arXiv subjects

Jun Xu

Publications and source records attributed to Jun Xu.

At least 397 records · Page 22Linked to original sources

arXiv2019

Examining the Casimir puzzle with upgraded technique and advanced surface cleaning

We performed measurements of the gradient of the Casimir force between Au-coated surfaces of a sphere and a plate by means of significantly upgraded dynamic atomic force microscope (AFM) based technique. By introducing combined cleaning procedure of interior surfaces of the vacuum chamber and the test bodies by means of UV light and Ar ions, we reached higher vacuum and eliminated the role of electrostatic patches. Furthermore, the use of much softer cantilever allowed a sixfold decrease of the systematic error in measuring the force gradient. The experimental data are compared with theoretical predictions of the Lifshitz theory taking into account corrections due to the inaccuracy of the proximity force approximation and that due to surface roughness. It is shown that the theoretical approach accounting for the relaxation properties of free electrons is excluded by the data up to a larger than previous sphere-plate separation of 820~nm, whereas an alternative approach is found in a very good agreement with the data. Importance of these results in connection with the foundations of quantum statistical physics is discussed.

cond-mat.mes-hall↗

arXiv2019

DeepRank: A New Deep Architecture for Relevance Ranking in Information Retrieval

This paper concerns a deep learning approach to relevance ranking in information retrieval (IR). Existing deep IR models such as DSSM and CDSSM directly apply neural networks to generate ranking scores, without explicit understandings of the relevance. According to the human judgement process, a relevance label is generated by the following three steps: 1) relevant locations are detected, 2) local relevances are determined, 3) local relevances are aggregated to output the relevance label. In this paper we propose a new deep learning architecture, namely DeepRank, to simulate the above human judgment process. Firstly, a detection strategy is designed to extract the relevant contexts. Then, a measure network is applied to determine the local relevances by utilizing a convolutional neural network (CNN) or two-dimensional gated recurrent units (2D-GRU). Finally, an aggregation network with sequential integration and term gating mechanism is used to produce a global relevance score. DeepRank well captures important IR characteristics, including exact/semantic matching signals, proximity heuristics, query term importance, and diverse relevance requirement. Experiments on both benchmark LETOR dataset and a large scale clickthrough data show that DeepRank can significantly outperform learning to ranking methods, and existing deep learning methods.

cs.IR↗

arXiv2019

Neural or Statistical: An Empirical Study on Language Models for Chinese Input Recommendation on Mobile

Chinese input recommendation plays an important role in alleviating human cost in typing Chinese words, especially in the scenario of mobile applications. The fundamental problem is to predict the conditional probability of the next word given the sequence of previous words. Therefore, statistical language models, i.e.~n-grams based models, have been extensively used on this task in real application. However, the characteristics of extremely different typing behaviors usually lead to serious sparsity problem, even n-gram with smoothing will fail. A reasonable approach to tackle this problem is to use the recently proposed neural models, such as probabilistic neural language model, recurrent neural network and word2vec. They can leverage more semantically similar words for estimating the probability. However, there is no conclusion on which approach of the two will work better in real application. In this paper, we conduct an extensive empirical study to show the differences between statistical and neural language models. The experimental results show that the two different approach have individual advantages, and a hybrid approach will bring a significant improvement.

cs.CL↗

arXiv2019

Predicting Retrosynthetic Reaction using Self-Corrected Transformer Neural Networks

Synthesis planning is the process of recursively decomposing target molecules into available precursors. Computer-aided retrosynthesis can potentially assist chemists in designing synthetic routes, but at present it is cumbersome and provides results of dissatisfactory quality. In this study, we develop a template-free self-corrected retrosynthesis predictor (SCROP) to perform a retrosynthesis prediction task trained by using the Transformer neural network architecture. In the method, the retrosynthesis planning is converted as a machine translation problem between molecular linear notations of reactants and the products. Coupled with a neural network-based syntax corrector, our method achieves an accuracy of 59.0% on a standard benchmark dataset, which increases >21% over other deep learning methods, and >6% over template-based methods. More importantly, our method shows an accuracy 1.7 times higher than other state-of-the-art methods for compounds not appearing in the training set.

