arXiv subjects

Junjie Cao

Publications and source records attributed to Junjie Cao.

At least 55 records · Page 3Linked to original sources

arXiv2022

Impact of recent $(g-2)_μ$ measurement on the light CP-even Higgs scenario in general Next-to-Minimal Supersymmetric Standard Model

The General Next-to-Minimal Supersymmetric Standard Model (GNMSSM) is an attractive theory that is free from the tadpole problem and the domain-wall problem of $Z_3$-NMSSM, and can form an economic secluded dark matter (DM) sector to naturally predict the DM experimental results. It also provides mechanisms to easily and significantly weaken the constraints from the LHC search for supersymmetric particles. These characteristics enable the theory to explain the recently measured muon anomalous magnetic moment, $(g-2)_μ$, in a broad parameter space that is consistent with all experimental results and at same time keeps the electroweak symmetry breaking natural. This work focuses on a popular scenario of the GNMSSM in which the next-to-lightest CP-even Higgs boson corresponds to the scalar discovered at the Large Hadron Collider (LHC). Both analytic formulae and a sophisticated numerical study show that in order to predict the scenario without significant tunings of relevant parameters, the Higgsino mass $μ_{tot} \lesssim 500~{\rm GeV}$ and $\tan β\lesssim 30$ are preferred. This character, if combined with the requirement to account for the $(g-2)_μ$ anomaly, will entail some light sparticles and make the LHC constraints very tight. As a result, this scenario can explain the muon anomalous magnetic moment in very narrow corners of its parameter space.

hep-ph↗

arXiv2021

Entity Relation Extraction as Dependency Parsing in Visually Rich Documents

Previous works on key information extraction from visually rich documents (VRDs) mainly focus on labeling the text within each bounding box (i.e., semantic entity), while the relations in-between are largely unexplored. In this paper, we adapt the popular dependency parsing model, the biaffine parser, to this entity relation extraction task. Being different from the original dependency parsing model which recognizes dependency relations between words, we identify relations between groups of words with layout information instead. We have compared different representations of the semantic entity, different VRD encoders, and different relation decoders. The results demonstrate that our proposed model achieves 65.96% F1 score on the FUNSD dataset. As for the real-world application, our model has been applied to the in-house customs data, achieving reliable performance in the production setting.

cs.CL↗

arXiv2021

Improved $(g-2)_μ$ measurement and singlino dark matter in $μ$-term extended $\mathbb{Z}_3$-NMSSM

Very recently, a Fermilab report of muon $g-2$ showed a $4.2σ$ discrepancy between it and the standard model (SM) prediction. Motivated by this inspiring result and the increasing tension in supersymmetric interpretation of the anomalous magnetic moment, it is argued that in the general next-to-minimal supersymmetric standard model (GNMSSM), a singlino-dominated neutralino can act as a feasible dark matter (DM) candidate in explaining the discrepancy naturally. In this case, the singlino-dominated DM and singlet-dominated Higgs bosons can form a secluded DM sector with $\tildeχ_1^0\tildeχ_1^0 \to h_s A_s$ responsible for the measured DM relic abundance. when $m_{\tildeχ_1^0} \gtrsim 150~{\rm GeV}$ and the Yukawa coupling $κ$ is around $0.2$. This sector communicates with the SM sector by weak singlet-doublet Higgs mixing, so the scatterings of the singlino-dominated DM with nucleons are suppressed. Furthermore, due to the singlet nature of the DM and the complex mass hierarchy, sparticle decay chains in the GNMSSM are lengthened in comparison with the prediction of the minimal supersymmetric standard model. These characteristics lead to sparticle detection at the Large Hadron Collider (LHC) being rather tricky. This study surveys a specific scenario of the GNMSSM, which extends the $\mathbb{Z}_3$-NMSSM by adding an explicit $μ$-term, to reveal the features. It indicates that the theory can readily explain the discrepancy of the muon anomalous magnetic moment without conflicting with the experimental results in DM and Higgs physics, and the LHC searches for sparticles.

