arXiv subjects

Ying Zhou

Publications and source records attributed to Ying Zhou.

At least 109 records · Page 6Linked to original sources

arXiv2023

BURT: A Chatbot for Interactive Bug Reporting

This paper introduces BURT, a web-based chatbot for interactive reporting of Android app bugs. BURT is designed to assist Android app end-users in reporting high-quality defect information using an interactive interface. BURT guides the users in reporting essential bug report elements, i.e., the observed behavior, expected behavior, and the steps to reproduce the bug. It verifies the quality of the text written by the user and provides instant feedback. In addition, BURT provides graphical suggestions that the users can choose as alternatives to textual descriptions. We empirically evaluated BURT, asking end-users to report bugs from six Android apps. The reporters found that BURT's guidance and automated suggestions and clarifications are useful and BURT is easy to use. BURT is an open-source tool, available at github.com/sea-lab-wm/burt/tree/tool-demo. A video showing the full capabilities of BURT can be found at https://youtu.be/SyfOXpHYGRo

cs.SE↗

arXiv2023

Pressure-induced superconductivity in quasi-one-dimensional semimetal $\mathrm{Ta}_2 \mathrm{PdSe}_6$

Here we report the discovery of pressure-induced superconductivity in quasi-one-dimensional $\mathrm{Ta}_2 \mathrm{PdSe}_6$, through a combination of electrical transport, synchrotron x-ray diffraction, and theoretical calculations. Our transport measurements show that the superconductivity appears at a critical pressure $P_{\mathrm{c}} \sim 18.3$ GPa and is robust upon further compression up to $62.6$ GPa. The estimated upper critical field $μ_0 H_{\mathrm{c} 2}(0)$ in the pressurized $\mathrm{Ta}_2 \mathrm{PdSe}_6$ is much lower than the Pauli limiting field, in contrast to the case in its isostructural analogs $M_2 \mathrm{Pd}_{\mathrm{x}} X_5$ $(M=\mathrm{Nb}$, Ta; $X=\mathrm{S}, \mathrm{Se})$. Concomitant with the occurrence of superconductivity, anomalies in pressuredependent transport properties are observed, including sign reversal of Hall coefficient, abnormally enhanced resistance, and dramatically suppressed magnetoresistance. Meanwhile, room-temperature synchrotron x-ray diffraction experiments reveal the stability of the pristine monoclinic structure (space group $C 2 / m$ ) upon compression. Combined with the density functional theory calculations, we argue that a pressure-induced Lifshitz transition could be the electronic origin of the emergent superconductivity in $\mathrm{Ta}_2 \mathrm{PdSe}_6$.

cond-mat.supr-con↗

arXiv2023

Physical properties, electronic structure, and strain-tuned monolayer of the weak topological insulator RbTi3Bi5 with Kagome lattice

Kagome metals AV3Sb5 (A = K, Rb, and Cs) with a V-Kagome lattice acting as a fertile platform to investigate geometric frustration, electron correlation, superconductivity, and nontrivial band topology, have attracted tremendous attention. Here we reported the structure and properties of ATi3Bi5 (A = Rb, Cs) family with a Ti-Kagome lattice, specifically focusing on the electronic structure and nontrivial band topology of RbTi3Bi5. ATi3Bi5 (A = Rb, Cs) is found to be non-superconducting metal with strong quasi-two-dimensional feature, moderate electron correlation, and small Pauli paramagnetism. Based on first principles calculations, RbTi3Bi5 is determined to be a weak topological insulator with gapless surface states along (100) plane, and the electronic band structure along (001) plane is in great agreement with experimentally observed one. In particular, the electronic properties of the RbTi3Bi5 monolayer can be efficiently tuned by a biaxial strain according to calculation, with its lower saddle points coming from Kagome lattice approaching the Fermi level. These results highlight ATi3Bi5 (A = Rb, Cs) with Ti-Kagome lattice is a new Kagome metal to explore nontrivial band topology and exotic phases.

