arXiv subjects

Wei Bai

Publications and source records attributed to Wei Bai.

At least 19 recordsLinked to original sources

arXiv2025

BO-PBK: A comprehensive solver for dispersion relations of obliquely propagating waves in magnetized multi-species plasma with anisotropic loss-cone drift product-bi-kappa distribution

We present BO-PBK (BO-Product-Bi-Kappa), a new solver for kinetic dispersion relations of obliquely propagating waves in magnetized plasmas with complex velocity distributions. It reformulates the linearized Vlasov-Maxwell system into a compact eigenvalue problem, enabling direct computation of multiple wave branches and unstable modes without iterative initial-value searches. Key innovations include a unified framework supporting product-bi-kappa, kappa-Maxwellian, bi-Maxwellian, and hybrid distributions with multi-component and loss-cone features; a concise rational-form eigenvalue formulation; and a 2--3 times reduction in matrix dimensions compared to the BO-KM solver, with improved efficiency at larger kappa indices. Benchmark tests confirm accurate reproduction of standard kinetic results and efficient resolution of waves and instabilities. BO-PBK thus provides a computationally efficient tool for wave and stability analysis in space and laboratory plasmas.

physics.plasm-ph↗

arXiv2025

Ultrafast dynamics of three-dimensional Kane plasmons in the narrow-bandgap Hg$_{0.8}$Cd$_{0.2}$Te

We report on an ultrafast terahertz spectroscopic study on the dynamics of free carriers and the pertinent bulk plasmons in Hg$_{0.8}$Cd$_{0.2}$Te (MCT) film, a narrowband semiconductor accommodating three dimensional massless Kane fermions. The ultrabroadband terahertz source enables the investigation of the lightly doped equilibrium state in the presence of plasmon-phonon hybridization through the heavily doped excited state, primarily dominated by plasmons. Without the recourse to the resource consuming cryogenic high magnetic field spectroscopy that hinges on observable related to the interband transition, we show that the massless band dispersion can instead be conveniently perceived by the room temperature study of the intraband transition through the determination of the plasmon carrier density relationship. We found the plasma frequency in MCT scales with the cube root of carrier density, in contrast with the square root scaling in the conventional massive fermion system of parabolic band dispersion. This work also answers the curious question of whether the MCT can maintain its massless Kane fermion character in case the strict gapless condition is deviated from. The method presented herein provides a convenient approach to identifying the landscape of both massless and massive band dispersion.

cond-mat.mtrl-sci↗

arXiv2024

Lazarus: Resilient and Elastic Training of Mixture-of-Experts Models

Sparsely-activated Mixture-of-Experts (MoE) architecture has increasingly been adopted to further scale large language models (LLMs). However, frequent failures still pose significant challenges as training scales. The cost of even a single failure is significant, as all GPUs need to idle wait until the failure is resolved, potentially losing considerable training progress as training has to restart from checkpoints. This problem is exacerbated by the growing use of spot instances on public clouds for model training, which despite offering substantial cost savings, introduce frequent preemptions-essentially failures that regularly occur throughout the training process. Existing solutions for efficient fault-tolerant training either lack elasticity or rely on building resiliency into pipeline parallelism, which cannot be applied to MoE models due to the expert parallelism strategy adopted by the MoE architecture. We present Lazarus, a system for resilient and elastic training of MoE models. Lazarus adaptively allocates expert replicas to address the inherent imbalance in expert workload and speeds up training, while a provably optimal expert placement algorithm is developed to maximize the probability of recovery upon failures. Through adaptive expert placement and a flexible token dispatcher, Lazarus can also fully utilize all available nodes after failures, leaving no GPU idle. Our evaluation shows that Lazarus outperforms existing MoE training systems by up to 5.7x under frequent node failures and 3.4x on a real spot instance trace.

cs.DC↗

arXiv2022

The Gender Pay Gap in China: Insights from a Discrimination Perspective

Equal pay is an essential component of gender equality, one of the Sustainable Development Goals of the United Nations. Using resume data of over ten million Chinese online job seekers in 2015, we study the current gender pay gap in China. The results show that on average women only earned 71.57\% of what men earned in China. The gender pay gap exists across all age groups and educational levels. Contrary to the commonly held view that developments in education, economy, and a more open culture would reduce the gender pay gap, the fusion analysis of resume data and socio-economic data presents that they have not helped reach the gender pay equality in China. China seems to be stuck in a place where traditional methods cannot make further progress. Our analysis further shows that 81.47\% of the variance in the gender pay gap can be potentially attributed to discrimination. In particular, compared with the unmarried, both the gender pay gap itself and proportion potentially attributed to discrimination of the married are larger, indicating that married women suffer greater inequality and more discrimination than unmarried ones. Taken together, we suggest that more research attention should be paid to the effect of discrimination in understanding gender pay gap based on the family constraint theory. We also suggest the Chinese government to increase investment in family-supportive policies and grants in addition to female education.