hep-ph↗

arXiv2021

Electron and Muon Anomalous Magnetic Moments in the Inverse Seesaw Extended NMSSM

The recently improved observation of the fine structure constant has led to a negative $2.4σ$ anomaly of electron $g-2$. Combined with the long-existing positive $4.2σ$ discrepancy of the muon anomalous magnetic moment, it is interesting and difficult to explain these two anomalies with a consistent model without introducing flavor violations. We show that they can be simultaneously explained in the inverse seesaw extended next-to-minimal supersymmetric standard model (ISS-NMSSM) by the Higgsino--sneutrino contributions to $(g-2)_e$ and $(g-2)_μ$. The spectrum features prefer light $μ$, which can predict $m_Z$ naturally, and it is not difficult to obtain a $τ$-type sneutrino dark matter candidate that is compatible with the observed dark matter relic density and the bounds from dark matter direct detection experiments. Due to the compressed spectra and the undetectable decay mode of selectrons, they can evade the current Large Hadron Collider (LHC) constraints.

hep-ph↗

arXiv2021

HILONet: Hierarchical Imitation Learning from Non-Aligned Observations

It is challenging learning from demonstrated observation-only trajectories in a non-time-aligned environment because most imitation learning methods aim to imitate experts by following the demonstration step-by-step. However, aligned demonstrations are seldom obtainable in real-world scenarios. In this work, we propose a new imitation learning approach called Hierarchical Imitation Learning from Observation(HILONet), which adopts a hierarchical structure to choose feasible sub-goals from demonstrated observations dynamically. Our method can solve all kinds of tasks by achieving these sub-goals, whether it has a single goal position or not. We also present three different ways to increase sample efficiency in the hierarchical structure. We conduct extensive experiments using several environments. The results show the improvement in both performance and learning efficiency.

cs.LG↗

arXiv2021

Singlino-dominated dark matter in $Z_3$-NMSSM

Singlino-dominated dark matter properties are investigated in the $Z_3$ Next-to-Minimal Supersymmetric Standard Model, producing superweak interactions with nucleons involved in dark matter direct detection experiments. Approximate analytical formulas describing the dark matter abundance and cross section in the scattering with nucleons are used to illustrate a dependence on theoretical parameters in neutralino and Higgs sectors. It is shown that the measured abundance requires a sizable singlet--doublet Higgs coupling parameter $λ$, while the experimental detection results prefer a small $λ$. The parameter space is then surveyed using a nest sampling technique guided by a likelihood function containing various observables in dark matter, Higgs, and B physics, such as the abundance and the scattering cross section. It is demonstrated that dark matter can achieve the correct abundance through $\tildeχ_1^0 \tildeχ_1^0 \to t \bar{t}$ or co-annihilation with higgsinos. The former process provides significantly larger Bayesian evidence than the latter, but this will be examined by the near-future PandaX-4T experiment. If the experiment shows no signs of dark matter, it will become highly disfavored. Furthermore, four cases are summarized to suppress dark matter scattering with nucleons, namely, a small $λ$ and three kinds of cancellation between different contributions.

hep-ph↗

arXiv2021

Singlino-dominated dark matter in general NMSSM

The general Next-to-Minimal Supersymmetric Standard Model (NMSSM) describes the singlino-dominated dark-matter (DM) property by four independent parameters: singlet-doublet Higgs coupling coefficient $λ$, Higgsino mass $μ_{tot}$, DM mass $m_{\tildeχ_1^0}$, and singlet Higgs self-coupling coefficient $κ$. The first three parameters strongly influence the DM-nucleon scattering rate, while $κ$ usually affects the scattering only slightly. This characteristic implies that singlet-dominated particles may form a secluded DM sector. Under such a theoretical structure, the DM achieves the correct abundance by annihilating into a pair of singlet-dominated Higgs bosons by adjusting $κ$'s value. Its scattering with nucleons is suppressed when $λv/μ_{tot}$ is small. This speculation is verified by sophisticated scanning of the theory's parameter space with various experiment constraints considered. In addition, the Bayesian evidence of the general NMSSM and that of $Z_3$-NMSSM is computed. It is found that, at the cost of introducing one additional parameter, the former is approximately $3.3 \times 10^3$ times the latter. This result corresponds to Jeffrey's scale of 8.05 and implies that the considered experiments strongly prefer the general NMSSM to the $Z_3$-NMSSM.

