arXiv subjects

Jun Xu

Publications and source records attributed to Jun Xu.

At least 469 records · Page 26Linked to original sources

arXiv2016

Equations of motion of test particles for solving the spin-dependent Boltzmann-Vlasov equation

A consistent derivation of the equations of motion (EOMs) of test particles for solving the spin-dependent Boltzmann-Vlasov equation is presented. The resulting EOMs in phase space are similar to the canonical equations in Hamiltonian dynamics, and the EOM of spin is the same as that in the Heisenburg picture of quantum mechanics. Considering further the quantum nature of spin and choosing the direction of total angular momentum in heavy-ion reactions as a reference of measuring nucleon spin, the EOMs of spin-up and spin-down nucleons are given separately. The key elements affecting the spin dynamics in heavy-ion collisions are identified. The resulting EOMs provide a solid foundation for using the test-particle approach in studying spin dynamics in heavy-ion collisions at intermediate energies. Future comparisons of model simulations with experimental data will help constrain the poorly known in-medium nucleon spin-orbit coupling relevant for understanding properties of rare isotopes and their astrophysical impacts.

nucl-th↗

arXiv2016

Incorporating Semantic Knowledge into Latent Matching Model in Search

The relevance between a query and a document in search can be represented as matching degree between the two objects. Latent space models have been proven to be effective for the task, which are often trained with click-through data. One technical challenge with the approach is that it is hard to train a model for tail queries and tail documents for which there are not enough clicks. In this paper, we propose to address the challenge by learning a latent matching model, using not only click-through data but also semantic knowledge. The semantic knowledge can be categories of queries and documents as well as synonyms of words, manually or automatically created. Specifically, we incorporate semantic knowledge into the objective function by including regularization terms. We develop two methods to solve the learning task on the basis of coordinate descent and gradient descent respectively, which can be employed in different settings. Experimental results on two datasets from an app search engine demonstrate that our model can make effective use of semantic knowledge, and thus can significantly enhance the accuracies of latent matching models, particularly for tail queries.

cs.IR↗

arXiv2016

Match-SRNN: Modeling the Recursive Matching Structure with Spatial RNN

Semantic matching, which aims to determine the matching degree between two texts, is a fundamental problem for many NLP applications. Recently, deep learning approach has been applied to this problem and significant improvements have been achieved. In this paper, we propose to view the generation of the global interaction between two texts as a recursive process: i.e. the interaction of two texts at each position is a composition of the interactions between their prefixes as well as the word level interaction at the current position. Based on this idea, we propose a novel deep architecture, namely Match-SRNN, to model the recursive matching structure. Firstly, a tensor is constructed to capture the word level interactions. Then a spatial RNN is applied to integrate the local interactions recursively, with importance determined by four types of gates. Finally, the matching score is calculated based on the global interaction. We show that, after degenerated to the exact matching scenario, Match-SRNN can approximate the dynamic programming process of longest common subsequence. Thus, there exists a clear interpretation for Match-SRNN. Our experiments on two semantic matching tasks showed the effectiveness of Match-SRNN, and its ability of visualizing the learned matching structure.

cs.CL↗

arXiv2016

Understanding transport simulations of heavy-ion collisions at 100 and 400 AMeV: Comparison of heavy ion transport codes under controlled conditions

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.

nucl-th↗

arXiv2016

Semantic Regularities in Document Representations

Recent work exhibited that distributed word representations are good at capturing linguistic regularities in language. This allows vector-oriented reasoning based on simple linear algebra between words. Since many different methods have been proposed for learning document representations, it is natural to ask whether there is also linear structure in these learned representations to allow similar reasoning at document level. To answer this question, we design a new document analogy task for testing the semantic regularities in document representations, and conduct empirical evaluations over several state-of-the-art document representation models. The results reveal that neural embedding based document representations work better on this analogy task than conventional methods, and we provide some preliminary explanations over these observations.

cs.CL↗

arXiv2016

Kibble-Zurek dynamics in an array of coupled binary Bose condensates

Universal dynamics of spontaneous symmetry breaking is central to understanding the universal behavior of spontaneous defect formation in various system from the early universe, condensed-matter systems to ultracold atomic systems. We explore the universal real-time dynamics in an array of coupled binary atomic Bose-Einstein condensates in optical lattices, which undergo a spontaneous symmetry breaking from the symmetric Rabi oscillation to the broken-symmetry self-trapping. In addition to Goldstone modes, there exist gapped Higgs mode whose excitation gap vanishes at the critical point. In the slow passage through the critical point, we analytically find that the symmetry-breaking dynamics obeys the Kibble-Zurek mechanism. From the scalings of bifurcation delay and domain formation, we numerically extract two Kibble-Zurek exponents $b_{1}=ν/(1+νz)$ and $b_{2}=1/(1+νz)$, which give the static correlation-length critical exponent $ν$ and the dynamic critical exponent $z$. Our approach provides an efficient way to simultaneous determination of the critical exponents $ν$ and $z$ for a continuous phase transition.

