arXiv subjects

Yong Gao

Publications and source records attributed to Yong Gao.

At least 55 records · Page 3Linked to original sources

arXiv2021

Neutron stars in massive scalar-Gauss-Bonnet gravity: Spherical structure and time-independent perturbations

The class of scalar-tensor theories with the scalar field coupling to the Gauss-Bonnet invariant has drawn great interest since solutions of spontaneous scalarization were found for black holes in these theories. We contribute to the existing literature a detailed study of the spontaneously scalarized neutron stars (NSs) in a typical theory where the coupling function of the scalar field takes the quadratic form and the scalar field is massive. The investigation here includes the spherical solutions of the NSs as well as their perturbative properties, namely the tidal deformability and the moment of inertia, treated in a unified and extendable way under the framework of spherical decomposition. We find that while the mass, the radius, and the moment of inertia of the spontaneously scalarized NSs show very moderate deviations from those of the NSs in general relativity (GR), the tidal deformability exhibits significant differences between the solutions in GR and the solutions of spontaneous scalarization for certain values of the parameters in the scalar-Gauss-Bonnet theory. As a result, the celebrated universal relation between the moment of inertia and the tidal deformability of neutron stars breaks down. With the mass and the tidal deformability of NSs attainable in the gravitational waves from binary NS mergers, the radius measurable using the X-ray satellites, and the moment of inertia accessible via the high-precision pulsar timing techniques, future multi-messenger observations can be contrasted with the theoretical results and provide us necessary information for building up theories beyond GR.

gr-qc↗

arXiv2021

Wave scattering in layered orthotropic media I: a stable PML and a high-accuracy boundary integral equation method

In anisotropic media, the standard perfectly matched layer (PML) technique suffers irrevocable instability in terminating the unbounded problem domains. It remains an open question whether a stable PML-like absorbing boundary condition exists. For wave scattering in a layered orthotropic medium, this question is affirmatively answered for the first time in this paper. In each orthotropic medium, the permittivity tensor uniquely determines a change of coordinates, that transforms the governing anisotropic Helmholtz equation into an isotropic Helmholtz equation in the new coordinate system. This leads us to propose a novel Sommerfeld radiation condition (SRC) to rigorously characterize outgoing waves in the layered orthotropic medium. Naturally, the SRC motivates a regionalized PML (RPML) to truncate the scattering problem, in the sense that a standard PML is set up in the new coordinate system in each orthotropic region. It is revealed that the RPML is unconditionally stable compared with the unstable uniaxial PML. A high-accuracy boundary integral equation (BIE) method is developed to solve the resulting boundary value problem. Numerical experiments are carried out to validate the stability of the RPML and the accuracy of the BIE method, showing exponentially decaying truncation errors as the RPML parameters increase.

math.NA↗

arXiv2021

Code Representation Learning with Prüfer Sequences

An effective and efficient encoding of the source code of a computer program is critical to the success of sequence-to-sequence deep neural network models for tasks in computer program comprehension, such as automated code summarization and documentation. A significant challenge is to find a sequential representation that captures the structural/syntactic information in a computer program and facilitates the training of the learning models. In this paper, we propose to use the Prüfer sequence of the Abstract Syntax Tree (AST) of a computer program to design a sequential representation scheme that preserves the structural information in an AST. Our representation makes it possible to develop deep-learning models in which signals carried by lexical tokens in the training examples can be exploited automatically and selectively based on their syntactic role and importance. Unlike other recently-proposed approaches, our representation is concise and lossless in terms of the structural information of the AST. Empirical studies on real-world benchmark datasets, using a sequence-to-sequence learning model we designed for code summarization, show that our Prüfer-sequence-based representation is indeed highly effective and efficient, outperforming significantly all the recently-proposed deep-learning models we used as the baseline models.

cs.AI↗

arXiv2021

Rotation and deformation of strangeon stars in the Lennard-Jones model

The strong interactions at low energy scales determine the state of the supranuclear matter in the pulsar-like compact objects. It is proposed that the bulk strong matter could be composed of strangeons, which are quark clusters with a nearly equal number of three light-flavor quarks. In this work, to characterize the strong-repulsive interactions at short distances and the non-relativistic nature of the strangeons, the Lennard-Jones model is used to describe the equation of state (EoS) of strangeon stars (SSs). We investigate the static, the slowly rotating, and the tidally deformed SSs in detail. The corrections resulted from the finite surface densities are considered crucially in the perturbative approaches. We also study the universal relations between the moments of inertia, the tidal deformabilities, and the quadrupole moments. Those results are ready to be used for various purposes in astrophysics, and possible constraints from contemporary observations on the parameter space of the Lennard-Jones model are discussed. Future observations of the pulsars' radio signals, the X-ray emissions from the hot spots on the surface of the stars, and the gravitational waves (GWs) from binary mergers can give tighter constraints or even verify or falsify the existence of SSs.