physics.chem-ph↗

arXiv2019

SAVIOR: Towards Bug-Driven Hybrid Testing

Hybrid testing combines fuzz testing and concolic execution. It leverages fuzz testing to test easy-to-reach code regions and uses concolic execution to explore code blocks guarded by complex branch conditions. However, its code coverage-centric design is inefficient in vulnerability detection. First, it blindly selects seeds for concolic execution and aims to explore new code continuously. However, as statistics show, a large portion of the explored code is often bug-free. Therefore, giving equal attention to every part of the code during hybrid testing is a non-optimal strategy. It slows down the detection of real vulnerabilities by over 43%. Second, classic hybrid testing quickly moves on after reaching a chunk of code, rather than examining the hidden defects inside. It may frequently miss subtle vulnerabilities despite that it has already explored the vulnerable code paths. We propose SAVIOR, a new hybrid testing framework pioneering a bug-driven principle. Unlike the existing hybrid testing tools, SAVIOR prioritizes the concolic execution of the seeds that are likely to uncover more vulnerabilities. Moreover, SAVIOR verifies all vulnerable program locations along the executing program path. By modeling faulty situations using SMT constraints, SAVIOR reasons the feasibility of vulnerabilities and generates concrete test cases as proofs. Our evaluation shows that the bug-driven approach outperforms mainstream automated testing techniques, including state-of-the-art hybrid testing systems driven by code coverage. On average, SAVIOR detects vulnerabilities 43.4% faster than DRILLER and 44.3% faster than QSYM, leading to the discovery of 88 and 76 more uniquebugs,respectively.Accordingtotheevaluationon11 well fuzzed benchmark programs, within the first 24 hours, SAVIOR triggers 481 UBSAN violations, among which 243 are real bugs.

cs.SE↗

arXiv2019

Anisotropic evolution of 4-brane in a 6D generalized Randall-Sundrum model

We investigate a 6d generalized Randall-Sundrum brane world scenario with a bulk cosmological constant. It is shown that each stress-energy tensor $T_{ab}^{i}$ on the brane is similar to a constant vacuum energy. This is consistent with the Randall-Sundrum model in which each 3-brane Lagrangian separated out a constant vacuum energy. By adopting an anisotropic metric ansatz, we obtain the 5d Friedmann-Robertson-Walker field equations. At a little later period, the expansion of the universe is proportional to $t^{\frac{1}{2}}$ which is as similar as the period of the radiation-dominated. We also investigate the case with two $a(t)$ and two $b(t)$. In a large region of $t$, we obtain the 3d effective cosmological constant $Λ_{eff}=-2Ω/3>0$ which is independent of the integral constant. Here the scale factor is exponential expansion which is consistent with our present observation of the universe. Our results demonstrate that it is possible to construct a model which solves the dark energy problem, meanwhile guaranteeing a positive brane tension.

gr-qc↗

arXiv2019

Generating Multiple Diverse Responses with Multi-Mapping and Posterior Mapping Selection

In human conversation an input post is open to multiple potential responses, which is typically regarded as a one-to-many problem. Promising approaches mainly incorporate multiple latent mechanisms to build the one-to-many relationship. However, without accurate selection of the latent mechanism corresponding to the target response during training, these methods suffer from a rough optimization of latent mechanisms. In this paper, we propose a multi-mapping mechanism to better capture the one-to-many relationship, where multiple mapping modules are employed as latent mechanisms to model the semantic mappings from an input post to its diverse responses. For accurate optimization of latent mechanisms, a posterior mapping selection module is designed to select the corresponding mapping module according to the target response for further optimization. We also introduce an auxiliary matching loss to facilitate the optimization of posterior mapping selection. Empirical results demonstrate the superiority of our model in generating multiple diverse and informative responses over the state-of-the-art methods.

cs.CL↗

arXiv2019

Non-flow effects in three-particle mixed-harmonic azimuthal correlations in small collision systems

The Multi-particle technique has been used to unravel the nature of the long-range collectivity in small collision systems. A large three-particle mixed-harmonic correlation signal was recently observed by the ATLAS Collaboration, but the role of non-flow correlations is not yet studied. We estimate the influence of non-flow correlations to the three-particle correlators in $pp$ and $p$+Pb collisions using PYTHIA and HIJING models, and compare with the ATLAS results. The large non-flow effects from the jet and dijet production is found to be largely suppressed in $p$+Pb collisions using the subevent cumulant method by calculating the azimuthal correlation between two or more longitudinal pseudorapidity ranges. Depending on the experimental subevent method, however, the non-flow effects may still be significant in $pp$ collisions.

nucl-th↗

arXiv2019

Accurate space potential measurements with emissive probe in high pressure plasma and neutral gas

The accurate measurement of plasma potentials at high pressure is investigated with the emissive probe. The emissive probe I-V characteristic of argon plasma obtained at 100 Pa is interpreted in detail, showing two inflection points in the I-V trace. The accurate plasma potentials at high pressure can be determined from the first inflection point potentials (the higher potential) by the improved inflection point method of the emissive probe, while the second inflection point is a result of the additional ionizing phenomenon caused by the collision between the emitted electrons and the neutral argon atoms. Besides, the accuracy of the plasma potential measurement at high pressure is verified to be 0.3 V by the measurement of space potential distribution between two parallel plates in neutral gas at 100 Pa. The accurate measurement of space potentials in high pressure plasma and neutral gas indicates that the improved inflection point method of the emissive probe is promising in the study of collisional sheath structures and the electrostatic probe diagnostic of high pressure plasmas.