hep-ph↗

arXiv2020

Impact of leptonic unitarity and dark matter direct detection experiments on the NMSSM with inverse seesaw mechanism

In the Next-to-Minimal Supersymmetric Standard Model with the inverse seesaw mechanism to generate neutrino masses, the lightest sneutrino may act as a feasible dark matter candidate in vast parameter space. In this case, the smallness of the leptonic unitarity violation and the recent XENON-1T experiment can limit the dark matter physics. In particular, they set upper bounds of the neutrino Yukawa couplings $λ_ν$ and $Y_ν$. We study such effects by encoding the constraints in a likelihood function and carrying out elaborated scans over the parameter space of the theory with the Nested Sampling algorithm. We show that these constraints are complementary to each other in limiting the theory, and in some cases, they are very strict. We also study the impact of the future LZ experiment on the theory.

hep-ph↗

arXiv2020

SMPR: Single-Stage Multi-Person Pose Regression

Existing multi-person pose estimators can be roughly divided into two-stage approaches (top-down and bottom-up approaches) and one-stage approaches. The two-stage methods either suffer high computational redundancy for additional person detectors or group keypoints heuristically after predicting all the instance-free keypoints. The recently proposed single-stage methods do not rely on the above two extra stages but have lower performance than the latest bottom-up approaches. In this work, a novel single-stage multi-person pose regression, termed SMPR, is presented. It follows the paradigm of dense prediction and predicts instance-aware keypoints from every location. Besides feature aggregation, we propose better strategies to define positive pose hypotheses for training which all play an important role in dense pose estimation. The network also learns the scores of estimated poses. The pose scoring strategy further improves the pose estimation performance by prioritizing superior poses during non-maximum suppression (NMS). We show that our method not only outperforms existing single-stage methods and but also be competitive with the latest bottom-up methods, with 70.2 AP and 77.5 AP75 on the COCO test-dev pose benchmark. Code is available at https://github.com/cmdi-dlut/SMPR.

cs.CV↗

arXiv2020

Moving Forward in Formation: A Decentralized Hierarchical Learning Approach to Multi-Agent Moving Together

Multi-agent path finding in formation has many potential real-world applications like mobile warehouse robots. However, previous multi-agent path finding (MAPF) methods hardly take formation into consideration. Furthermore, they are usually centralized planners and require the whole state of the environment. Other decentralized partially observable approaches to MAPF are reinforcement learning (RL) methods. However, these RL methods encounter difficulties when learning path finding and formation problem at the same time. In this paper, we propose a novel decentralized partially observable RL algorithm that uses a hierarchical structure to decompose the multi objective task into unrelated ones. It also calculates a theoretical weight that makes every task reward has equal influence on the final RL value function. Additionally, we introduce a communication method that helps agents cooperate with each other. Experiments in simulation show that our method outperforms other end-to-end RL methods and our method can naturally scale to large world sizes where centralized planner struggles. We also deploy and validate our method in a real world scenario.

cs.RO↗

arXiv2020

A Comparative Analysis of Knowledge-Intensive and Data-Intensive Semantic Parsers

We present a phenomenon-oriented comparative analysis of the two dominant approaches in task-independent semantic parsing: classic, knowledge-intensive and neural, data-intensive models. To reflect state-of-the-art neural NLP technologies, we introduce a new target structure-centric parser that can produce semantic graphs much more accurately than previous data-driven parsers. We then show that, in spite of comparable performance overall, knowledge- and data-intensive models produce different types of errors, in a way that can be explained by their theoretical properties. This analysis leads to new directions for parser development.