physics.soc-ph↗

arXiv2022

Jumping to male-dominated occupations: A novel way to reduce gender wage gap for Chinese women

Occupational segregation is widely considered as one major reason leading to the gender discrimination in labor market. Using large-scale Chinese resume data of online job seekers, we uncover an interesting phenomenon that occupations with higher proportion of men have smaller gender wage gap measured by the female-male ratio on wage. We further show that the severity of occupational segregation in China is low both overall and regionally, and the inter-occupational discrimination is much smaller than the intra-occupational discrimination. That is to say, Chinese women do not face large barriers when changing their occupations. Accordingly, we suggest Chineses women a new way to narrow the gender wage gap: to join male-dominated occupations. Meanwhile, it is worth noticing that although the gender wage gap is smaller in male-dominated occupations, it does not mean that the gender discrimination is smaller there.

physics.soc-ph↗

arXiv2021

Discover the Hidden Attack Path in Multi-domain Cyberspace Based on Reinforcement Learning

In this work, we present a learning-based approach to analysis cyberspace security configuration. Unlike prior methods, our approach has the ability to learn from past experience and improve over time. In particular, as we train over a greater number of agents as attackers, our method becomes better at discovering hidden attack paths for previously methods, especially in multi-domain cyberspace. To achieve these results, we pose discovering attack paths as a Reinforcement Learning (RL) problem and train an agent to discover multi-domain cyberspace attack paths. To enable our RL policy to discover more hidden attack paths and shorter attack paths, we ground representation introduction an multi-domain action select module in RL. Our objective is to discover more hidden attack paths and shorter attack paths by our proposed method, to analysis the weakness of cyberspace security configuration. At last, we designed a simulated cyberspace experimental environment to verify our proposed method, the experimental results show that our method can discover more hidden multi-domain attack paths and shorter attack paths than existing baseline methods.

cs.CR↗

arXiv2020

Quantitative Evaluations on Saliency Methods: An Experimental Study

It has been long debated that eXplainable AI (XAI) is an important topic, but it lacks rigorous definition and fair metrics. In this paper, we briefly summarize the status quo of the metrics, along with an exhaustive experimental study based on them, including faithfulness, localization, false-positives, sensitivity check, and stability. With the experimental results, we conclude that among all the methods we compare, no single explanation method dominates others in all metrics. Nonetheless, Gradient-weighted Class Activation Mapping (Grad-CAM) and Randomly Input Sampling for Explanation (RISE) perform fairly well in most of the metrics. Utilizing a set of filtered metrics, we further present a case study to diagnose the classification bases for models. While providing a comprehensive experimental study of metrics, we also examine measuring factors that are missed in current metrics and hope this valuable work could serve as a guide for future research.

cs.AI↗

arXiv2020

Domain-specific Communication Optimization for Distributed DNN Training

Communication overhead poses an important obstacle to distributed DNN training and draws increasing attention in recent years. Despite continuous efforts, prior solutions such as gradient compression/reduction, compute/communication overlapping and layer-wise flow scheduling, etc., are still coarse-grained and insufficient for an efficient distributed training especially when the network is under pressure. We present DLCP, a novel solution exploiting the domain-specific properties of deep learning to optimize communication overhead of DNN training in a fine-grained manner. At its heart, DLCP comprises of several key innovations beyond prior work: e.g., it exploits {\em bounded loss tolerance} of SGD-based training to improve tail communication latency which cannot be avoided purely through gradient compression. It then performs fine-grained packet-level prioritization and dropping, as opposed to flow-level scheduling, based on layers and magnitudes of gradients to further speedup model convergence without affecting accuracy. In addition, it leverages inter-packet order-independency to perform per-packet load balancing without causing classical re-ordering issues. DLCP works with both Parameter Server and collective communication routines. We have implemented DLCP with commodity switches, integrated it with various training frameworks including TensorFlow, MXNet and PyTorch, and deployed it in our small-scale testbed with 10 Nvidia V100 GPUs. Our testbed experiments and large-scale simulations show that DLCP delivers up to $84.3\%$ additional training acceleration over the best existing solutions.

