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Researcher profile

Teng Ma

Teng Ma contributes to research discovery and scholarly infrastructure.

ResearcherAffiliation not importedOpen to collaborate
hep-phquant-phhep-thRoboticsArtificial IntelligenceComputation and LanguageComputer VisionDatabaseshep-exMultiagent Systemsphysics.app-ph

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Published work

19 published item(s)

preprint2026arXiv

SiriusHelper: An LLM Agent-Based Operations Assistant for Big Data Platforms

Big data platforms are widely used in modern enterprises, and an in-production intelligent assistant is increasingly important to help users quickly find actionable guidance and reduce operational burden. While recent LLM+RAG assistants provide a natural interface, they face practical challenges in real deployments: limited scenario coverage across both general consultation and domain-specific troubleshooting workflows, inefficient knowledge access due to inadequate multi-hop retrieval and flat knowledge organization, and high maintenance cost because escalated tickets are unstructured and hard to convert into assistant improvements and reusable SOPs. In this paper, we present SiriusHelper, a deployed intelligent assistant for big data platforms. SiriusHelper serves as a unified online assistant that automatically identifies user intent and routes queries to the right handling path, including dedicated expert workflows for specialized scenarios (e.g., SQL execution diagnosis). To support complex troubleshooting, SiriusHelper combines a DeepSearch-driven mechanism with a priority-based hierarchical knowledge base to enable multi-hop retrieval without context overload, thus improving answer reliability and latency. To reduce expert overhead, SiriusHelper further introduces automated ticket understanding and SOP distillation: it diagnoses the assistant failure reason (e.g., missing knowledge or wrong routing) and extracts domain-specific SOPs to continuously enrich the knowledge base. Experiments and online deployment on Tencent Big Data platform show that SiriusHelper outperforms representative alternatives and reduces online ticket volume by 20.8\%.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

A Piecewise Monotonic Gait Phase Estimation Model for Controlling a Powered Transfemoral Prosthesis in Various Locomotion Modes

Gait phase-based control is a trending research topic for walking-aid robots, especially robotic lower-limb prostheses. Gait phase estimation is a challenge for gait phase-based control. Previous researches used the integration or the differential of the human's thigh angle to estimate the gait phase, but accumulative measurement errors and noises can affect the estimation results. In this paper, a more robust gait phase estimation method is proposed using a unified form of piecewise monotonic gait phase-thigh angle models for various locomotion modes. The gait phase is estimated from only the thigh angle, which is a stable variable and avoids phase drifting. A Kalman filter-based smoother is designed to further suppress the mutations of the estimated gait phase. Based on the proposed gait phase estimation method, a gait phase-based joint angle tracking controller is designed for a transfemoral prosthesis. The proposed gait estimation method, the gait phase smoother, and the controller are evaluated through offline analysis on walking data in various locomotion modes. And the real-time performance of the gait phase-based controller is validated in an experiment on the transfemoral prosthesis.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Combating fluctuations in relaxation times of fixed-frequency transmon qubits with microwave-dressed states

With the long coherence time, the fixed-frequency transmon qubit is a promising qubit modality for quantum computing. Currently, diverse qubit architectures that utilize fixed-frequency transmon qubits have been demonstrated with high-fidelity gate performance. Nevertheless, the relaxation times of transmon qubits can have large temporal fluctuations, causing instabilities in gate performance. The fluctuations are often believed to be caused by nearly on-resonance couplings with sparse two-level-system (TLS) defects. To mitigate their impact on qubit coherence and gate performance, one direct approach is to tune the qubits away from these TLSs. In this work, to combat the potential TLS-induced performance fluctuations in a tunable-bus architecture unitizing fixed-frequency transmon qubits, we explore the possibility of using an off-resonance microwave drive to effectively tuning the qubit frequency through the ac-Stark shift while implementing universal gate operations on the microwave-dressed qubit. We show that the qubit frequency can be tuned up to 20 MHz through the ac-stark shift while keeping minimal impacts on the qubit control. Besides passive approaches that aim to remove these TLSs through more careful treatments of device fabrications, this work may offer an active approach towards mitigating the TLS-induced performance fluctuations in fixed-frequency transmon qubit devices.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Quantum circuit architecture search on a superconducting processor

