Point cloud classification is one of the essential technologies for achieving intelligent perception of 3D environments by machines, its core challenge is to efficiently extract local and global features. Mamba leverages state space models (SSMs) for global point cloud modeling. Although prior Mamba-based point cloud processing methods pay attention to the limitation of its flattened sequence modeling mechanism in fusing local and global features, the critical issue of weakened local geometric relevance caused by decoupling geometric structures and features in the input patches remains not fully revealed, and both jointly limit local feature extraction. Therefore, we propose HyMamba, a geometry and feature coupled Mamba framework featuring: (1) Geometry-Feature Coupled Pooling (GFCP), which achieves physically interpretable geometric information coupling by dynamically aggregating adjacent geometric information into local features; (2) Collaborative Feature Enhancer (CoFE), which enhances sparse signal capture through cross-path feature hybridization while effectively integrating global and local contexts. We conducted extensive experiments on ModelNet40 and ScanObjectNN datasets. The results demonstrate that the proposed model achieves superior classification performance, particularly on the ModelNet40, where it elevates accuracy to 95.99% with merely 0.03M additional parameters. Furthermore, it attains 98.9% accuracy on the ModelNetFewShot dataset, validating its robust generalization capabilities under sparse samples. Our code and weights are available at this https URL

The dark photon is a well motivated candidate for the dark matter which comprises most of the mass of our visible Universe, leading to worldwide experimental and observational efforts towards its discovery. A primary tool in this search is the cavity haloscope, which facilitates resonantly enhanced conversion to photons from both dark photons and axions. In this context, limits from axion search experiments are often directly converted into dark photon constraints, without re-analyzing the original data. However, this rescaling may not fully capture all of the relevant physics due to various reasons. By re-examining data taken by the Taiwan Axion Search Experiment with Haloscope (TASEH) experiment, we derive a world-leading constraint on the dark photon parameter space, excluding $|\epsilon|\gtrsim2\times10^{-14}$ in the $19.46 - 19.84\,\mu$eV mass range, which exceeds the naive `rescaling limit' by roughly one order of magnitude. In this data, we also identify a tentative signal with a local significance of 4.7$\sigma$, previously disregarded due to an axion-specific veto, corresponding to a dark photon with mass $m_X \simeq 19.5\,\mu$eV ($f_X\simeq 4.71$ GHz) and kinetic mixing $\epsilon \simeq 6.5\times10^{-15}$.

Intracity heavy truck freight trips are basic data in city freight system planning and management. In the big data era, massive heavy truck GPS trajectories can be acquired cost effectively in real-time. Identifying freight trip ends (origins and destinations) from heavy truck GPS trajectories is an outstanding problem. Although previous studies proposed a variety of trip end identification methods from different perspectives, these studies subjectively defined key threshold parameters and ignored the complex intracity heavy truck travel characteristics. Here, we propose a data-driven trip end identification method in which the speed threshold for identifying truck stops and the multilevel time thresholds for distinguishing temporary stops and freight trip ends are objectively defined. Moreover, an appropriate time threshold level is dynamically selected by considering the intracity activity patterns of heavy trucks. Furthermore, we use urban road networks and point-of-interest (POI) data to eliminate misidentified trip ends to improve method accuracy. The validation results show that the accuracy of the method we propose is 87.45%. Our method incorporates the impact of the city freight context on truck trajectory characteristics, and its results can reflect the spatial distribution and chain patterns of intracity heavy truck freight trips, which have a wide range of practical applications.

We propose the generic high-quality axion models with anomalous $U(1)_X$ gauge symmetry and vector-like particles. We briefly review the gauge anomaly cancellations via the Green-Schwarz mechanism, study the breaking of the $U(1)_X$ gauge symmetry, as well as derive the Nambu-Goldstone boson, Peccei-Quinn (PQ) axion, and axion decay constant in general. The high-dimensional operators, which break the $U(1)_{PQ}$ global symmetry, have dimension eleven or higher due to the anomalous $U(1)_X$ gauge symmetry, and thus the axion quality problem is solved. In particular, unlike the high-quality axion models with anomaly free $U(1)$ gauge symmetry, we only need to introduce two pairs of vector-like particles. To be concrete, we present three specific models with two pairs of vector-like particles. We show that gauge anomalies in all three models can be canceled via the Green-Schwarz mechanism. To achieve gauge coupling unification, we need to introduce additional vector-like particles only in Model I. We find that gauge coupling unification is achieved at the unification scale around $10^{16}$ GeV with a relative error of less than 1\%. Notably, gauge coupling unification in Model II is achieved naturally with the smallest relative error of 0.1\%.