cond-mat.supr-con↗

arXiv2022

The Promises of Parallel Outcomes

A key challenge in causal inference from observational studies is the identification and estimation of causal effects in the presence of unmeasured confounding. In this paper, we introduce a novel approach for causal inference that leverages information in multiple outcomes to deal with unmeasured confounding. The key assumption in our approach is conditional independence among multiple outcomes. In contrast to existing proposals in the literature, the roles of multiple outcomes in our key identification assumption are symmetric, hence the name parallel outcomes. We show nonparametric identifiability with at least three parallel outcomes and provide parametric estimation tools under a set of linear structural equation models. Our proposal is evaluated through a set of synthetic and real data analyses.

stat.ME↗

arXiv2022

GW190814: Circumstantial Evidence for Up-Down Quark Star

Within a confining quark matter model which considers phenomenologically the quark confinement and asymptotic freedom as well as the chiral symmetry restoration and quark deconfinement at high baryon density, we find that if the up-down quark matter ($ud$QM) is more stable than nuclear matter and strange quark matter (SQM), the maximum mass of static quark stars with $ud$QM is $2.87M_{\odot}$ under agreement with both the constraints on star tidal deformability from gravitational wave signal GW170817 and the mass-radius of PSR J0030+0451 and PSR J0740+6620 measured by NICER. In contrast, the conventional strange quark star with the SQM that is more stable than nuclear matter while the nuclear matter is more stable than $ud$QM, has a maximum static mass of only $1.87M_{\odot}$ and its radius significantly deviates from NICER's constraint. Our results thus provide circumstantial evidence suggesting the recently reported GW190814's secondary component with a mass of $2.59^{+0.08}_{-0.09}M_\odot$ could be an up-down quark star.

astro-ph.HE↗

arXiv2022

Toward Interactive Bug Reporting for (Android App) End-Users

Many software bugs are reported manually, particularly bugs that manifest themselves visually in the user interface. End-users typically report these bugs via app reviewing websites, issue trackers, or in-app built-in bug reporting tools, if available. While these systems have various features that facilitate bug reporting (e.g., textual templates or forms), they often provide limited guidance, concrete feedback, or quality verification to end-users, who are often inexperienced at reporting bugs and submit low-quality bug reports that lead to excessive developer effort in bug report management tasks. We propose an interactive bug reporting system for end-users (Burt), implemented as a task-oriented chatbot. Unlike existing bug reporting systems, Burt provides guided reporting of essential bug report elements (i.e., the observed behavior, expected behavior, and steps to reproduce the bug), instant quality verification, and graphical suggestions for these elements. We implemented a version of Burt for Android and conducted an empirical evaluation study with end-users, who reported 12 bugs from six Android apps studied in prior work. The reporters found that Burt's guidance and automated suggestions/clarifications are useful and Burt is easy to use. We found that Burt reports contain higher-quality information than reports collected via a template-based bug reporting system. Improvements to Burt, informed by the reporters, include support for various wordings to describe bug report elements and improved quality verification. Our work marks an important paradigm shift from static to interactive bug reporting for end-users.

cs.SE↗

arXiv2022

Sequence-to-Set Generative Models

In this paper, we propose a sequence-to-set method that can transform any sequence generative model based on maximum likelihood to a set generative model where we can evaluate the utility/probability of any set. An efficient importance sampling algorithm is devised to tackle the computational challenge of learning our sequence-to-set model. We present GRU2Set, which is an instance of our sequence-to-set method and employs the famous GRU model as the sequence generative model. To further obtain permutation invariant representation of sets, we devise the SetNN model which is also an instance of the sequence-to-set model. A direct application of our models is to learn an order/set distribution from a collection of e-commerce orders, which is an essential step in many important operational decisions such as inventory arrangement for fast delivery. Based on the intuition that small-sized sets are usually easier to learn than large sets, we propose a size-bias trick that can help learn better set distributions with respect to the $\ell_1$-distance evaluation metric. Two e-commerce order datasets, TMALL and HKTVMALL, are used to conduct extensive experiments to show the effectiveness of our models. The experimental results demonstrate that our models can learn better set/order distributions from order data than the baselines. Moreover, no matter what model we use, applying the size-bias trick can always improve the quality of the set distribution learned from data.

cs.LG↗

arXiv2022

Flipping of antiferromagnetic to superconducting states in pressurized quasi-one-dimensional manganese-based compounds