cond-mat.quant-gas↗

arXiv2016

Text Matching as Image Recognition

Matching two texts is a fundamental problem in many natural language processing tasks. An effective way is to extract meaningful matching patterns from words, phrases, and sentences to produce the matching score. Inspired by the success of convolutional neural network in image recognition, where neurons can capture many complicated patterns based on the extracted elementary visual patterns such as oriented edges and corners, we propose to model text matching as the problem of image recognition. Firstly, a matching matrix whose entries represent the similarities between words is constructed and viewed as an image. Then a convolutional neural network is utilized to capture rich matching patterns in a layer-by-layer way. We show that by resembling the compositional hierarchies of patterns in image recognition, our model can successfully identify salient signals such as n-gram and n-term matchings. Experimental results demonstrate its superiority against the baselines.

cs.CL↗

arXiv2015

A Deep Architecture for Semantic Matching with Multiple Positional Sentence Representations

Matching natural language sentences is central for many applications such as information retrieval and question answering. Existing deep models rely on a single sentence representation or multiple granularity representations for matching. However, such methods cannot well capture the contextualized local information in the matching process. To tackle this problem, we present a new deep architecture to match two sentences with multiple positional sentence representations. Specifically, each positional sentence representation is a sentence representation at this position, generated by a bidirectional long short term memory (Bi-LSTM). The matching score is finally produced by aggregating interactions between these different positional sentence representations, through $k$-Max pooling and a multi-layer perceptron. Our model has several advantages: (1) By using Bi-LSTM, rich context of the whole sentence is leveraged to capture the contextualized local information in each positional sentence representation; (2) By matching with multiple positional sentence representations, it is flexible to aggregate different important contextualized local information in a sentence to support the matching; (3) Experiments on different tasks such as question answering and sentence completion demonstrate the superiority of our model.

cs.AI↗

arXiv2015

Investigating the scaling of higher-order flows in relativistic heavy-ion collisions

The modified number of constituent quark (NCQ) scaling $v_{n}/n_{q}^{n/2} \sim KE_{T}/n_{q}$ for mesons and baryons and the scaling relation $v_{n} \sim v_{2}^{n/2}$ for higher-order anisotropic flows, which were observed experimentally, have been investigated at top RHIC energy. It has been found that the modified NCQ scaling can not be obtained from the naive coalescence even by taking into account event-by-event fluctuations but may be due to hadronic afterburner or thermal freeze-out. In addition, we observed that the behavior of the $v_{n}/v_{2}^{n/2}$ ratio is sensitive to the partonic interaction, and it is different for mesons and baryons from the naive coalescence but is expected to be almost the same experimentally.

nucl-th↗

arXiv2015

Data Allocation in a Heterogeneous Disk Array - HDA with Multiple RAID Levels for Database Applications

We consider the allocation of Virtual Arrays (VAs) in a Heterogeneous Disk Array (HDA). Each VA holds groups of related objects and datasets such as files, relational tables, which has similar performance and availability characteristics. We evaluate single-pass data allocation methods for HDA using a synthetic stream of allocation requests, where each VA is characterized by its RAID level, disk loads and space requirements. The goal is to maximize the number of allocated VAs and maintain high disk bandwidth and capacity utilization, while balancing disk loads. Although only RAID1 (basic mirroring) and RAID5 (rotated parity arrays) are considered in the experimental study, we develop the analysis required to estimate disk loads for other RAID levels. Since VA loads vary significantly over time, the VA allocation is carried out at the peak load period, while ensuring that disk bandwidth is not exceeded at other high load periods. Experimental results with a synthetic stream of allocation requests show that allocation methods minimizing the maximum disk bandwidth and capacity utilization or their variance across all disks yield the maximum number of allocated VAs. HDA saves disk bandwidth, since a single RAID level accommodating the most stringent availability requirements for a small subset of objects would incur an unnecessarily high overhead for updating check blocks or data replicas for all objects. The number of allocated VAs can be increased by adopting the clustered RAID5 paradigm, which exploits the tradeoff between redundancy and bandwidth utilization. Since rebuild can be carried out at the level of individual VAs, prioritizing rebuild of VAs with higher access rates can improve overall performance.