cs.CL↗

arXiv2020

Explaining The XENON1T Excess With Light Goldstini Dark Matter

In the scenario with a multiplicity of sectors which independently break supersymmetry, multiplicity of goldstini are predicted. We propose a new interpretation of the electron recoil excess at 2-7 keV observed in the XENON1T experiment with very long-lived goldstini DM elastically scattering off the electrons. The goldstini DM can be boosted by the late-decay of the other nearly degenerate (long-lived) goldstini DM, with their tiny mass difference being converted into kinetic energy of the lighter goldstini DM and neutrinos. We show that viable parameter space can be found which can explain the excess of electron recoil events around 2-3 keV recently reported by the XENON1T experiment.

hep-ph↗

arXiv2020

Anomalous Muon Magnetic Moment in the Inverse Seesaw Extended Next-to-Minimal Supersymmetric Standard Model

The present work investigates the possibility that both dark matter and the anomalous magnetic moment of the muon may be explained within the context of the inverse seesaw extended Next-to-Minimal Supersymmetric Standard Model (ISS-NMSSM). In ISS-NMSSM, the newly introduced Higgs-neutrino Yukawa coupling $Y_ν$ provides additional Higgsino-sneutrino loop contribution to $(g-2)_μ$. If the deviation between the experimental observations and the Standard Model predictions of the anomalous muon magnetic moment is confirmed by the further experimental and theoretical studies, it can be explained naturally within the ISS-NMSSM framework without conflicting with the current stringent limits on the direct detection of dark matter and Large Hadron Collider searches.

hep-ph↗

arXiv2020

Suppressing the Scattering of WIMP DM with Nucleons in Supersymmetric Theories

The continuously improving sensitivity of dark matter direct detection experiments has limited the interaction between dark matter and nucleons being increasingly feeble, while the dark matter relic density favors it to take part in weak interactions. After taking into account the constraints from the Large Hadron Collider (LHC) search for Higgs bosons and sparticles, it is becoming difficult for the neutralino dark matter in the Minimal Supersymmetric Standard Model and the Next-to-Minimal Supersymmetric Standard Model to possess these two seemingly paradoxical features in their most natural parameter space for electroweak symmetry breaking due to the limited theoretical structure. In contrast, the seesaw extension of the Next-to-Minimal Supersymmetric Standard Model, which was initially proposed to solve the neutrino mass problem, enables the lightest sneutrino to act as a viable dark matter candidate, readily has these features, and thus, it easily satisfies the constraints from dark matter and LHC experiments. Compared with the Type-I seesaw extension, the dark matter physics in the inverse seesaw extension is more flexible, allowing it to be consistent with the experimental results in broader parameter space. We conclude that weakly interacting massive particles (such as the sneutrino in this study) work well in supersymmetric theories as dark matter candidates.

hep-ph↗

arXiv2019

The 96 GeV Diphoton Excess in the Seesaw Extensions of the Natural NMSSM

The Next-to Minimal Supersymmetric Standard Model (NMSSM) with a Type-I seesaw mechanism extends the NMSSM by three generations of right-handed neutrino fields to generate neutrino mass. As a byproduct it renders the lightest sneutrino as a viable DM candidate. Due to the gauge singlet nature of the DM, its scattering with nucleon is suppressed in most cases to coincide spontaneously with the latest XENON-1T results. Consequently, broad parameter spaces in the Higgs sector, especially a light Higgsino mass, are resurrected as experimentally allowed, which makes the theory well suited to explain the long standing $b \bar{b}$ excess at LEP-II and the continuously observed $γγ$ excess by CMS collaboration. We show by both analytic formulas and numerical results that the theory can naturally predict the central values of the excesses in its broad parameter space, and the explanations are consistent with the Higgs data of the discovered Higgs boson, $B-$physics and DM physics measurements, the electroweak precision data as well as the LHC search for sparticles. Part of the explanations may be tested by future DM experiments and the SUSY search at the LHC.

