensures the optimal prediction accuracy.

cs.CR↗

arXiv2015

A Faster Algorithm to Build New Users Similarity List in Neighbourhood-based Collaborative Filtering

Neighbourhood-based Collaborative Filtering (CF) has been applied in the industry for several decades, because of the easy implementation and high recommendation accuracy. As the core of neighbourhood-based CF, the task of dynamically maintaining users' similarity list is challenged by cold-start problem and scalability problem. Recently, several methods are presented on solving the two problems. However, these methods applied an $O(n^2)$ algorithm to compute the similarity list in a special case, where the new users, with enough recommendation data, have the same rating list. To address the problem of large computational cost caused by the special case, we design a faster ($O(\frac{1}{125}n^2)$) algorithm, TwinSearch Algorithm, to avoid computing and sorting the similarity list for the new users repeatedly to save the computational resources. Both theoretical and experimental results show that the TwinSearch Algorithm achieves better running time than the traditional method.

cs.IR↗