cs.DC↗

arXiv2015

Dynamical effects of spin-dependent interactions in low- and intermediate-energy heavy-ion reactions

It is well known that non-central nuclear forces, such as the spin-orbital coupling and the tensor force, play important roles in understanding many interesting features of nuclear structures. However, their dynamical effects in nuclear reactions are poorly known since only the spin-averaged observables are normally studied both experimentally and theoretically. Realizing that spin-sensitive observables in nuclear reactions may carry useful information about the in-medium properties of non-central nuclear interactions, besides earlier studies using the time-dependent Hartree-Fock approach to understand effects of spin-orbital coupling on the threshold energy and spin polarization in fusion reactions, some efforts have been made recently to explore dynamical effects of non-central nuclear forces in intermediate-energy heavy-ion collisions using transport models. The focuses of these studies have been on investigating signatures of the density and isospin dependence of the form factor in the spin-dependent single-nucleon potential. Interestingly, some useful probes were identified in the model studies while so far there is still no data to compare with. In this brief review, we summarize the main physics motivations as well as the recent progress in understanding the spin dynamics and identifying spin-sensitive observables in heavy-ion reactions at intermediate energies. We hope the interesting, important, and new physics potentials identified in the spin dynamics of heavy-ion collisions will stimulate more experimental work in this direction.

nucl-th↗

arXiv2015

Mean-field potential effects on particle and antiparticle elliptic flows in the beam-energy scan program at RHIC

The elliptic flow splitting between particles and their antiparticles has recently been observed by the STAR Collaboration in the beam-energy scan program at the Relativistic Heavy Ion Collider. In studies based on transport models, we have found that this splitting can be explained by the different mean-field potentials acting on particles and their antiparticles in the produced baryon-rich matter. In particular, we have shown that the experimentally measured relative elliptic flow difference can help constrain the vector coupling constant in the Nambu-Jona-Lasinio model used in describing the partonic stage of heavy-ion collisions. This information is useful for locating the critical point in the QCD phase diagram and thus understanding the phase structure of QCD.

nucl-th↗

arXiv2015

Instantly Obsoleting the Address-code Associations: A New Principle for Defending Advanced Code Reuse Attack

Fine-grained Address Space Randomization has been considered as an effective protection against code reuse attacks such as ROP/JOP. However, it only employs a one-time randomization, and such a limitation has been exploited by recent just-in-time ROP and side channel ROP, which collect gadgets on-the-fly and dynamically compile them for malicious purposes. To defeat these advanced code reuse attacks, we propose a new defense principle: instantly obsoleting the address-code associations. We have initialized this principle with a novel technique called virtual space page table remapping and implemented the technique in a system CHAMELEON. CHAMELEON periodically re-randomizes the locations of code pages on-the-fly. A set of techniques are proposed to achieve our goal, including iterative instrumentation that instruments a to-be-protected binary program to generate a re-randomization compatible binary, runtime virtual page shuffling, and function reordering and instruction rearranging optimizations. We have tested CHAMELEON with over a hundred binary programs. Our experiments show that CHAMELEON can defeat all of our tested exploits by both preventing the exploit from gathering sufficient gadgets, and blocking the gadgets execution. Regarding the interval of our re-randomization, it is a parameter and can be set as short as 100ms, 10ms or 1ms. The experiment results show that CHAMELEON introduces on average 11.1%, 12.1% and 12.9% performance overhead for these parameters, respectively.

cs.CR↗

arXiv2015

Cluster Gutzwiller study of Bose-Hubbard ladder: ground-state phase diagram and many-body Landau-Zener dynamics

We present a cluster Gutzwiller mean-field study for ground states and time-evolution dynamics in the Bose-Hubbard ladder (BHL), which can be realized by loading Bose atoms in double-well optical lattices. In our cluster mean-field approach, we treat each double-well unit of two lattice sites as a coherent whole for composing the cluster Gutzwiller ansatz, which may remain some residual correlations in each two-site unit. For a unbiased BHL, in addition to conventional superfluid phase and integer Mott insulator phases, we find that there are exotic fractional insulator phases if the inter-chain tunneling is much stronger than the intra-chain one. The fractional insulator phases can not be found by using a conventional mean-field treatment based upon the single-site Gutzwiller ansatz. For a biased BHL, we find there appear single-atom tunneling and interaction blockade if the system is dominated by the interplay between the on-site interaction and the inter-chain bias. In the many-body Landau-Zener process, in which the inter-chain bias is linearly swept from negative to positive or vice versa, our numerical results are qualitatively consistent with the experimental observation [Nat. Phys. \textbf{7}, 61 (2011)]. Our cluster bosonic Gutzwiller treatment is of promising perspectives in exploring exotic quantum phases and time-evolution dynamics of bosonic particles in superlattices.