gr-qc↗

arXiv2021

Content Filtering Enriched GNN Framework for News Recommendation

Learning accurate users and news representations is critical for news recommendation. Despite great progress, existing methods seem to have a strong bias towards content representation or just capture collaborative filtering relationship. However, these approaches may suffer from the data sparsity problem (user-news interactive behavior sparsity problem) or maybe affected more by news (or user) with high popularity. In this paper, to address such limitations, we propose content filtering enriched GNN framework for news recommendation, ConFRec in short. It is compatible with existing GNN-based approaches for news recommendation and can capture both collaborative and content filtering information simultaneously. Comprehensive experiments are conducted to demonstrate the effectiveness of ConFRec over the state-of-the-art baseline models for news recommendation on real-world datasets for news recommendation.

cs.IR↗

arXiv2021

Probing dipole radiation from binary neutron stars with ground-based laser-interferometer and atom-interferometer gravitational-wave observatories

Atom-interferometer gravitational-wave (GW) observatory, as a new design of ground-based GW detector for the near future, is sensitive at a relatively low frequency for GW observations. Taking the proposed atom interferometer Zhaoshan Long-baseline Atom Interferometer Gravitation Antenna (ZAIGA), and its illustrative upgrade (Z+) as examples, we investigate how the atom interferometer will complement ground-based laser interferometers in testing the gravitational dipole radiation from binary neutron star (BNS) mergers. A test of such kind is important for a better understanding of the strong equivalence principle laying at the heart of Einstein's general relativity. To obtain a statistically sound result, we sample BNS systems according to their merger rate and population, from which we study the expected bounds on the parameterized dipole radiation parameter $B$. Extracting BNS parameters and the dipole radiation from the combination of ground-based laser interferometers and the atom-interferometer ZAIGA/Z+, we are entitled to obtain tighter bounds on $B$ by a few times to a few orders of magnitude, compared to ground-based laser interferometers alone, ultimately reaching the levels of $|B| \lesssim 10^{-9}$ (with ZAIGA) and $|B| \lesssim 10^{-10}$ (with Z+).

gr-qc↗

arXiv2021

ScaleFreeCTR: MixCache-based Distributed Training System for CTR Models with Huge Embedding Table

Because of the superior feature representation ability of deep learning, various deep Click-Through Rate (CTR) models are deployed in the commercial systems by industrial companies. To achieve better performance, it is necessary to train the deep CTR models on huge volume of training data efficiently, which makes speeding up the training process an essential problem. Different from the models with dense training data, the training data for CTR models is usually high-dimensional and sparse. To transform the high-dimensional sparse input into low-dimensional dense real-value vectors, almost all deep CTR models adopt the embedding layer, which easily reaches hundreds of GB or even TB. Since a single GPU cannot afford to accommodate all the embedding parameters, when performing distributed training, it is not reasonable to conduct the data-parallelism only. Therefore, existing distributed training platforms for recommendation adopt model-parallelism. Specifically, they use CPU (Host) memory of servers to maintain and update the embedding parameters and utilize GPU worker to conduct forward and backward computations. Unfortunately, these platforms suffer from two bottlenecks: (1) the latency of pull \& push operations between Host and GPU; (2) parameters update and synchronization in the CPU servers. To address such bottlenecks, in this paper, we propose the ScaleFreeCTR: a MixCache-based distributed training system for CTR models. Specifically, in SFCTR, we also store huge embedding table in CPU but utilize GPU instead of CPU to conduct embedding synchronization efficiently. To reduce the latency of data transfer between both GPU-Host and GPU-GPU, the MixCache mechanism and Virtual Sparse Id operation are proposed. Comprehensive experiments and ablation studies are conducted to demonstrate the effectiveness and efficiency of SFCTR.

cs.IR↗

arXiv2021

Precession of spheroids under Lorentz violation and observational consequences for neutron stars

The Standard-Model Extension (SME) is an effective-field-theoretic framework that catalogs all Lorentz-violating field operators. The anisotropic correction from the minimal gravitational SME to Newtonian gravitational energy for spheroids is studied, and the rotation of rigid spheroids is solved with perturbation method and numerical approach. The well-known forced precession solution given by Nordtvedt in the parameterized post-Newtonian formalism is recovered and applied to two observed solitary millisecond pulsars to set bounds on the coefficients for Lorentz violation in the SME framework. A different solution, which describes the rotation of an otherwise free-precessing star in the presence of Lorentz violation, is found, and its consequences on pulsar signals and continuous gravitational waves (GWs) emitted by neutron stars (NSs) are investigated. The study provides new possible tests of Lorentz violation once free-precessing NSs are firmly identified in the future.

gr-qc↗

arXiv2021

Signature of Lorentz Violation in Continuous Gravitational-Wave Spectra of Ellipsoidal Neutron Stars