cs.DC↗

arXiv2020

Weakness Analysis of Cyberspace Configuration Based on Reinforcement Learning

In this work, we present a learning-based approach to analysis cyberspace configuration. Unlike prior methods, our approach has the ability to learn from past experience and improve over time. In particular, as we train over a greater number of agents as attackers, our method becomes better at rapidly finding attack paths for previously hidden paths, especially in multiple domain cyberspace. To achieve these results, we pose finding attack paths as a Reinforcement Learning (RL) problem and train an agent to find multiple domain attack paths. To enable our RL policy to find more hidden attack paths, we ground representation introduction an multiple domain action select module in RL. By designing a simulated cyberspace experimental environment to verify our method. Our objective is to find more hidden attack paths, to analysis the weakness of cyberspace configuration. The experimental results show that our method can find more hidden multiple domain attack paths than existing baselines methods.

cs.AI↗

arXiv2020

Preliminary prediction of the basic reproduction number of the Wuhan novel coronavirus 2019-nCoV

Objectives.--To estimate the basic reproduction number of the Wuhan novel coronavirus (2019-nCoV). Methods.--Based on the susceptible-exposed-infected-removed (SEIR) compartment model and the assumption that the infectious cases with symptoms occurred before January 25, 2020 are resulted from free propagation without intervention, we estimate the basic reproduction number of 2019-nCoV according to the reported confirmed cases and suspected cases, as well as the theoretical estimated number of infected cases by other research teams, together with some epidemiological determinants learned from the severe acute respiratory syndrome. Results The basic reproduction number falls between 2.8 to 3.3 by using the real-time reports on the number of 2019-nCoV infected cases from People's Daily in China, and falls between 3.2 and 3.9 on the basis of the predicted number of infected cases from colleagues. Conclusions.--The early transmission ability of 2019-nCoV is closed to or slightly higher than SARS. It is a controllable disease with moderate-high transmissibility. Timely and effective control measures are needed to suppress the further transmissions. Notes Added.--Using a newly reported epidemiological determinants for early 2019-nCoV, the estimated basic reproduction number is in the range [2.2,3.0].

q-bio.PE↗

arXiv2019

All-optical switch and logic gates based on all-dielectric hybrid silicon-Ge2Sb2Te5 metamaterials

We numerically propose an all-dielectric hybrid metamaterial (MM) to realize all-optical switch and logic gates in shortwave infrared (SWIR) band. Such MM consists of one silicon rod and one Ge2Sb2Te5 (GST) rod pair. Utilizing the transition from amorphous to crystalline state of GST, such MM can produce electromagnetically induced transparency (EIT) analogue with active control. Based on this, we realized all-optical switching at 1500 nm with a modulation depth 84%. Besides, three different logic gates, NOT, NOR and OR, can also be achieved in this device simultaneously. Thanks to the reversible and fast phase transition process of GST, this device possesses reconfigurable ability as well as fast response time, and has potential applications in future optical networks.

physics.optics↗

arXiv2019

Chipscale plasmonic modulators and switches based on metal-insulator-metal waveguides with Ge2Sb2Te5

We introduce phase-change material Ge2Sb2Te5 (GST) into metal-insulator-metal (MIM) waveguide systems to realize chipscale plasmonic modulators and switches in the telecommunication band. Benefitting from the high contrast of optical properties between amorphous and crystalline GST, the three proposed structures can act as reconfigurable and non-volatile modulators and switches with excellent modulation depth 14 dB and fast response time in nanosecond, meanwhile possessing small footprints, simple frameworks and easy fabrication. This work provides new solutions to design active devices in MIM waveguide systems, and can find potential applications in more compact all-optical circuits for information processing and storage.

physics.app-ph↗

arXiv2017

Ferroelectric control of the giant Rashba spin orbit coupling in GeTe(111)/InP(111) superlattice

GeTe wins the renewed research interest due to its giant bulk Rashba spin orbit coupling (SOC), and becomes the father of a new multifunctional material, i.e., ferroelectric Rashba semiconductor. In the present work, we investigate Rashba SOC at the interface of the ferroelectric semiconductor superlattice GeTe(111)/InP(111) by using the first principles calculation. Contribution of the interface electric field and the ferroelectric field to Rashba SOC is revealed. A large modulation to Rashba SOC and a reversal of the spin polarization is obtained by switching the ferroelectric polarization. Our investigation about GeTe(111)/InP(111) superlattice is of great importance in the application of ferroelectric Rashba semiconductor in the spin field effect transistor.