Variational quantum algorithms (VQAs) have shown strong evidences to gain provable computational advantages for diverse fields such as finance, machine learning, and chemistry. However, the heuristic ansatz exploited in modern VQAs is incapable of balancing the tradeoff between expressivity and trainability, which may lead to the degraded performance when executed on the noisy intermediate-scale quantum (NISQ) machines. To address this issue, here we demonstrate the first proof-of-principle experiment of applying an efficient automatic ansatz design technique, i.e., quantum architecture search (QAS), to enhance VQAs on an 8-qubit superconducting quantum processor. In particular, we apply QAS to tailor the hardware-efficient ansatz towards classification tasks. Compared with the heuristic ansatze, the ansatz designed by QAS improves test accuracy from 31% to 98%. We further explain this superior performance by visualizing the loss landscape and analyzing effective parameters of all ansatze. Our work provides concrete guidance for developing variable ansatze to tackle various large-scale quantum learning problems with advantages.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

SuperLine3D: Self-supervised Line Segmentation and Description for LiDAR Point Cloud

Poles and building edges are frequently observable objects on urban roads, conveying reliable hints for various computer vision tasks. To repetitively extract them as features and perform association between discrete LiDAR frames for registration, we propose the first learning-based feature segmentation and description model for 3D lines in LiDAR point cloud. To train our model without the time consuming and tedious data labeling process, we first generate synthetic primitives for the basic appearance of target lines, and build an iterative line auto-labeling process to gradually refine line labels on real LiDAR scans. Our segmentation model can extract lines under arbitrary scale perturbations, and we use shared EdgeConv encoder layers to train the two segmentation and descriptor heads jointly. Base on the model, we can build a highly-available global registration module for point cloud registration, in conditions without initial transformation hints. Experiments have demonstrated that our line-based registration method is highly competitive to state-of-the-art point-based approaches. Our code is available at https://github.com/zxrzju/SuperLine3D.git.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

The Visual-Inertial-Dynamical Multirotor Dataset

Recently, the community has witnessed numerous datasets built for developing and testing state estimators. However, for some applications such as aerial transportation or search-and-rescue, the contact force or other disturbance must be perceived for robust planning and control, which is beyond the capacity of these datasets. This paper introduces a Visual-Inertial-Dynamical (VID) dataset, not only focusing on traditional six degrees of freedom (6-DOF) pose estimation but also providing dynamical characteristics of the flight platform for external force perception or dynamics-aided estimation. The VID dataset contains hardware synchronized imagery and inertial measurements, with accurate ground truth trajectories for evaluating common visual-inertial estimators. Moreover, the proposed dataset highlights rotor speed and motor current measurements, control inputs, and ground truth 6-axis force data to evaluate external force estimation. To the best of our knowledge, the proposed VID dataset is the first public dataset containing visual-inertial and complete dynamical information in the real world for pose and external force evaluation. The dataset: https://github.com/ZJU-FAST-Lab/VID-Dataset and related files: https://github.com/ZJU-FAST-Lab/VID-Flight-Platform are open-sourced.

0 citations0 reviewsNo code linkedOpen access
preprint2021arXiv

LUXE-NPOD: new physics searches with an optical dump at LUXE

We propose a novel way to search for feebly interacting massive particles, exploiting two properties of systems involving collisions between high energy electrons and intense laser pulses. The first property is that the electron-intense-laser collision results in a large flux of hard photons, as the laser behaves effectively as a thick medium. The second property is that the emitted photons free-stream inside the laser and thus for them the laser behaves effectively as a very thin medium. Combining these two features implies that the electron-intense-laser collision is an apparatus which can efficiently convert UV electrons to a large flux of hard, co-linear photons. We further propose to direct this unique large and hard flux of photons onto a physical dump which in turn is capable of producing feebly interacting massive particles, in a region of parameters that has never been probed before. We denote this novel apparatus as ``optical dump'' or NPOD (new physics search with optical dump). The proposed LUXE experiment at Eu.XFEL has all the required basic ingredients of the above experimental concept. We discuss how this concept can be realized in practice by adding a detector after the last physical dump of the experiment to reconstruct the two-photon decay product of a new spin-0 particle. We show that even with a relatively short dump, the search can still be background free. Remarkably, even with a 40 TW laser, which corresponds to the initial run, and definitely with a 350 TW laser, of the main run with one year of data taking, LUXE-NPOD will be able to probe uncharted territory of both models of pseudo-scalar and scalar fields, and in particular probe natural of scalar theories for masses above 100 MeV.