Solar greenhouses are crucial infrastructure of modern agricultural production in northern China. However, highly fluctuating temperature in winter season results in poor greenhouse temperature control, which affects crop growth and increases energy consumption. To tackle these challenges, an advanced control system that can efficiently optimize multiple objectives under dramatic climate conditions is essential. Therefore, this study propose a model predictive control-coupled proximal policy optimization (MPC-PPO) control framework. A teacher-student control framework is constructed in which the MPC generating high-quality control experiences to guide the PPO agent's learning process. An adaptive dynamic weighting mechanism is employed to balance the influence of MPC experiences during PPO training. Evaluation conducted in solar greenhouses across three provinces in northern China (Beijing, Hebei, and Shandong) demonstrates that: (1) the MPC-PPO method achieved the highest temperature control performance (96.31 on a 100-point scale), with a 5.46-point improvement compared to the non-experience integration baseline, when reduced standard deviation by nearly half and enhanced exploration efficiency; (2) the MPC-PPO method achieved a ventilation control reward of 99.19, optimizing ventilation window operations with intelligent time-differentiated strategies that reduced energy loss during non-optimal hours; (3) feature analysis reveals that historical window opening, air temperature, and historical temperature are the most influential features for effective control, i.e., SHAP values of 7.449, 4.905, and 4.747 respectively; and (4) cross-regional tests indicated that MPC-PPO performs best in all test regions, confirming generalization of the method.

Second-order topological superconductors host Majorana corner and hingemodes in contrast to conventional edge and surface modes in two and three dimensions. However, the realization of such second-order corner modes usually demands unconventional superconducting pairing or complicated junctions or layered structures. Here we show that Majorana corner modes could be realized using a 2D quantum spin Hall insulator in proximity contact with an $s$-wave superconductor and subject to an in-plane Zeeman field. Beyond a critical value, the in-plane Zeeman field induces opposite effective Dirac masses between adjacent boundaries, leading to one Majorana mode at each corner. A similar paradigm also applies to 3D topological insulators with the emergence of Majorana hinge states. Avoiding complex superconductor pairing and material structure, our scheme provides an experimentally realistic platform for implementing Majorana corner and hinge states.

We study the quantum entanglement at the colliders which is independent of the spin-analyzing powers. Taking $\Lambda(\to p\pi^-)\bar{\Lambda}(\to \bar{p}\pi^+)$ as an example, we investigate whether quantum entanglement in fermion pairs produced at colliders can be certified by using only angular information from final-state decays, while remaining independent of the parity-violating decay parameters $\alpha_\Lambda$ and $\alpha_{\bar{\Lambda}}$. Building on a general decomposition of any angular observable in terms of Wigner d-functions, we show that the expectation value must take the form $\mathcal{O}_0+\mathcal{O}_1\alpha_\Lambda+\mathcal{O}_2\alpha_{\bar{\Lambda}}+\mathcal{O}_3\alpha_\Lambda\alpha_{\bar{\Lambda}}$, with coefficients $\mathcal{O}_i$ ($i=0,1,2,3$) linear in the spin-density matrix elements $\alpha_{k,j}\alpha^*_{m,n}$. We obtain the value ranges of observables over the general and separable spaces of $\alpha_{k,j}$, and demonstrate a sufficient entanglement condition for pure states, extending it to mixed states by convexity. In constructing an $\alpha_\Lambda$- and $\alpha_{\bar{\Lambda}}$-independent witness from angular observables alone, we find that there are obstacles to probe quantum entanglement via the inequality-type and ratio-type ways. Finally, we present the successful constructions with additional spin information: for the process of $e^+e^-\to J/\Psi\to \Lambda\bar{\Lambda}$ at $e^+ e^-$ collider, independent spin information provided by beam-axis selection enables the construction of normalized observables $f_i~(i=1,2)$ that are insensitive to $\alpha_\Lambda$ and $\alpha_{\bar{\Lambda}}$; if their measured values lie in $\left[-1,-\tfrac{1}{2}\right)\cup\left(\tfrac{1}{2},1\right]$, entanglement is certified, irrespective of purity or mixedness.

