arXiv subjects

Tong Li

Publications and source records attributed to Tong Li.

At least 199 records · Page 11Linked to original sources

arXiv2021

Two Sample Unconditional Quantile Effect

This paper proposes a new framework to evaluate unconditional quantile effects (UQE) in a data combination model. The UQE measures the effect of a marginal counterfactual change in the unconditional distribution of a covariate on quantiles of the unconditional distribution of a target outcome. Under rank similarity and conditional independence assumptions, we provide a set of identification results for UQEs when the target covariate is continuously distributed and when it is discrete, respectively. Based on these identification results, we propose semiparametric estimators and establish their large sample properties under primitive conditions. Applying our method to a variant of Mincer's earnings function, we study the counterfactual quantile effect of actual work experience on income.

econ.EM↗

arXiv2021

Interpretation of the Galactic gamma-ray excess with the dark matter indicated by $^8$Be and $^4$He anomalous transitions

The long-standing Galactic center gamma-ray excess could be explained by GeV dark matter (DM) annihilation, while the DM interpretation seems in tension with recent joint limits from different astronomical scale observations, such as dwarf spheroidal galaxies, the Milky Way halo and galaxy groups/clusters. Motivated by $^8$Be and $^4$He anomalous transitions with possible new interactions mediated by a vector boson $X$, we consider a small fraction of DM mainly annihilating into a pair of on-shell vector boson $X X$ followed by $X \to e^+ e^-$ in this paper. The Galactic center gamma-ray excess is explained by this DM cascade annihilation. The gamma rays are mainly from Inverse Compton Scattering emission, and the DM cascade annihilation could be compatible with joint astrophysical limits and meanwhile be allowed by the AMS-02 positron observation. The direct detection of this model is also discussed.

hep-ph↗

arXiv2021

Microscopic origin of reflection-asymmetric nuclear shapes

Background: The presence of nuclear ground states with stable reflection-asymmetric shapes is supported by rich experimental evidence. Theoretical surveys of odd-multipolarity deformations predict the existence of pear-shaped isotopes in several fairly localized regions of the nuclear landscape in the vicinity of near-lying single-particle shells with $Δ\ell=Δj=3$. Purpose: We analyze the role of isoscalar, isovector, neutron-proton, neutron-neutron, and proton-proton multipole interaction energies in inducing the onset of reflection-asymmetric ground-state deformations. Methods: The calculations are performed in the framework of axial reflection-asymmetric Hartree-Fock-Bogoliubov theory using two Skyrme energy density functionals and density-dependent pairing force. Results: We show that reflection-asymmetric ground-state shapes of atomic nuclei are driven by the odd-multipolarity neutron-proton (or isoscalar) part of the nuclear interaction energy. This result is consistent with the particle-vibration picture, in which the main driver of octupole instability is the isoscalar octupole-octupole interaction giving rise to large $E3$ polarizability.

nucl-th↗

arXiv2021

Building Blocks of Sharding Blockchain Systems: Concepts, Approaches, and Open Problems

Sharding is the prevalent approach to breaking the trilemma of simultaneously achieving decentralization, security, and scalability in traditional blockchain systems, which are implemented as replicated state machines relying on atomic broadcast for consensus on an immutable chain of valid transactions. Sharding is to be understood broadly as techniques for dynamically partitioning nodes in a blockchain system into subsets (shards) that perform storage, communication, and computation tasks without fine-grained synchronization with each other. Despite much recent research on sharding blockchains, much remains to be explored in the design space of these systems. Towards that aim, we conduct a systematic analysis of existing sharding blockchain systems and derive a conceptual decomposition of their architecture into functional components and the underlying assumptions about system models and attackers they are built on. The functional components identified are node selection, epoch randomness, node assignment, intra-shard consensus, cross-shard transaction processing, shard reconfiguration, and motivation mechanism. We describe interfaces, functionality, and properties of each component and show how they compose into a sharding blockchain system. For each component, we systematically review existing approaches, identify potential and open problems, and propose future research directions. We focus on potential security attacks and performance problems, including system throughput and latency concerns such as confirmation delays. We believe our modular architectural decomposition and in-depth analysis of each component, based on a comprehensive literature study, provides a systematic basis for conceptualizing state-of-the-art sharding blockchain systems, proving or improving security and performance properties of components, and developing new sharding blockchain system designs.