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

Characterization of bulk nanobubbles formed by using a porous alumina film with ordered nanopores

Gaseous nanobubbles (NBs), with their unique physicochemical properties and promising applications, have become an important research topic. Generation of monodispersed bulk NBs with specified gas content remains a challenge. We developed a simple method for generating bulk NBs, using porous alumina films with ordered straight nano-scaled holes. Different techniques, such as nanoparticle tracking analysis (NTA), atomic force microscopy (AFM), and infrared absorption spectroscopy (IRAS), are used to confirm NB formation. The NTA data demonstrates that the minimum size of the NBs formed is less than 100 nm, which is comparable to the diameter of nanoholes in the porous alumina film. By generating NBs with different gases, including CO2, O2, N2, Ar, and He, we discovered that the minimum size of NBs negatively correlated with the solubility of encapsulated gases in water. Due to the monodispersed size of NBs generated from the highly ordered porous alumina, we determined that NB size is distributed discretely with a uniform increment factor of sqrt(2). To explain the observed characteristic size distribution of NBs, we propose a simple model in which two NBs of the same size are assumed to preferentially coalesce. This characteristic bubble size distribution is useful for elucidating the basic characteristics of nanobubbles, such as the long-term stability of NBs. This distribution can also be used to develop new applications of NBs, for example, nano-scaled reaction fields through bubble coalescence.

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

Coherence Concurrence for X States

We study the properties of coherence concurrence and present a physical explanation analogous to the coherence of assistance. We give an optimal pure state decomposition which attains the coherence concurrence for qubit states. We prove the additivity of coherence concurrence under direct sum operations in another way. Using these results, we calculate analytically the coherence concurrence for X states and show its optimal decompositions. Moreover, we show that the coherence concurrence is exactly twice the convex roof extended negativity of the Schmidt correlated states, thus establishing a direct relation between coherence concurrence and quantum entanglement.

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

Keyphrase Extraction with Span-based Feature Representations

Keyphrases are capable of providing semantic metadata characterizing documents and producing an overview of the content of a document. Since keyphrase extraction is able to facilitate the management, categorization, and retrieval of information, it has received much attention in recent years. There are three approaches to address keyphrase extraction: (i) traditional two-step ranking method, (ii) sequence labeling and (iii) generation using neural networks. Two-step ranking approach is based on feature engineering, which is labor intensive and domain dependent. Sequence labeling is not able to tackle overlapping phrases. Generation methods (i.e., Sequence-to-sequence neural network models) overcome those shortcomings, so they have been widely studied and gain state-of-the-art performance. However, generation methods can not utilize context information effectively. In this paper, we propose a novelty Span Keyphrase Extraction model that extracts span-based feature representation of keyphrase directly from all the content tokens. In this way, our model obtains representation for each keyphrase and further learns to capture the interaction between keyphrases in one document to get better ranking results. In addition, with the help of tokens, our model is able to extract overlapped keyphrases. Experimental results on the benchmark datasets show that our proposed model outperforms the existing methods by a large margin.

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

Linear Response Theory of Entanglement Entropy

Linear response theory (LRT) is a key tool in investigating the quantum matter, for quantum systems perturbed by a weak probe, it connects the dynamics of experimental observable with the correlation function of unprobed equilibrium states. Entanglement entropy(EE) is a measure of quantum entanglement, it is a very important quantity of quantum physics and quantum information science. While EE is not an observable, developing the LRT of it is an interesting thing. In this work, we develop the LRT of von Neumann entropy for an open quantum system. Moreover, we found that the linear response of von Neumann entanglement entropy is determined by the linear response of an observable. Using this observable, we define the Kubo formula and susceptibility of EE, which have the same properties of its conventional counterpart. Through using the LRT of EE, we further found that the linear response of EE will be zero for maximally entangled or separable states, this is a unique feature of entanglement dynamics. A numerical verification of our analytical derivation is also given using XX spin chain model. The LRT of EE provides a useful tool in investigating and understanding EE.

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

Renormalization Group Evolution from On-shell SMEFT

We describe the on-shell method to deriving the Renormalization Group (RG) evolution of Wilson coefficients of high dimensional operators at one loop, which is a necessary part in the on-shell construction of the Standard Model Effective Field Theory (SMEFT), and exceptionally efficient based on the amplitude basis in hand. The UV divergence is obtained by firstly calculating the coefficients of scalar bubble integrals by unitary cuts, then subtracting the IR divergence in the massless bubbles, which can be easily read from the collinear factors we obtained for the Standard Model fields. Examples of deriving the anomalous dimensions at dimension six are presented in a pedagogical manner. We also give the results of contributions from the dimension-8 $H^4D^4$ operators to the running of $V^+V^-H^2$ operators, as well as the running of $B^+B^-H^2D^{2n}$ from $H^4D^{2n+4}$ for general $n$.

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

Stealth decaying spin-1 dark matter

We consider models of decaying spin-1 dark matter whose dominant coupling to the standard model sector is through a dark-Higgs Yukawa portal connecting a TeV-scale vector-like lepton to the standard model (right-handed) electron. Below the electron-positron threshold, dark matter has very slow, loop-suppressed decays to photons and (electron) neutrinos, and is stable on cosmological time-scale for sufficiently small gauge coupling values. Its relic abundance is set by in-equilibrium dark lepton decays, through the freeze-in mechanism. We show that this model accommodates the observed dark matter abundance for natural values of its parameters and a dark matter mass in the ~5keV to 1MeV range, while evading constraints from direct detection, indirect detection, stellar cooling and cosmology. We also consider the possibility of a nonzero gauge kinetic mixing with the standard model hypercharge field, which is found to yield a mild impact on the model's phenomenology.