We study effects of Lorentz-invariance violation on the rotation of neutron stars (NSs) in the minimal gravitational Standard-Model Extension framework, and calculate the quadrupole radiation generated by them. Aiming at testing Lorentz invariance with observations of continuous gravitational waves (GWs) from rotating NSs in the future, we compare the GW spectra of a rotating ellipsoidal NS under Lorentz-violating gravity with those of a Lorentz-invariant one. The former are found to possess frequency components higher than the second harmonic, which does not happen for the latter, indicating those higher frequency components to be potential signatures of Lorentz violation in continuous GW spectra of rotating NSs.

gr-qc↗

arXiv2020

Precession of triaxially deformed neutron stars

A deformed neutron star (NS) will precess if the instantaneous spin axis and the angular momentum are not aligned. Such a precession can produce continuous gravitational waves (GWs) and modulate electromagnetic pulse signals of pulsars. In this contribution we extend our previous work in a more convenient parameterization. We treat NSs as rigid triaxial bodies and give analytical solutions for angular velocities and Euler angles. We summarize the general GW waveforms from freely precessing triaxial NSs and use Taylor expansions to obtain waveforms with a small wobble angle. For pulsar signals, we adopt a simple cone model to study the timing residuals and pulse profile modulations. In reality, the electromagnetic torque acts on pulsars and affects the precession behavior. Thereof, as an additional extension to our previous work, we consider a vacuum torque and display an illustrative example for the residuals of body-frame angular velocities. Detailed investigations concerning continuous GWs and modulated pulsar signals from forced precession of triaixal NSs will be given in future studies.

astro-ph.HE↗

arXiv2020

Strong-field effects in massive scalar-tensor gravity for slowly spinning neutron stars and application to X-ray pulsar pulse profiles

Neutron stars (NSs) in scalar-tensor (ST) theories of gravitation can acquire scalar charges and generate distinct spacetimes from those in General Relativity (GR) through the celebrated phenomenon of spontaneous scalarization. Taking on an ST theory with the mass term of the scalar field, we determine the theory parameter space for spontaneous scalarization by investigating the linearized scalar field equation. Then the full numerical solutions for slowly rotating NSs are obtained and studied in great detail. The resulted spacetime is used to calculate test-particle geodesics. The lightlike geodesics are used to construct the profile of X-ray radiation from a pair of hot spots on the surface of scalarized NSs, which potentially can be compared with the data from the Neutron star Interior Composition Explorer (NICER) mission for testing the ST theory.

gr-qc↗

arXiv2020

Triaxially-deformed Freely-precessing Neutron Stars: Continuous electromagnetic and gravitational radiation

The shape of a neutron star (NS) is closely linked to its internal structure and the equation of state of supranuclear matters. A rapidly rotating, asymmetric NS in the Milky Way undergoes free precession, making it a potential source for multimessenger observation. The free precession could manifest in (i) the spectra of continuous gravitational waves (GWs) in the kilohertz band for ground-based GW detectors, and (ii) the timing behavior and pulse-profile characteristics if the NS is monitored as a pulsar with radio and/or X-ray telescopes. We extend previous work and investigate in great detail the free precession of a triaxially deformed NS with analytical and numerical approaches. In particular, its associated continuous GWs and pulse signals are derived. Explicit examples are illustrated for the continuous GWs, as well as timing residuals in both time and frequency domains. These results are ready to be used for future multimessenger observation of triaxially-deformed freely-precessing NSs, in order to extract scientific implication as much as possible.

astro-ph.HE↗

arXiv2020

Multiband Observation of LIGO/Virgo Binary Black Hole Mergers in the Gravitational-wave Transient Catalog GWTC-1

The Advanced LIGO and Virgo detectors opened a new era to study black holes (BHs) in our Universe. A population of stellar-mass binary BHs (BBHs) are discovered to be heavier than previously expected. These heavy BBHs provide us an opportunity to achieve multiband observation with ground-based and space-based gravitational-wave (GW) detectors. In this work, we use BBHs discovered by the LIGO/Virgo Collaboration as indubitable examples, and study in great detail the prospects for multiband observation with GW detectors in the near future. We apply the Fisher matrix to spinning, non-precessing inspiral-merger-ringdown waveforms, while taking the motion of space-based GW detectors fully into account. Our analysis shows that, detectors with decihertz sensitivity are expected to log stellar-mass BBH signals with very large signal-to-noise ratio, and provide accurate parameter estimation, including the sky location and time to coalescence. Furthermore, the combination of multiple detectors will achieve unprecedented measurement of BBH properties. As an explicit example, we present the multiband sensitivity to the generic dipole radiation for BHs, which is vastly important for the equivalence principle in the foundation of gravitation, in particular for those theories that predict curvature-induced scalarization of BHs.