physics.plasm-ph↗

arXiv2019

Compact fiber optical interferometer technique to measure picometer displacements in biological piezoelectric materials

A simple and robust fiber optical interferometer was developed to non-invasively study the weak piezoelectric effect from thin samples. A biological sample from inter-molt dactyl clubs obtained from the mantis shrimp was used as the test sample. The non-contact technique can measure displacements better than 0.5 picometer for samples subjected to large electric fields. The approach utilizes the phase dependent detection of an oscillating cavity at different frequencies from 0.5 kHz to 2.0 kHz. The piezoelectric constant of the biological samples was calculated from the optical interference fringes and determined to be in the range of 0.3-0.5 pm/V. The noise of 20 fm/Hz^0.5 in the setup is primarily due to thermally associated strains from current flow to the sample electrodes during the measurement.

physics.ins-det↗

arXiv2019

Investigation of HIV-1 Gag binding with RNAs and Lipids using Atomic Force Microscopy

Atomic Force Microscopy was utilized to study the morphology of Gag, ΨRNA, and their binding complexes with lipids in a solution environment with 0.1Å vertical and 1nm lateral resolution. TARpolyA RNA was used as a RNA control. The lipid used was phospha-tidylinositol-(4,5)-bisphosphate (PI(4,5)P2). The morphology of specific complexes Gag-ΨRNA, Gag-TARpolyA RNA, Gag-PI(4,5)P2 and PI(4,5)P2-ΨRNA-Gag were studied. They were imaged on either positively or negatively charged mica substrates depending on the net charges carried. Gag and its complexes consist of monomers, dimers and tetramers, which was confirmed by gel electrophoresis. The addition of specific ΨRNA to Gag is found to increase Gag multimerization. Non-specific TARpolyA RNA was found not to lead to an increase in Gag multimerization. The addition PI(4,5)P2 to Gag increases Gag multimerization, but to a lesser extent than ΨRNA. When both ΨRNA and PI(4,5)P2 are present Gag undergoes comformational changes and an even higher degree of multimerization.

q-bio.BM↗

arXiv2019

PTrix: Efficient Hardware-Assisted Fuzzing for COTS Binary

Despite its effectiveness in uncovering software defects, American Fuzzy Lop (AFL), one of the best grey-box fuzzers, is inefficient when fuzz-testing source-unavailable programs. AFL's binary-only fuzzing mode, QEMU-AFL, is typically 2-5X slower than its source-available fuzzing mode. The slowdown is largely caused by the heavy dynamic instrumentation. Recent fuzzing techniques use Intel Processor Tracing (PT), a light-weight tracing feature supported by recent Intel CPUs, to remove the need of dynamic instrumentation. However, we found that these PT-based fuzzing techniques are even slower than QEMU-AFL when fuzzing real-world programs, making them less effective than QEMU-AFL. This poor performance is caused by the slow extraction of code coverage information from highly compressed PT traces. In this work, we present the design and implementation of PTrix, which fully unleashes the benefits of PT for fuzzing via three novel techniques. First, PTrix introduces a scheme to highly parallel the processing of PT trace and target program execution. Second, it directly takes decoded PT trace as feedback for fuzzing, avoiding the expensive reconstruction of code coverage information. Third, PTrix maintains the new feedback with stronger feedback than edge-based code coverage, which helps reach new code space and defects that AFL may not. We evaluated PTrix by comparing its performance with the state-of-the-art fuzzers. Our results show that, given the same amount of time, PTrix achieves a significantly higher fuzzing speed and reaches into code regions missed by the other fuzzers. In addition, PTrix identifies 35 new vulnerabilities in a set of previously well-fuzzed binaries, showing its ability to complement existing fuzzers.

cs.SE↗

arXiv2019

Cryogenic low power CMOS analog buffer at 4.2K

A novel power-efficient analog buffer at liquid helium temperature is proposed. The proposed circuit is based on an input stage consisting of two complementary differential pairs to achieve rail-to-rail level tracking. Results of simulation based on SMIC 0.18um CMOS technology show the high driving capability and low quiescent power consumption at cryogenic temperature. Operating at single 1.4 V supply, the circuit could achieve a slew-rate of +51 V/us and -93 V/us for 10 pF capacitive load. The static power of the circuit is only 79uW.