One of the universal features of unconventional superconductors is that the superconducting (SC) state is developed in the proximity of an antiferromagnetic (AFM) state. Understanding the interplay between these two states is one of the key issues to uncover the underlying physics of unconventional SC mechanism. Here, we report a pressure-induced flipping of the AFM state to SC state in the quasi-one-dimensional AMn6Bi5 (A = K, Rb, and Cs) compounds. We find that at a critical pressure the AFM state suddenly disappears at a finite temperature and a SC state simultaneously emerges at a lower temperature without detectable structural changes. Intriguingly, all members of the family present the AFM-SC transition at almost the same critical pressures (Pc), though their ambient-pressure unit-cell volumes vary substantially. Our theoretical calculations indicate that the increasing weight of dxz orbital electrons near Fermi energy under the pressure may be the origin of the flipping. These results reveal a diversity of competing nature between the AFM and SC states among the 3d-transition-metal compounds.

cond-mat.supr-con↗

arXiv2022

Constraints on the Symmetry Energy from PREX-II in the Multimessenger Era

The neutron skin thickness $Δr_{\rm{np}}$ of heavy nuclei is essentially determined by the symmetry energy density slope $L({ρ})$ at $ρ_c = 0.11~{\rm {fm}^{-3}}\approx 2/3ρ_0$ ($ρ_0$ is nuclear saturation density), roughly corresponding to the average density of finite nuclei. The PREX collaboration recently reported a model-independent extraction of $Δr^{208}_{\rm{np}} = 0.283 \pm 0.071$ fm for the $Δr_{\rm{np}}$ of $^{208}$Pb, suggesting a rather stiff symmetry energy $E_{\rm{sym}}({ρ})$ with $L({ρ_c }) \ge 52$ MeV. We show that the $E_{\rm{sym}}({ρ})$ cannot be too stiff and $L({ρ_c }) \le 73$ MeV is necessary to be compatible with (1) the ground-state properties and giant monopole resonances of finite nuclei, (2) the constraints on the equation of state of symmetric nuclear matter at suprasaturation densities from flow data in heavy-ion collisions, (3) the largest neutron star (NS) mass reported so far for PSR J0740+6620, (4) the NS tidal deformability extracted from gravitational wave signal GW170817 and (5) the mass-radius of PSR J0030+045 measured simultaneously by NICER. This allows us to obtain $52 \le L({ρ_c }) \le 73$ MeV and $0.212 \le Δr^{208}_{\rm{np}} \le 0.271$ fm, and further $E_{\rm{sym}}({ρ_0 }) = 34.3 \pm 1.7$ MeV, $L({ρ_0 }) = 83.1 \pm 24.7$ MeV, and $E_{\rm{sym}}({2ρ_0 }) = 62.8 \pm 15.9$ MeV. A number of critical implications on nuclear physics and astrophysics are discussed.

nucl-th↗

arXiv2022

Re-thinking Knowledge Graph Completion Evaluation from an Information Retrieval Perspective

Knowledge graph completion (KGC) aims to infer missing knowledge triples based on known facts in a knowledge graph. Current KGC research mostly follows an entity ranking protocol, wherein the effectiveness is measured by the predicted rank of a masked entity in a test triple. The overall performance is then given by a micro(-average) metric over all individual answer entities. Due to the incomplete nature of the large-scale knowledge bases, such an entity ranking setting is likely affected by unlabelled top-ranked positive examples, raising questions on whether the current evaluation protocol is sufficient to guarantee a fair comparison of KGC systems. To this end, this paper presents a systematic study on whether and how the label sparsity affects the current KGC evaluation with the popular micro metrics. Specifically, inspired by the TREC paradigm for large-scale information retrieval (IR) experimentation, we create a relatively "complete" judgment set based on a sample from the popular FB15k-237 dataset following the TREC pooling method. According to our analysis, it comes as a surprise that switching from the original labels to our "complete" labels results in a drastic change of system ranking of a variety of 13 popular KGC models in terms of micro metrics. Further investigation indicates that the IR-like macro(-average) metrics are more stable and discriminative under different settings, meanwhile, less affected by label sparsity. Thus, for KGC evaluation, we recommend conducting TREC-style pooling to balance between human efforts and label completeness, and reporting also the IR-like macro metrics to reflect the ranking nature of the KGC task.