cs.CR↗

arXiv2021

Loop effect in the coherent neutrino-nucleus scattering

A connection between the neutrino and an exotic fermion is described in the general neutrino model. In this model the neutrinos can convert into the new fermion and thus the interaction leads to novel recoil spectrum in the neutrino scattering experiments. We study the general neutrino interaction by evaluating both the tree-level and loop-level contributions to the coherent elastic neutrino-nucleus scattering. We illustrate the scattering by taking the framework of a simplified neutrino model with a Dirac fermion $χ$ and a spin-0 mediator. For the CP phase in the quark sector being 0 and $π/2$, the detection processes are dominated by the tree-level and loop-level contribution, respectively. We investigate the constraints on the couplings between the mediator and the new particle $χ$ or the quarks by fitting to the COHERENT data. The parameter space with $m_χ$ larger than the maximal energy of incoming neutrinos can be also constrained by including the loop-level contribution.

hep-ph↗

arXiv2021

C-Learning: Horizon-Aware Cumulative Accessibility Estimation

Multi-goal reaching is an important problem in reinforcement learning needed to achieve algorithmic generalization. Despite recent advances in this field, current algorithms suffer from three major challenges: high sample complexity, learning only a single way of reaching the goals, and difficulties in solving complex motion planning tasks. In order to address these limitations, we introduce the concept of cumulative accessibility functions, which measure the reachability of a goal from a given state within a specified horizon. We show that these functions obey a recurrence relation, which enables learning from offline interactions. We also prove that optimal cumulative accessibility functions are monotonic in the planning horizon. Additionally, our method can trade off speed and reliability in goal-reaching by suggesting multiple paths to a single goal depending on the provided horizon. We evaluate our approach on a set of multi-goal discrete and continuous control tasks. We show that our method outperforms state-of-the-art goal-reaching algorithms in success rate, sample complexity, and path optimality. Our code is available at https://github.com/layer6ai-labs/CAE, and additional visualizations can be found at https://sites.google.com/view/learning-cae/.

cs.LG↗

arXiv2021

Relation-aware Meta-learning for Market Segment Demand Prediction with Limited Records

E-commerce business is revolutionizing our shopping experiences by providing convenient and straightforward services. One of the most fundamental problems is how to balance the demand and supply in market segments to build an efficient platform. While conventional machine learning models have achieved great success on data-sufficient segments, it may fail in a large-portion of segments in E-commerce platforms, where there are not sufficient records to learn well-trained models. In this paper, we tackle this problem in the context of market segment demand prediction. The goal is to facilitate the learning process in the target segments by leveraging the learned knowledge from data-sufficient source segments. Specifically, we propose a novel algorithm, RMLDP, to incorporate a multi-pattern fusion network (MPFN) with a meta-learning paradigm. The multi-pattern fusion network considers both local and seasonal temporal patterns for segment demand prediction. In the meta-learning paradigm, transferable knowledge is regarded as the model parameter initialization of MPFN, which are learned from diverse source segments. Furthermore, we capture the segment relations by combining data-driven segment representation and segment knowledge graph representation and tailor the segment-specific relations to customize transferable model parameter initialization. Thus, even with limited data, the target segment can quickly find the most relevant transferred knowledge and adapt to the optimal parameters. We conduct extensive experiments on two large-scale industrial datasets. The results justify that our RMLDP outperforms a set of state-of-the-art baselines. Besides, RMLDP has been deployed in Taobao, a real-world E-commerce platform. The online A/B testing results further demonstrate the practicality of RMLDP.