physics.app-ph↗

arXiv2019

Lijiang 2.4-meter Telescope and its Instruments

Lijiang 2.4-meter Telescope(LJT), the largest common-purpose optical telescope in China, has been applied to the world-wide astronomers since 2008. It is located at Gaomeigu site, Lijiang Observatory(LJO), the southwest of China. The site has very good observational conditions. Since 10-year operation, several instruments have been equipped on the LJT. Astronomers can perform both photometric and spectral observations. The main scientific goals of LJT include photometric and spectral evolution of supernova, reverberation mapping of active galactic nucleus, physical properties of binary star and near-earth object(comet and asteroid), identification of exoplanet, and all kinds of transients. Until now, the masses of 41 high accretion rate black holes have been measured, and more than 168 supernova have been identified by the LJT. More than 190 papers related to the LJT have been published. In this paper, the general observation condition of the Gaomeigu site is introduced at first. Then, the LJT structure is described in detail, including the optical, mechanical, motion and control system. The specification of all the instruments, and some detailed parameters of the YFOSC is also presented. Finally, some important scientific results and future expectations are summarized.

astro-ph.IM↗

arXiv2019

Investigating different $Λ$ and $\barΛ$ polarizations in relativistic heavy-ion collisions

Based on the chiral kinetic equations of motion, spin polarizations of various quarks, due to the magnetic field induced by spectator protons as well as the quark-antiquark vector interaction, are studied within a partonic transport approach. Although the magnetic field in QGP enhances the splitting of the spin polarizations of partons compared to the results under the magnetic field in vacuum, the spin polarizations of $s$ and $\bar s$ quarks are also sensitive to the quark-antiquark vector interaction, challenging that the different $Λ$ and $\bar Λ$ spin polarization is a good measure of the magnetic field in relativistic heavy-ion collisions. It is also found that there is no way to obtain the large splitting of the spin polarization between $Λ$ and $\bar Λ$ at $\sqrt{s_{NN}}=7.7$ GeV with partonic dynamics.

nucl-th↗

arXiv2019

Charge asymmetry dependence of the elliptic flow splitting in relativistic heavy-ion collisions

The elliptic flow splitting $Δv_2$ between $\bar{u}$ and $u$ quarks as well as between $π^-$ and $π^+$ in midcentral Au+Au collisions at $\sqrt{s_{NN}}=200$ GeV has been studied, based on the framework of an extended multiphase transport model with the partonic evolution described by the chiral kinetic equations of motion. Within the available statistics, the slope of $Δv_2$ between $\bar{u}$ and $u$ quarks with respect to the electric charge asymmetry $A_{ch}$ from the linear fit is found to be negative, due to the correlation between the velocity and the coordinate in the initial parton phase-space distribution. Simulations with the magnetic field in QGP overestimate the splitting of the spin polarization between $Λ$ and $\barΛ$ observed experimentally, with the latter more consistent with results under the magnetic field in vacuum. Considering the uncertainties from the magnetic field, the quark-antiquark vector interaction, and the hadronization, as well as the hadronic evolution, our study shows that the experimentally observed positive slope of $Δv_2$ with respect to $A_{ch}$ is not likely due to the chiral magnetic wave.

nucl-th↗

arXiv2019

Pre-training of Context-aware Item Representation for Next Basket Recommendation

Next basket recommendation, which aims to predict the next a few items that a user most probably purchases given his historical transactions, plays a vital role in market basket analysis. From the viewpoint of item, an item could be purchased by different users together with different items, for different reasons. Therefore, an ideal recommender system should represent an item considering its transaction contexts. Existing state-of-the-art deep learning methods usually adopt the static item representations, which are invariant among all of the transactions and thus cannot achieve the full potentials of deep learning. Inspired by the pre-trained representations of BERT in natural language processing, we propose to conduct context-aware item representation for next basket recommendation, called Item Encoder Representations from Transformers (IERT). In the offline phase, IERT pre-trains deep item representations conditioning on their transaction contexts. In the online recommendation phase, the pre-trained model is further fine-tuned with an additional output layer. The output contextualized item embeddings are used to capture users' sequential behaviors and general tastes to conduct recommendation. Experimental results on the Ta-Feng data set show that IERT outperforms the state-of-the-art baseline methods, which demonstrated the effectiveness of IERT in next basket representation.

cs.IR↗

arXiv2019

Transport approaches for the Description of Intermediate-Energy Heavy-Ion Collisions

The transport approach is a useful tool to study dynamics of non-equilibrium systems. For heavy-ion collisions at intermediate energies, where both the smooth nucleon potential and the hard-core nucleon-nucleon collision are important, the dynamics are properly described by two families of transport models, i.e., the Boltzmann-Uehling-Uhlenbeck approach and the quantum molecular dynamics approach. These transport models have been extensively used to extract valuable information of the nuclear equation of state, the nuclear symmetry energy, and microscopic nuclear interactions from intermediate-energy heavy-ion collision experiments. On the other hand, there do exist deviations on the predications and conclusions from different transport models. Efforts on the transport code evaluation project are devoted in order to understand the model dependence of transport simulations and well control the main ingredients, such as the initialization, the mean-field potential, the nucleon-nucleon collision, etc. A new era of accurately extracting nuclear interactions from transport model studies is foreseen.

nucl-th↗