When an unexpected metro disruption occurs, metro managers need to reschedule timetables to avoid trains going into the disruption area, and transport passengers stranded at disruption stations as quickly as possible. This paper proposes a two-stage optimization model to jointly make decisions for two tasks. In the first stage, the timetable rescheduling problem with cancellation and short-turning strategies is formulated as a mixed integer linear programming (MILP). In particular, the instantaneous parameters and variables are used to describe the accumulation of time-varying passenger flow. In the second one, a system-optimal dynamic traffic assignment (SODTA) model is employed to dynamically schedule response vehicles, which is able to capture the dynamic traffic and congestion. Numerical cases of Beijing Metro Line 9 verify the efficiency and effectiveness of our proposed model, and results show that: (1) when occurring a disruption event during peak hours, the impact on the normal timetable is greater, and passengers in the direction with fewer train services are more affected; (2) if passengers stranded at the terminal stations of disruption area are not transported in time, they will rapidly increase at a speed of more than 300 passengers per minute; (3) compared with the fixed shortest path, using the response vehicles reduces the total travel time about 7%. However, it results in increased travel time for some passengers.

Measuring similarity between complex objects is a fundamental task in many scientific fields. When objects are represented as graphs, graph similarity/distance measures offer a powerful framework for quantifying structural resemblance. Those comparative measures play a key role in domains such as network science, chemoinformatics, and social network analysis. While methods like graph edit distance and graph kernels are widely used, they can be computationally intensive or fail to capture fine structural variations, since they require graphs without any structural uncertainty. Another class of methods is based on using topological indices to encode structural information of the graphs, followed by the application of distance or similarity measures for real numbers to obtain corresponding graph-level metrics. In this paper, we introduce a novel class of distance/similarity measures which are based on multiple topological indices. Since they are generally computed in polynomial time, our method is computationally efficient in practice. We demonstrate its effectiveness through comparisons and show that it captures subtle structural information meaningfully. Additionally, we explore its applicability in two domains: analyzing random graph models in network theory and assessing molecular similarity among isomers in chemoinformatics. These preliminary results suggest that our approach holds promise for graph comparison across disciplines.

We study the propagation of dark-bright solitons in two-component Bose-Einstein condensates (BECs) with general nonlinear parameters, and explore how nonlinear interactions enrich the soliton dynamics giving rise to nonsinusoidal oscillations under constant forces. Treating the bright soliton as an effective barrier, we reveal that such oscillations are characterized by the Josephson equations with self-adapted critical current and bias voltage, whose explicit analytic expressions are derived using the Lagrangian variational method. The dynamical phase diagram in nonlinear parameter space is presented, identifying oscillation regions with different skewed sinusoidal dependence, and diffusion regions with irreversible soliton spreading due to instability of the barrier. Furthermore, we obtain periodic dispersion relations of the solitons, indicating a switch between positive and negative inertial masses, consistent with the oscillation behaviors. Our results provide a general and comprehensive theoretical framework for soliton oscillation dynamics and pave the way for investigating various nonlinear transports and their potential applications.

We propose a new formalism for quantum entanglement (QE), and study its generic searches at the colliders. For a general quantum system with $N$ particles, we show that the quantum space (the total spin polarization parameter space) is complex projective space, and the classical space (the spin polarization parameter space for classical theory) is the cartesian product of the complex projective spaces. Thus, the quantum entanglement space is the difference of these two spaces. For the $ff$, $AA$, $Af$, $fff$, and $ffA$ systems, we propose their discriminants $\Delta_i$. The corresponding classical spaces are the discriminant locus $\Delta=0$ for $ff$ system, and intersections of the discriminant loci $\Delta_i=0$ for $AA$, $Af$, $fff$, and $ffA$ systems in the quantum space. In particular, for two fermion $ff$ system, we prove that our discriminant criterion is equivalent to the original Peres-Horodecki criterion and the CHSH criterion. And thus our quantum entanglement space is indeed Bell non-local. With the collider searches, we can reconstruct the discriminants from various measurements, and probe the quantum entanglement spaces via a fundamental approach at exact level. In addition, for the specific approach, we present a comprehensive framework to detect quantum entanglement in high-energy multi-particle systems, spanning fermion pairs ($t\bar{t}$, $\tau^{+}\tau^{-}$), bosonic pairs ($W^{-}W^{+}$), and hybrid or three-body systems ($W^{-}t$, $ttt$, $t\bar{t}W^{-}$), by diverse observables through angular correlations in decay products. These results establish model-independent methodologies for probing QE across collider experiments, bridging quantum information principles with high-energy phenomenology, while offering novel pathways to explore exotic particles and quantum properties in multi-particle systems.