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

The l1 Norm of Coherence of Assistance

We introduce and study the l1 norm of coherence of assistance both theoretically and operationally. We first provide an upper bound for the l1 norm of coherence of assistance and show a necessary and sufficient condition for the saturation of the upper bound. For two and three dimensional quantum states, the analytical expression of the l1 norm of coherence of assistance is given. Operationally, the mixed quantum coherence can always be increased with the help of another party' s local measurement and one way classical communication since the l1 norm of coherence of assistance, as well as the relative entropy of coherence of assistance, is shown to be strictly larger than the original coherence. The relation between the l1 norm of coherence of assistance and entanglement is revealed. Finally, a comparison between the l1 norm of coherence of assistance and the relative entropy of coherence of assistance is made.

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

Towards a fundamental safe theory of composite Higgs and Dark Matter

We present a novel paradigm that allows to define a composite theory at the electroweak scale that is well defined all the way up to any energy by means of safety in the UV. The theory flows from a complete UV fixed point to an IR fixed point for the strong dynamics (which gives the desired walking) before generating a mass gap at the TeV scale. We discuss two models featuring a composite Higgs, Dark Matter and partial compositeness for all SM fermions. The UV theories can also be embedded in a Pati-Salam partial unification, thus removing the instability generated by the $\mbox{U}(1)$ running. Finally, we find a Dark Matter candidate still allowed at masses of $260$ GeV, or $1.5 \sim 2$ TeV, where the latter mass range will be covered by next generation direct detection experiments.

0 citations0 reviewsNo code linkedOpen access
preprint2019arXiv

Generating a Higgs Quartic

We present a simple mechanism for generating a Higgs quartic in composite Higgs models without a corresponding quadratic term. The extra quartic will originate from a Higgs dependent kinetic mixing between additional fermionic states. The mechanism can be naturally embedded to models with maximal symmetry as well as Twin Higgs models. The resulting Twin Higgs models will have a fully natural realistic Higgs potential, where the quartic mechanism will serve as the only source for the $Z_2$ breaking, while the top and gauge sectors can remain exactly $Z_2$ invariant.

0 citations0 reviewsNo code linkedOpen access
preprint2019arXiv

The Left-Right Symmetric Composite Higgs

We find the exchange symmetry between left and right handed top quark in composite Higgs model with partial compositeness is efficient to soften the Higgs potential and reduce fine tuning. This symmetry can keep the Higgs potential in top sector invariant under trigonometric parity $\sin (h/f) \leftrightarrow \cos (h/f)$ and thus the Higgs quadratic divergences can be completely cancelled, resulting a UV insensitive Higgs potential. We explicitly construct the minimal left-right symmetric model based on coset space $SO(6)/SO(5)$ which is locally isomorphic to $SU(4)/Sp(4)$ and thus has well defined fermionic UV completion. This UV completion can automatically keep Higgs potential in gauge sector finite even the gauge sector breaks this discrete symmetry. We find that the vector mesons can be very heavy while the colored top partners are relatively light ($>1.5$ TeV) to obtain a light Higgs.

0 citations0 reviewsNo code linkedOpen access
preprint2018arXiv

Emergence of Maximal Symmetry

An emergent global symmetry of the composite sector (called maximal symmetry) can soften the ultraviolet behavior of the Higgs potential and also significantly modify its structure. We explain the conditions for the emergence of maximal symmetry as well as its main consequences. We present two simple implementations and generalize both to N-site as well as full warped extra dimensional models. The gauge symmetry of these models enforces the emergence of maximal symmetry. The corresponding Higgs potentials have unique properties: one case minimizes the tuning while the other allows heavy top partners evading direct LHC bounds.

0 citations0 reviewsNo code linkedOpen access
preprint2018arXiv

Six Top Messages of New Physics at the LHC

Six top signatures provide a novel probe of new physics. We discuss production of six top quarks as the decay products of a pair of top partners in the setting of a composite Higgs model, and argue that the six top signal may generically provide one of the first final states to show a discrepancy. We construct an analysis based on quantities such as $H_T$ and the numbers of jets which are tagged as boosted tops, $W$s, or containing $b$-tags, and show that the LHC with 3~ab$^{-1}$ can discover top partners with masses up to around 2.5 TeV in the six top signature.

0 citations0 reviewsNo code linkedOpen access