cond-mat.quant-gas↗

arXiv2015

Extraordinary focusing of sound above a soda can array without time reversal

Recently, Lemoult et al. [Phys. Rev. Lett. 107, 064301 (2011)] used time reversal to focus sound above an array of soda cans into a spot much smaller than the acoustic wavelength in air. In this study, we show that equally sharp focusing can be achieved without time reversal, by arranging transducers around a nearly circular array of soda cans. The size of the focal spot at the center of the array is made progressively smaller as the frequency approaches the Helmholtz resonance frequency of a can from below, and, near the resonance, becomes smaller than the size of a single can. We show that the locally resonant metamaterial formed by soda cans supports a guided wave at frequencies below the Helmholtz resonance frequency. The small focal spot results from a small wavelength of this guided wave near the resonance in combination with a near field effect making the acoustic field concentrate at the opening of a can. The focusing is achieved with propagating rather than evanescent waves. No sub-diffraction-limited focusing is observed if the diffraction limit is defined with respect to the wavelength of the guided mode in the metamaterial medium rather than the wavelength of the bulk wave in air.

physics.class-ph↗

arXiv2015

Revisit of the neutron/proton ratio puzzle in intermediate-energy heavy-ion collisions

Incorporating a newly improved isospin- and momentum-dependent interaction in the isospin-dependent Boltzmann-Uehling-Uhlenbeck transport model IBUU11, we have investigated relative effects of the density dependence of nuclear symmetry energy $E_{sym}(ρ)$ and the neutron-proton effective mass splitting $m^*_n-m^*_p$ on the neutron/proton ratio of free nucleons and those in light clusters. It is found that the $m^*_n-m^*_p$ has a relatively stronger effect than the $E_{sym}(ρ)$ and the assumption of $m^*_n\leq m^*_p$ leads to a higher neutron/proton ratio. Moreover, this finding is independent of the in-medium nucleon-nucleon cross sections used. However, results of our calculations using the $E_{sym}(ρ)$ and $m^*_n-m^*_p$ both within their current uncertainty ranges are all too low compared to the recent NSCL/MSU double neutron/proton ratio data from central $^{124}$Sn+$^{124}$Sn and $^{112}$Sn+$^{112}$Sn collisions at 50 and 120 MeV/u, thus calling for new mechanisms to explain the puzzlingly high neutron/proton ratio observed in the experiments.

nucl-th↗

arXiv2015

Isospin splitting of nucleon effective mass and shear viscosity of nuclear matter

Based on an improved isospin- and momentum-dependent interaction, we have studied the qualitative effect of isospin splitting of nucleon effective mass on the specific shear viscosity of neutron-rich nuclear matter from a relaxation time approach. It is seen that for $m_n^\star>m_p^\star$, the relaxation time of neutrons is smaller and the neutron flux between flow layers is weaker, leading to a smaller specific shear viscosity of neutron-rich matter compared to the case for $m_n^\star<m_p^\star$. The effect is larger in nuclear matter at higher densities, lower temperatures, and larger isospin asymmetries, but it doesn't affect much the behavior of the specific shear viscosity near nuclear liquid-gas phase transition.

nucl-th↗

arXiv2015

Influence of neutron-skin thickness on $π^{-}/π^{+}$ ratio in Pb+Pb collisions

Within an isospin- and momentum-dependent transport model IBUU11 using as an input nucleon density profiles from Hartree-Fock calculations based on a modified Skyrme-like (MSL) model, we study the influence of the uncertainty of the neutron skin thickness on the $π^{-}/π^{+}$ ratio in both central and peripheral Pb+Pb collisions at beam energies of 400 MeV/nucleon and 1000 MeV/nucleon. Within the current experimental uncertainty range of neutron skin in $^{208}$Pb, while the neutron skin effect on the \rpi ratio is negligible in central reactions at both energies, it increases gradually with increasing impact parameter and becomes comparable with or even larger than the symmetry energy effect in peripheral collisions especially at 400 MeV/nucleon. Moreover, we found that while the \rpi ratio is larger with a softer \esym in central collisions, above certain impact parameters depending on the size of the neutron skin, a stiffer \esym can lead to a larger \rpi ratio as most of the pions are produced at densities below the saturation density in these peripheral reactions. Thus, a clear impact parameter selection is important to extract reliable information about the \esym at suprasaturation densities (size of neutron skin) from the $π^-/π^+$ ratio in central (peripheral) heavy-ion collisions.

nucl-th↗