cs.CL↗

arXiv2022

Pressure-induced superconductivity in kagome single crystal Pd3P2S8

Kagome lattice offers unique opportunities for the exploration of unusual quantum states of correlated electrons. Here, we report on the observation of superconductivity in a kagome single crystal Pd3P2S8 when a semiconducting to metallic transition is driven by pressure. High-pressure resistance measurements show that the metallization and superconductivity are simultaneously observed at about 11 GPa. With increasing pressure, the superconducting critical temperature Tc is monotonously enhanced from 2.6 K to a maximum 7.7 K at ~52 GPa. Interestingly, superconductivity retains when the pressure is fully released. Synchrotron XRD and Raman experiments consistently evidence that the emergence of superconductivity is accompanied with an amorphization and the retainability of superconductivity upon decompression can be attributed to the irreversibility of the amorphization.

cond-mat.supr-con↗

arXiv2022

Tripartite: Tackle Noisy Labels by a More Precise Partition

Samples in large-scale datasets may be mislabeled due to various reasons, and Deep Neural Networks can easily over-fit to the noisy label data. To tackle this problem, the key point is to alleviate the harm of these noisy labels. Many existing methods try to divide training data into clean and noisy subsets in terms of loss values, and then process the noisy label data varied. One of the reasons hindering a better performance is the hard samples. As hard samples always have relatively large losses whether their labels are clean or noisy, these methods could not divide them precisely. Instead, we propose a Tripartite solution to partition training data more precisely into three subsets: hard, noisy, and clean. The partition criteria are based on the inconsistent predictions of two networks, and the inconsistency between the prediction of a network and the given label. To minimize the harm of noisy labels but maximize the value of noisy label data, we apply a low-weight learning on hard data and a self-supervised learning on noisy label data without using the given labels. Extensive experiments demonstrate that Tripartite can filter out noisy label data more precisely, and outperforms most state-of-the-art methods on five benchmark datasets, especially on real-world datasets.

cs.CV↗

arXiv2022

Effects of isoscalar- and isovector-scalar meson mixing on neutron star structure

Based on the accurately calibrated interaction FSUGold, we show that including isovector scalar $δ$ meson and its coupling to isoscalar scalar $σ$ meson in the relativistic mean field (RMF) model can soften the symmetry energy $E_{\rm{sym}}(n)$ at intermediate densities while stiffen the $E_{\rm{sym}}(n)$ at high densities. We find this new RMF model can be simultaneously compatible with (1) the constraints on the equation of state of symmetric nuclear matter at suprasaturation densities from flow data in heavy-ion collisions, (2) the neutron skin thickness of $^{208}$Pb from the PREX-II experiment, (3) the largest mass of neutron star (NS) reported so far from PSR J0740+6620, (4) the limit of $Λ_{1.4}\leq580$ for the dimensionless tidal deformability of the canonical 1.4$M_{\odot}$ NS from the gravitational wave signal GW170817, (5) the mass-radius relation of PSR J0030+0451 and PSR J0740+6620 measured by NICER, and thus remove the tension between PREX-II and GW170817 observed in the conventional RMF model.

nucl-th↗

arXiv2022

Two-dimensional ferroelectricity induced by octahedral rotation distortion in perovskite oxides

Two-dimensional (2D) ferroelectricity has attracted extensive attention since its discovery in the monolayers of van der Waals materials. Here we show that 2D ferroelectricity induced by octahedral rotation distortion is widely present in the perovskite bilayer system through first-principles calculations. The perovskite tolerance factor plays a crucial role in the lattice dynamics and ground-state structure of the perovskite monolayers and bilayers, thus providing an important indicator for screening this hybrid improper ferroelectricity. Generally, the ferroelectric switching via an orthorhombic twin state has the lowest energy barrier. Epitaxial strain can effectively tune the ferroelectric polarization and ferroelectric switching by changing the amplitude of octahedral rotation and tilt distortion. The increasing compressive strain causes a polar to nonpolar phase transition by suppressing the tilt distortion. The cooperative effect of octahedral distortion at the interface with the substrate can reduce the energy barrier of the reversing rotation mode and can even change the lowest-energy ferroelectric switching path.

cond-mat.mtrl-sci↗

arXiv2022

A new quasi-one-dimensional superconductor parent compound NaMn$_6$Bi$_5$ with lower antiferromagnetic transition temperatures