We explore a scenario of interacting dynamical dark energy model with the interaction term $Q$ including the varying equation-of-state parameter $w$. Using the data combination of the cosmic microwave background, the baryon acoustic oscillation, and the type Ia supernovae, to global fit the interacting dynamical dark energy model, we find that adding a factor of the varying $w$ in the function of $Q$ can change correlations between the coupling constant $\beta$ and other parameters, and then has a huge impact on the fitting result of $\beta$. In this model, the fitting value of $H_{0}$ is lower at the $3.54 \sigma$ level than the direct measurement value of $H_{0}$ . Comparing to the case of interacting dynamical dark energy model with $Q$ excluding $w$, the model with $Q$ including the constant $w$ is more favored by the current mainstream observation. To obtain higher fitting values of $H_{0}$ and narrow the discrepancy of $H_{0}$ between different observations, additional parameters including the effective number of relativistic species, the total neutrino mass, and massive sterile neutrinos are considered in the interacting dynamical dark energy cosmology. We find that the $H_{0}$ tension can be further reduced in these models, but is still at the about $3 \sigma$ level.

3D single object tracking within LIDAR point clouds is a pivotal task in computer vision, with profound implications for autonomous driving and robotics. However, existing methods, which depend solely on appearance matching via Siamese networks or utilize motion information from successive frames, encounter significant challenges. Issues such as similar objects nearby or occlusions can result in tracker drift. To mitigate these challenges, we design an innovative spatio-temporal bi-directional cross-frame distractor filtering tracker, named STMD-Tracker. Our first step involves the creation of a 4D multi-frame spatio-temporal graph convolution backbone. This design separates KNN graph spatial embedding and incorporates 1D temporal convolution, effectively capturing temporal fluctuations and spatio-temporal information. Subsequently, we devise a novel bi-directional cross-frame memory procedure. This integrates future and synthetic past frame memory to enhance the current memory, thereby improving the accuracy of iteration-based tracking. This iterative memory update mechanism allows our tracker to dynamically compensate for information in the current frame, effectively reducing tracker drift. Lastly, we construct spatially reliable Gaussian masks on the fused features to eliminate distractor points. This is further supplemented by an object-aware sampling strategy, which bolsters the efficiency and precision of object localization, thereby reducing tracking errors caused by distractors. Our extensive experiments on KITTI, NuScenes and Waymo datasets demonstrate that our approach significantly surpasses the current state-of-the-art methods.

We analyze a scheme for controlling coherent photon absorption by cavity electromagnetically induced transparency (EIT) in a three-level atom-cavity system. Coherent perfect absorption (CPA) can occur when time-reversed symmetry of lasing process is obtained and destructive interference happens at the cavity interfaces. Generally, the frequency range of CPA is dependent on the decay rates of cavity mirrors. When the control laser is settled, the smaller cavity decay rate causes the wider frequency range of CPA, and the input intensity is larger to satisfy CPA condition for a given frequency. While the cavity parameters are determined, Rabi frequency of the control laser has little effect on the frequency range of CPA. However, with EIT-type quantum interference, the CPA mode is tunable by the control laser. This means the CPA with given frequency and intensity of an input laser can be manipulated as the coherent non-perfect absorption (CNPA). Moreover, with the relative phase of input probe lasers, the probe fields can be perfectly transmitted and/or reflected. Therefore, the system can be used as a controllable coherent perfect absorber or transmitter and/or reflector, and our work may have practical applications in optical logic devices.