hep-ph↗

arXiv2019

A Bayesian analysis of sneutrino DM in the NMSSM with Type-I seesaw mechanism

In the Next-to-Minimal Supersymmetric Standard Model (NMSSM) with extra heavy neutrino superfields, neutrino may acquire its mass via a seesaw mechanism and sneutrino may act as a viable dark matter (DM) candidate. Given the strong tension between the naturalness for $Z$ boson mass and the DM direct detection experiments for customary neutralino DM candidate, we augment the NMSSM with Type-I seesaw mechanism, which is the simplest extension of the theory to predict neutrino mass, and study the scenarios of sneutrino DM. We construct likelihood function with LHC Higgs data, B-physics measurements, DM relic density and its direct and indirect search limits, and perform a comprehensive scan over the parameter space of the theory by Nested Sampling method. We adopt both Bayesian and frequentist statistical quantities to illustrate the favored parameter space of the scenarios, the DM annihilation mechanism as well as the features of DM-nucleon scattering. We find that the scenarios are viable over broad parameter regions, especially the Higgsino mass $μ$ can be below about $250 {\rm GeV}$ for a significant part of the region, which predicts $Z$ boson mass in a natural way. We also find that the DM usually co-annihilated with the Higgsinos to get the measured relic density, and consequently the DM-nucleon scattering rate is naturally suppressed to coincide with the recent XENON-1T results even for light Higgsinos. Other issues, such as the LHC search for the Higgsinos, are also addressed.

hep-ph↗

arXiv2019

Current Status of Natural NMSSM in Light of LHC 13TeV Data and XENON-1T Results

In the natural realization of the Next-to-minimal Supersymmetric Standard Model, Higgsinos tend to be lighter than about several hundred GeVs, which can induce detectable leptonic signals at the LHC as well as large DM-nucleon scattering cross section. We explore the constraints from the direct searches for electroweakino and slepton at the LHC Run II and the latest DM direct detection experiments on the scenario with low fine tuning indicator $Δ_{Z/h} \leq 50$. We find that these experiments are complementary to each other in excluding the scenario, and as far as each kind of experiment is concerned, it is strong enough to exclude a large portion of the parameter space. As a result, the scenario with Bino- or Higgsino-dominated DM is disfavored, and that with Singlino-dominated DM is tightly limited. There are two regions in natural NMSSM parameter space surviving in the current experimental limits. One is featured with a decoupled Singlino-dominated LSP with $μ\simeq m_{\widetildeχ_1^0}$, which cannot be explored by neither DM detections or collider searches. The other parameter space region is featured by $10^{-47}~{\rm cm^2} \lesssim σ^{SI}_{\widetildeχ-p} \lesssim 10^{-46}~{\rm cm^2}$ and the correlation $μ\simeq m_{\widetildeχ_1^0}$, which will be explored by near future DM detection experiments.

hep-ph↗

arXiv2018

Explaining the DAMPE data with scalar dark matter and gauged $U(1)_{L_e-L_μ}$ interaction

Inspired by the peak structure observed by recent DAMPE experiment in $e^+e^-$ cosmic-ray spectrum, we consider a scalar dark matter (DM) model with gauged $U(1)_{L_e-L_μ}$ symmetry, which is the most economical anomaly-free theory to potentially explain the peak by DM annihilation in nearby subhalo. We utilize the process $χχ\to Z^\prime Z^\prime \to l \bar{l} l^\prime \bar{l}^\prime$, where $χ$, $Z^\prime$, $l^{(\prime)}$ denote the scalar DM, the new gauge boson and $l^{(\prime)} =e, μ$, respectively, to generate the $e^+e^-$ spectrum. By fitting the predicted spectrum to the experimental data, we obtain the favored DM mass range $m_χ\simeq 3060^{+80}_{-100} \, {\rm GeV}$ and $Δm \equiv m_χ- m_{Z^\prime} \lesssim 14 \, {\rm GeV}$ at $68\%$ Confidence Level (C.L.). Furthermore, we determine the parameter space of the model which can explain the peak and meanwhile satisfy the constraints from DM relic abundance, DM direct detection and the collider bounds. We conclude that the model we consider can account for the peak, although there exists a tension with the constraints from the LEP-II bound on $m_{Z^\prime}$ arising from the cross section measurement of $e^+e^- \to Z^{\prime\ast} \to e^+ e^-$.

hep-ph↗