astro-ph.HE↗

arXiv2016

Exploring triad-rich substructures by graph-theoretic characterizations in complex networks

One of the most important problems in complex networks is how to detect metadata groups accurately. The main challenge lies in the fact that traditional structural communities do not always capture the intrinsic features of metadata groups. Motivated by the observation that metadata groups in PPI networks tend to consist of an abundance of interacting triad motifs, we define a 2-club substructure with diameter 2 which possessing triad-rich property to describe a metadata group. Based on the triad-rich substructure, we design a DIVision Algorithm using our proposed edge Niche Centrality DIVANC to detect metadata groups effectively in complex networks. We also extend DIVANC to detect overlapping metadata groups by proposing a simple 2-hop overlapping strategy. To verify the effectiveness of triad-rich substructures, we compare DIVANC with existing algorithms on PPI networks, LFR synthetic networks and football networks. The experimental results show that DIVANC outperforms most other algorithms significantly and, in particular, can detect sparse metadata groups.

physics.soc-ph↗

arXiv2013

A Qualitative Representation and Similarity Measurement Method in Geographic Information Retrieval

The modern geographic information retrieval technology is based on quantitative models and methods. The semantic information in web documents and queries cannot be effectively represented, leading to information lost or misunderstanding so that the results are either unreliable or inconsistent. A new qualitative approach is thus proposed for supporting geographic information retrieval based on qualitative representation, semantic matching, and qualitative reasoning. A qualitative representation model and the corresponding similarity measurement method are defined. Information in documents and user queries are represented using propositional logic, which considers the thematic and geographic semantics synthetically. Thematic information is represented as thematic propositions on the base of domain ontology. Similarly, spatial information is represented as geo-spatial propositions with the support of geographic knowledge base. Then the similarity is divided into thematic similarity and spatial similarity. The former is calculated by the weighted distance of proposition keywords in the domain ontology, and the latter similarity is further divided into conceptual similarity and spatial similarity. Represented by propositions and information units, the similarity measurement can take evidence theory and fuzzy logic to combine all sub similarities to get the final similarity between documents and queries. This novel retrieval method is mainly used to retrieve the qualitative geographic information to support the semantic matching and results ranking. It does not deal with geometric computation and is consistent with human commonsense cognition, and thus can improve the efficiency of geographic information retrieval technology.

cs.IR↗

arXiv2013

Uncovering patterns of inter-urban trip and spatial interaction from social media check-in data

The article revisits spatial interaction and distance decay from the perspective of human mobility patterns and spatially-embedded networks based on an empirical data set. We extract nationwide inter-urban movements in China from a check-in data set that covers half million individuals and 370 cities to analyze the underlying patterns of trips and spatial interactions. By fitting the gravity model, we find that the observed spatial interactions are governed by a power law distance decay effect. The obtained gravity model also well reproduces the exponential trip displacement distribution. However, due to the ecological fallacy issue, the movement of an individual may not obey the same distance decay effect. We also construct a spatial network where the edge weights denote the interaction strengths. The communities detected from the network are spatially connected and roughly consistent with province boundaries. We attribute this pattern to different distance decay parameters between intra-province and inter-province trips.

cs.SI↗

arXiv2012

Phase Transition of Tractability in Constraint Satisfaction and Bayesian Network Inference

There has been great interest in identifying tractable subclasses of NP complete problems and designing efficient algorithms for these tractable classes. Constraint satisfaction and Bayesian network inference are two examples of such problems that are of great importance in AI and algorithms. In this paper we study, under the frameworks of random constraint satisfaction problems and random Bayesian networks, a typical tractable subclass characterized by the treewidth of the problems. We show that the property of having a bounded treewidth for CSPs and Bayesian network inference problem has a phase transition that occurs while the underlying structures of problems are still sparse. This implies that algorithms making use of treewidth based structural knowledge only work efficiently in a limited range of random instance.

cs.AI↗

arXiv2011

Bounded Search Tree Algorithms for Parameterized Cograph Deletion: Efficient Branching Rules by Exploiting Structures of Special Graph Classes

Many fixed-parameter tractable algorithms using a bounded search tree have been repeatedly improved, often by describing a larger number of branching rules involving an increasingly complex case analysis. We introduce a novel and general search strategy that branches on the forbidden subgraphs of a graph class relaxation. By using the class of $P_4$-sparse graphs as the relaxed graph class, we obtain efficient bounded search tree algorithms for several parameterized deletion problems. We give the first non-trivial bounded search tree algorithms for the cograph edge-deletion problem and the trivially perfect edge-deletion problems. For the cograph vertex deletion problem, a refined analysis of the runtime of our simple bounded search algorithm gives a faster exponential factor than those algorithms designed with the help of complicated case distinctions and non-trivial running time analysis [21] and computer-aided branching rules [11].

cs.DM↗