Mn-based superconductor is rare and recently reported in quasi-one-dimensional KMn$_6$Bi$_5$ with [Mn$_6$Bi$_5$]-columns under high pressure. Here we report the synthesis, magnetic properties, electrical resistivity, and specific heat capacity of the newly-discovered quasi-one-dimensional NaMn$_6$Bi$_5$ single crystal. Compared with other AMn$_6$Bi$_5$ (A = K, Rb, and Cs), NaMn$_6$Bi$_5$ has larger intra-column Bi-Bi bond length, which may result in the two decoupled antiferromagnetic transitions at 47.3 K and 52.3 K. The relatively lower antiferromagnetic transition temperatures make NaMn$_6$Bi$_5$ a more suitable platform to explore Mn-based superconductors. Anisotropic resistivity and non-Fermi liquid behavior at low temperature are observed. Heat capacity measurement reveals that NaMn$_6$Bi$_5$ has similar Debye temperature with those of AMn$_6$Bi$_5$ (A = K and Rb), whereas the Sommerfeld coefficient is unusually large. Using first-principles calculations, the quite different density of states and an unusual enhancement near the Fermi level are observed for NaMn$_6$Bi$_5$, when compared with those of other AMn$_6$Bi$_5$ (A = K, Rb, and Cs) compounds.

cond-mat.supr-con↗

arXiv2022

Squeezed driving induced entanglement and squeezing among cavity modes and magnon mode in a magnon-cavity QED system

We propose a scheme to generate entanglement between two cavity modes and squeeze magnon mode in a magnon-cavity QED system, where the two microwave cavity modes are coupled with a massive yttrium iron garnet (YIG) sphere through magnetic dipole interaction. The nonlinearity used in our system originates from a squeezed driving via parametric down-conversion process, which is the reason to cause entanglement and squeezing. By using the mean field approximation and employing experimentally feasible parameters, we demonstrate that the system shows zero entanglement and squeezing without squeezed driving. Meanwhile, our QED system denotes that the entanglement between squeezed cavity mode and magnon mode can be transferred to the other cavity mode and magnon mode via magnon-cavity coupling interaction, and then the two cavity modes get entangled. A genuinely tripartite entangled state is formed. We also show that magnon mode can be prepared in a squeezed state via magnon-cavity beam-splitter interaction, which is as a result of the squeezed field. Moreover, we show that it is a good way to enhance entanglement and squeezing by increasing the nonlinear gain coefficient of squeezed driving. Our results denote that magnon-cavity QED system is a powerful platform for studying macroscopic quantum phenomena, which illustrates a new method to photon-photon entanglement and magnon squeezing.

quant-ph↗

arXiv2022

PP-ShiTu: A Practical Lightweight Image Recognition System

In recent years, image recognition applications have developed rapidly. A large number of studies and techniques have emerged in different fields, such as face recognition, pedestrian and vehicle re-identification, landmark retrieval, and product recognition. In this paper, we propose a practical lightweight image recognition system, named PP-ShiTu, consisting of the following 3 modules, mainbody detection, feature extraction and vector search. We introduce popular strategies including metric learning, deep hash, knowledge distillation and model quantization to improve accuracy and inference speed. With strategies above, PP-ShiTu works well in different scenarios with a set of models trained on a mixed dataset. Experiments on different datasets and benchmarks show that the system is widely effective in different domains of image recognition. All the above mentioned models are open-sourced and the code is available in the GitHub repository PaddleClas on PaddlePaddle.

cs.CV↗

arXiv2022

Measuring neutron skin by grazing isobaric collisions

Neutron skin thickness ($Δr_{\rm np}$) of nuclei and the inferred nuclear symmetry energy are of critical importance to nuclear physics and astrophysics. It is traditionally measured by nuclear processes with significant theoretical uncertainties. We recently proposed an indirect measurement of the $Δr_{\rm np}$ by charged hadron multiplicities in central isobaric collisions at relativistic energies, which are sensitive to nuclear densities. In this Letter, we propose a direct measurement of the $Δr_{\rm np}$ by using net-charge multiplicities in ultra-peripheral (grazing) collisions of those isobars, under the assumption that they are simple superimposition of nucleon-nucleon interactions. We illustrate this novel approach by the TRENTO and URQMD models.

nucl-th↗