cond-mat.mtrl-sci↗

arXiv2016

Cohomology of Heisenberg Lie Superalgebras

Suppose the ground field to be algebraically closed and of characteristic different from $2$ and $3$. All Heisenberg Lie superalgebras consist of two super versions of the Heisenberg Lie algebras, $\frak{h}_{2m,n}$ and $\frak{ba}_n$ with $m$ a nonnegative integer and $n$ a positive integer. The space of a "classical" Heisenberg Lie superalgebra $\frak{h}_{2m,n}$ is the direct sum of a superspace with a non-degenerate anti-supersymmetric even bilinear form and a one-dimensional space of values of this form constituting the even center. The other super analog of the Heisenberg Lie algebra, $\frak{ba}_n$, is constructed by means of a non-degenerate anti-supersymmetric odd bilinear form with values in the one-dimensional odd center. In this paper, we study the cohomology of $\frak{h}_{2m,n}$ and $\frak{ba}_n$ with coefficients in the trivial module by using the Hochschild-Serre spectral sequences relative to a suitable ideal. In characteristic zero case, for any Heisenberg Lie superalgebra, we determine completely the Betti numbers and associative superalgebra structure for their cohomology. In characteristic $p>3$ case, we determine the associative superalgebra structures for the divided power cohomology of $\frak{ba}_n$ and we also make an attempt to determine the cohomology of $\frak{h}_{2m,n}$ by computing it in a low-dimensional case.

math.RA↗

arXiv2014

RepNet: Cutting Tail Latency in Data Center Networks with Flow Replication

Data center networks need to provide low latency, especially at the tail, as demanded by many interactive applications. To improve tail latency, existing approaches require modifications to switch hardware and/or end-host operating systems, making them difficult to be deployed. We present the design, implementation, and evaluation of RepNet, an application layer transport that can be deployed today. RepNet exploits the fact that only a few paths among many are congested at any moment in the network, and applies simple flow replication to mice flows to opportunistically use the less congested path. RepNet has two designs for flow replication: (1) RepSYN, which only replicates SYN packets and uses the first connection that finishes TCP handshaking for data transmission, and (2) RepFlow which replicates the entire mice flow. We implement RepNet on {\tt node.js}, one of the most commonly used platforms for networked interactive applications. {\tt node}'s single threaded event-loop and non-blocking I/O make flow replication highly efficient. Performance evaluation on a real network testbed and in Mininet reveals that RepNet is able to reduce the tail latency of mice flows, as well as application completion times, by more than 50\%.

cs.NI↗

arXiv2014

Enabling Automatic Certification of Online Auctions

We consider the problem of building up trust in a network of online auctions by software agents. This requires agents to have a deeper understanding of auction mechanisms and be able to verify desirable properties of a given mechanism. We have shown how these mechanisms can be formalised as semantic web services in OWL-S, a good enough expressive machine-readable formalism enabling software agents, to discover, invoke, and execute a web service. We have also used abstract interpretation to translate the auction's specifications from OWL-S, based on description logic, to COQ, based on typed lambda calculus, in order to enable automatic verification of desirable properties of the auction by the software agents. For this language translation, we have discussed the syntactic transformation as well as the semantics connections between both concrete and abstract domains. This work contributes to the implementation of the vision of agent-mediated e-commerce systems.

cs.LO↗

arXiv2013

Revisiting $Kπ$ puzzle in the pQCD factorization approach

In this paper, we calculated the branching ratios and direct CP violation of the four $B\to Kπ$ decays with the inclusion of all currently known next-to-leading order (NLO) contributions by employing the perturbative QCD (pQCD) factorization approach. We found that (a) Besides the 10% enhancement from the NLO vertex corrections, the quark-loops and magnetic penguins, the NLO contributions to the form factors can provide an additional $\sim 15%$ enhancement to the branching ratios, and lead to a very good agreement with the data; (b) The NLO pQCD predictions are $\acp^{dir}(B^0\to K^+π^-)=(-6.5\pm 3.1)%$ and $\acp^{dir}(B^+\to K^+ π^0)=(2.2\pm 2.0)%$, become well consistent with the data due to the inclusion of the NLO contributions.

hep-ph↗

arXiv2013

Maximal Subalgebras for Lie Superalgebras of Cartan Type

The maximal graded subalgebras for four families of Lie superalgebras of Cartan type over a field of prime characteristic are studied. All maximal reducible graded subalgebras are described completely and their isomorphism classes, dimension formulas are found. The classification of maximal irreducible graded subalgebras is reduced to the classification of the maximal irreducible subalgebras for the classical Lie superalgebras $\frak{gl}(m,n)$, $\frak{sl}(m,n)$ and $\frak{osp}(m,n)$.

math.RA↗