With recent advances in simulating quantum phenomena in cold atoms, the higher-rank spin tensor Hall effect was discovered in larger spin systems with spin-tensor-momentum coupling, which is an extension of the celebrated spin Hall effects in larger spins. Previously, it has been proposed that a 2D electron gas with Rashba spin-orbit coupling can generate dissipationless transverse spin current, namely the spin Hall effect. However, later work showed that the spin current is canceled by vertex correction, which was subsequently proven by a cancellation theorem that does not depend on any assumptions related to the scattering mechanism, the strength of spin-orbit coupling, or the Fermi energy. While the recent proposal demonstrates a universal intrinsic spin-tensor Hall conductivity, it is unclear if it vanishes similarly to the spin Hall effect. In this work, we address this critical problem and show that the rank-2 spin-tensor current can be divergent by considering the contributions of both interbranch and intrabranch transitions, which resembles the quantum Hall effect in some sense. So the \textit{universal} spin-tensor Hall effect can not be observed in a system with finite size. However, we further show that there is an \textit{observable non-zero} resonance of spin-tensor Hall conductivity as the Landau levels cross under the magnetic field. Our work reveals interesting conductivity properties of larger-spin systems and will provide valuable guidance for experimental explorations of higher-rank spin-tensor Hall effects, as well as their potential device applications.

Scientific discovery evolves from the experimental, through the theoretical and computational, to the current data-intensive paradigm. Materials science is no exception, especially for computational materials science. In recent years, great achievements have been made in the field of materials science and engineering (MSE). Here, we review the previous paradigms of materials science and some classical MSE models. Then, our data-intensive MSE (DIMSE) model is proposed to reshape future materials innovations. This work will help to address the global challenge for materials discovery in the era of artificial intelligence (AI), and essentially contribute to accelerating future materials continuum.

The dark photon is a well motivated candidate for the dark matter which comprises most of the mass of our visible Universe, leading to worldwide experimental and observational efforts towards its discovery. A primary tool in this search is the cavity haloscope, which facilitates resonantly enhanced conversion to photons from both dark photons and axions. In this context, limits from axion search experiments are often directly converted into dark photon constraints, without re-analyzing the original data. However, this rescaling may not fully capture all of the relevant physics due to various reasons. By re-examining data taken by the Taiwan Axion Search Experiment with Haloscope (TASEH) experiment, we derive a world-leading constraint on the dark photon parameter space, excluding $|\epsilon|\gtrsim2\times10^{-14}$ in the $19.46 - 19.84\,\mu$eV mass range, which exceeds the naive `rescaling limit' by roughly one order of magnitude. In this data, we also identify a tentative signal with a local significance of 4.7$\sigma$, previously disregarded due to an axion-specific veto, corresponding to a dark photon with mass $m_X \simeq 19.5\,\mu$eV ($f_X\simeq 4.71$ GHz) and kinetic mixing $\epsilon \simeq 6.5\times10^{-15}$.

We theoretically propose a second-order topological magnon insulator by stacking the van der Waals honeycomb ferromagnets with antiferromagnetic interlayer coupling. The system exhibits Z$_{2}$ topological phase, protected by pseudo-time-reversal symmetry (PTRS). An easy-plane anisotropy term breaks PTRS and destroys the topological phase. Nevertheless, it respects a magnetic two-fold rotational symmetry which protects a second-order topological phase with corner modes in bilayer and hinge modes along stacking direction. Moreover, an introduced staggered interlayer coupling establishes a Z$_{2}$$\times$Z topology, giving rise to gapped topological surface modes carrying non-zero Chern numbers. Consequently, chiral hinge modes propagate along the horizontal hinges in a cuboid geometry and are robust against disorders. Our work bridges the higher-order topology and magnons in van der Waals platforms, and could be used for constructing topological magnonic devices.

We propose and analyze a scheme for realizing tunable coherent perfect absorption (CPA) and reflection (CPR) in a three-level $\Lambda$-type atom-cavity system. With EIT-type interference induced by a coherent coupling laser, the scheme provides a new method of attaining tunable near CPR at two-photon resonance. By different coupling strength, the system can be excited from linear CPA regime into nonlinear even bistable CPA regime without changing the frequency of the probe field, where the hysteresis cycle of the bistability is controllable. In addition, the CPA regime can be transferred into the near CPR regime with controllable atomic coherence and linear absorption induced by an incoherent pump field. Our work suggests a mechanism for manipulation on extreme absorption (0% and 100%), which can potentially be applied in logical gates and optical switches for coherent optical computing and communication.