cs.LG↗

arXiv2020

Document-aligned Japanese-English Conversation Parallel Corpus

Sentence-level (SL) machine translation (MT) has reached acceptable quality for many high-resourced languages, but not document-level (DL) MT, which is difficult to 1) train with little amount of DL data; and 2) evaluate, as the main methods and data sets focus on SL evaluation. To address the first issue, we present a document-aligned Japanese-English conversation corpus, including balanced, high-quality business conversation data for tuning and testing. As for the second issue, we manually identify the main areas where SL MT fails to produce adequate translations in lack of context. We then create an evaluation set where these phenomena are annotated to alleviate automatic evaluation of DL systems. We train MT models using our corpus to demonstrate how using context leads to improvements.

cs.CL↗

arXiv2020

Defect segregation and its effect on the photoelectrochemical properties of Ti-doped hematite photoanodes for solar water splitting

Optimising the photoelectrochemical performance of hematite photoanodes for solar water splitting requires better understanding of the relationships between dopant distribution, structural defects and photoelectrochemical properties. Here, we use complementary characterisation techniques including electron microscopy, conductive atomic force microscopy (CAFM), Rutherford backscattering spectroscopy (RBS), atom probe tomography (APT) and intensity modulated photocurrent spectroscopy (IMPS) to study this correlation in Ti-doped (1 cat.%) hematite films deposited by pulsed laser deposition (PLD) on F:SnO2 (FTO) coated glass substrates. The deposition was carried out at 300 °C, followed by annealing at 500 deg C for 2 h. Upon annealing, Ti was observed by APT to segregate to the hematite/FTO interface and into some hematite grains. Since no other pronounced changes in microstructure and chemical composition were observed by electron microscopy and RBS after annealing, the non-uniform Ti redistribution seems to be the reason for a reduced interfacial recombination in the annealed films, as observed by IMPS. This results in a lower onset potential, higher photocurrent and larger fill factor with respect to the as-deposited state. This work provides atomic-scale insights into the microscopic inhomogeneity in Ti-doped hematite thin films and the role of defect segregation in their electrical and photoelectrochemical properties.

physics.chem-ph↗

arXiv2020

Collapsing domain walls in the two-Higgs-doublet model and deep insights from the EDM

We study the domain wall solutions in the general two-Higgs-doublet model (2HDM) with a CP-violating phase. The 2HDM with the spontaneouse CP violation is found to have domain wall solutions whose tensions are $\mathcal{O}(10^6)\,{\rm GeV}^3$, which are excluded by the Zel'dovich-Kobzarev-Okun bound. With the explicit CP-violating (CPV) terms as the so-called biased term in the scalar potential, domain walls can collapse in the early Universe. The sizes of the explicit CP violation can be constrained from the Big Bang nucleosynthesis. This constraint is converted to the CPV mixing of $α_c$, and is mostly sensitive to the mass splittings between two heavy neutral Higgs bosons. We estimate the possible gravitational wave signals and the electric dipole moment (EDM) predictions due to the domain wall collapsing. It turns out that the peak spectrum of the GW from the domain wall collapsing cannot be probed in any future program. In contrast, the untenable regions with very tiny explicit CPV parameter in the Higgs potential has been partially excluded by the latest electron EDM measurements at the ACME-II and will be further confirmed or excluded by the future ACME-III projection.

hep-ph↗

arXiv2020

The future probe of the light Higgs boson pair production

In this work we study the light Higgs scenario in the framework of two Higgs doublet model (2HDM). In this case the heavier CP-even Higgs boson $H$ in 2HDM is the SM-like Higgs with 125 GeV mass and a CP-even Higgs boson $h$ lighter than 125 GeV exhibits in the spectrum. We find that this scenario exists in the alignment limit of $\sin(β-α)\simeq 0$ and is still allowed by the global fit of the 125 GeV Higgs and the direct searches for $H\to hh$ and $h\to γγ$. The case of $M_h M_H/2$ case and simulate the pair production of the light Higgs boson at the LHC. The pair production is sensitive to the soft $\mathbb{Z}_2$ symmetry breaking term $m_{12}$ in the 2HDM potential through the Higgs self-couplings. We find that the future high-luminosity LHC can discover the $b\bar{b}γγ$ signal in the region of $\tanβ\lesssim 1$ and $0<m_{12}<100$ GeV allowed by the theoretical constraints.

hep-ph↗

arXiv2020

Constraints on the charged currents in general neutrino interactions with sterile neutrinos

In this work we investigate the implication of low-energy precision measurements on the quark-lepton charged currents in general neutrino interactions with sterile neutrinos in effective field theories. The physics in low-energy measurements is described by the low-energy effective field theory extended with sterile neutrinos (LNEFT) defined below the electroweak scale. We also take into account renormalization group running and match the LNEFT onto the Standard Model (SM) effective field theory with sterile neutrinos (SMNEFT) to constrain new physics (NP) above the electroweak scale. The most sensitive low-energy probes are from leptonic decays of pseudoscalar mesons and hadronic tau lepton decays in terms of precise decay branching fractions, the lepton flavor universality and the Cabibbo-Kobayashi-Maskawa (CKM) unitarity. We also consider other constraints including nuclear beta decay. The constraints on charged current operators are generally stronger than the ones for quark-neutrino neutral current operators. We find that the most stringent bounds on the NP scale of lepton-number-conserving and lepton-number-violating operators in SMNEFT are 74 (110) TeV and 9.8 (13) TeV, respectively, for the operators with down (strange) quark.

hep-ph↗

arXiv2020

Nucleon localization function in rotating nuclei

Background: An electron localization function was originally introduced to visualize bond structures in molecules. It became a useful tool to describe electron configurations in atoms, molecules and solids. In nuclear physics, a nucleon localization function (NLF) has been used to characterize clusters in light nuclei, fragment formation in fission and pasta phases in the inner crust of neutron stars. Purpose: We use the NLF to study the nuclear response to fast rotation. Methods: We generalize the NLF to the case of nuclear rotation. The extended expressions involve both time-even and time-odd local densities. Since current density and density gradient contribute to the NLF primarily at the surface, we propose a simpler spatial measure given by the kinetic-energy density. Illustrative calculations for the superdeformed yrast band of $^{152}$Dy were carried out by using the cranked Skyrme-Hartree-Fock method. We also employed the cranked harmonic-oscillator model to gain insights into patterns revealed by the NLF at high angular momentum. Results: In a deformed rotating nucleus, several NLFs can be introduced, depending on the definition of the spin-quantization axis and self-consistent symmetries of the system. The oscillating pattern of the NLF can be explained by a constructive interference between the kinetic-energy and particle densities. The nodal pattern seen in the NLF along the major axis of a rotating nucleus comes from single-particle orbits with large aligned angular momentum. The variation of the NLF along the minor axis is traced back to deformation-aligned orbits. Conclusions: The NLF allows a simple interpretation of the shell structure evolution in the rotating nucleus in terms of the angular-momentum alignment of individual nucleons. We expect that the NLF will be useful for the characterization of other collective modes and time-dependent processes.

nucl-th↗

arXiv2020

Bluetooth-based COVID-19 Proximity Tracing Proposals: An Overview

Large-scale COVID-19 infections have occurred worldwide, which has caused tremendous impact on the economy and people's lives. The traditional method for tracing contagious virus, for example, determining the infection chain according to the memory of infected people, has many drawbacks. With the continuous spread of the pandemic, many countries or organizations have started to study how to use mobile devices to trace COVID-19, aiming to help people automatically record information about incidents with infected people through technologies, reducing the manpower required to determine the infection chain and alerting people at risk of infection. This article gives an overview on various Bluetooth-based COVID-19 proximity tracing proposals including centralized and decentralized proposals. We discussed the basic workflow and the differences between them before providing a survey of five typical proposals with explanations of their design features and benefits. Then, we summarized eight security and privacy design goals for Bluetooth-based COVID-19 proximity tracing proposals and applied them to analyze the five proposals. Finally, open problems and future directions are discussed.

cs.CR↗

arXiv2020

Large Time Behavior and Diffusion Limit for a System of Balance Laws From Chemotaxis in Multi-dimensions

We consider the Cauchy problem for a system of balance laws derived from a chemotaxis model with singular sensitivity in multiple space dimensions. Utilizing energy methods, we first prove the global well-posedness of classical solutions to the Cauchy problem when only the energy of the first order spatial derivatives of the initial data is sufficiently small, and the solutions are shown to converge to the prescribed constant equilibrium states as time goes to infinity. Then we prove that the solutions of the fully dissipative model converge to those of the corresponding partially dissipative model when the chemical diffusion coefficient tends to zero.

math.AP↗

arXiv2020

Designing the Business Conversation Corpus

While the progress of machine translation of written text has come far in the past several years thanks to the increasing availability of parallel corpora and corpora-based training technologies, automatic translation of spoken text and dialogues remains challenging even for modern systems. In this paper, we aim to boost the machine translation quality of conversational texts by introducing a newly constructed Japanese-English business conversation parallel corpus. A detailed analysis of the corpus is provided along with challenging examples for automatic translation. We also experiment with adding the corpus in a machine translation training scenario and show how the resulting system benefits from its use.

cs.CL↗

arXiv2020

General neutrino interactions with sterile neutrinos in light of coherent neutrino-nucleus scattering and meson invisible decays

In this work we study the current bounds from the CEνNS process and meson invisible decays on generic neutrino interactions with sterile neutrinos in effective field theories. The interactions between quarks and left-handed SM neutrinos and/or right-handed neutrinos are first described by the low-energy effective field theory (LNEFT) between the electroweak scale and the chiral symmetry breaking scale. We complete the independent operator basis for the LNEFT up to dimension-6 by including both the lepton-number-conserving (LNC) and lepton-number-violating (LNV) operators involving right-handed neutrinos. We translate the bounds on the LNEFT Wilson coefficients from the COHERENT observation and calculate the branching fractions of light meson invisible decays. The bounds on LNEFT are then mapped onto the SM effective field theory with sterile neutrinos (SMNEFT) to constrain new physics above the electroweak scale. We find that the meson invisible decays can provide the only sensitive probe for τ neutrino flavor component and s quark component in the quark-neutrino interactions involving two (one) active neutrinos and for the effective operators without any active neutrino fields. The CEνNS process places the most stringent bound on all other Wilson coefficients. By assuming one dominant Wilson coefficient at a time in SMNEFT and negligible sterile neutrino mass, the most stringent limits on the new physics scale are 2.7 - 10 TeV from corresponding dipole operator in LNEFT and 0.5 - 1.5 TeV from neutrino-quark operator in LNEFT.

hep-ph↗

arXiv2020

Edge Intelligence: Architectures, Challenges, and Applications

Edge intelligence refers to a set of connected systems and devices for data collection, caching, processing, and analysis in locations close to where data is captured based on artificial intelligence. The aim of edge intelligence is to enhance the quality and speed of data processing and protect the privacy and security of the data. Although recently emerged, spanning the period from 2011 to now, this field of research has shown explosive growth over the past five years. In this paper, we present a thorough and comprehensive survey on the literature surrounding edge intelligence. We first identify four fundamental components of edge intelligence, namely edge caching, edge training, edge inference, and edge offloading, based on theoretical and practical results pertaining to proposed and deployed systems. We then aim for a systematic classification of the state of the solutions by examining research results and observations for each of the four components and present a taxonomy that includes practical problems, adopted techniques, and application goals. For each category, we elaborate, compare and analyse the literature from the perspectives of adopted techniques, objectives, performance, advantages and drawbacks, etc. This survey article provides a comprehensive introduction to edge intelligence and its application areas. In addition, we summarise the development of the emerging research field and the current state-of-the-art and discuss the important open issues and possible theoretical and technical solutions.

cs.NI↗