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Meng Gao

Publications and source records attributed to Meng Gao.

At least 37 records · Page 2Linked to original sources
arXiv2026

AIVD: Adaptive Edge-Cloud Collaboration for Accurate and Efficient Industrial Visual Detection

Multimodal large language models (MLLMs) demonstrate exceptional capabilities in semantic understanding and visual reasoning, yet they still face challenges in precise object localization and resource-constrained edge-cloud deployment. To address this, this paper proposes the AIVD framework, which achieves unified precise localization and high-quality semantic generation through the collaboration between lightweight edge detectors and cloud-based MLLMs. To enhance the cloud MLLM's robustness against edge cropped-box noise and scenario variations, we design an efficient fine-tuning strategy with visual-semantic collaborative augmentation, significantly improving classification accuracy and semantic consistency. Furthermore, to maintain high throughput and low latency across heterogeneous edge devices and dynamic network conditions, we propose a heterogeneous resource-aware dynamic scheduling algorithm. Experimental results demonstrate that AIVD substantially reduces resource consumption while improving MLLM classification performance and semantic generation quality. The proposed scheduling strategy also achieves higher throughput and lower latency across diverse scenarios.

cs.CV↗
arXiv2025

UPETrack: Unidirectional Position Estimation for Tracking Occluded Deformable Linear Objects

Real-time state tracking of Deformable Linear Objects (DLOs) is critical for enabling robotic manipulation of DLOs in industrial assembly, medical procedures, and daily-life applications. However, the high-dimensional configuration space, nonlinear dynamics, and frequent partial occlusions present fundamental barriers to robust real-time DLO tracking. To address these limitations, this study introduces UPETrack, a geometry-driven framework based on Unidirectional Position Estimation (UPE), which facilitates tracking without the requirement for physical modeling, virtual simulation, or visual markers. The framework operates in two phases: (1) visible segment tracking is based on a Gaussian Mixture Model (GMM) fitted via the Expectation Maximization (EM) algorithm, and (2) occlusion region prediction employing UPE algorithm we proposed. UPE leverages the geometric continuity inherent in DLO shapes and their temporal evolution patterns to derive a closed-form positional estimator through three principal mechanisms: (i) local linear combination displacement term, (ii) proximal linear constraint term, and (iii) historical curvature term. This analytical formulation allows efficient and stable estimation of occluded nodes through explicit linear combinations of geometric components, eliminating the need for additional iterative optimization. Experimental results demonstrate that UPETrack surpasses two state-of-the-art tracking algorithms, including TrackDLO and CDCPD2, in both positioning accuracy and computational efficiency.

cs.RO↗
arXiv2025

Learning from the electronic structure of molecules across the periodic table

Machine-Learned Interatomic Potentials (MLIPs) require vast amounts of atomic structure data to learn forces and energies, and their performance continues to improve with training set size. Meanwhile, the even greater quantities of accompanying data in the Hamiltonian matrix H behind these datasets has so far gone unused for this purpose. Here, we provide a recipe for integrating the orbital interaction data within H towards training pipelines for atomic-level properties. We first introduce HELM ("Hamiltonian-trained Electronic-structure Learning for Molecules"), a state-of-the-art Hamiltonian prediction model which bridges the gap between Hamiltonian prediction and universal MLIPs by scaling to H of structures with 100+ atoms, high elemental diversity, and large basis sets including diffuse functions. To accompany HELM, we release a curated Hamiltonian matrix dataset, 'OMol_CSH_58k', with unprecedented elemental diversity (58 elements), molecular size (up to 150 atoms), and basis set (def2-TZVPD). Finally, we introduce 'Hamiltonian pretraining' as a method to extract meaningful descriptors of atomic environments even from a limited number atomic structures, and repurpose this shared embedding space to improve performance on energy-prediction in low-data regimes. Our results highlight the use of electronic interactions as a rich and transferable data source for representing chemical space.

physics.chem-ph↗
arXiv2025

Dynamical Phase Transition of Dark Solitons in Spherical Holographic Superfluids

In this paper, we employ, for the first time, the holographic gravity approach to investigate the dynamical stability of solitons in spherical superfluids. Transverse perturbations are applied to the background of spherical soliton configurations, and the collective excitation modes of the solitons are examined within the framework of linear analysis. Our study reveals the existence of two distinct unstable modes in the soliton configurations. Through fully nonlinear evolution schemes, the dynamical evolution and final states of the solitons are elucidated. The results demonstrate that the solitons exhibit both self-acceleration instability and snake instability at different temperatures, respectively. And we explore the corresponding temperature-dependent dynamical phase transitions. It is noteworthy that the dynamical behavior of spherical solitons is distinct from the planar case due to the presence of spherical curvature.

hep-th↗
arXiv2025

Violation of Luttinger's theorem in one-dimensional interacting fermions

Using the density matrix renormalization group method, we systematically investigate the evolution of the Luttinger integral in the one-dimensional generalized $t$-$V$ model as a function of filling and interaction strength, and identify three representative phases. In the weak-coupling regime, the zero-frequency Green's function exhibits a branch-cut structure at the Fermi momentum, and the Luttinger integral accurately reflects the particle density, indicating that the Luttinger theorem holds. As the interaction increases, the spectral weight near the Fermi momentum is gradually suppressed. Interestingly, in the strong coupling regime near half-filling, this singularity is progressively destroyed, accompanied by the emergence of momentum-space zeros in the real part of the Green's function, leading to a novel non-Fermi liquid metallic phase beyond the classic Luttinger liquid paradigm, where the Luttinger surface is no longer defined by a single singularity. While finite spectral weight remains at the original Fermi momentum, the singularity gradually diminishes. Meanwhile, zeros with negligible spectral weight appear away from this momentum, significantly affecting the integral. At exact half-filling, a single-particle gap opens, and the Green's function becomes nearly vanishing across the entire momentum space, indicating the complete suppression of low-energy electronic states consistent with the nature of an insulating charge-density-wave phase. These results suggest that the breakdown of the Luttinger theorem is not triggered by a single mechanism, but rather results from the interplay between interaction-driven evolution of excitation modes and the breaking of particle-hole symmetry, ultimately leading to a continuous reconstruction of the generalized Fermi surface from topologically protected to correlation-driven.

cond-mat.str-el↗
arXiv2025

Open Molecular Crystals 2025 (OMC25) Dataset and Models

The development of accurate and efficient machine learning models for predicting the structure and properties of molecular crystals has been hindered by the scarcity of publicly available datasets of structures with property labels. To address this challenge, we introduce the Open Molecular Crystals 2025 (OMC25) dataset, a collection of over 27 million molecular crystal structures containing 12 elements and up to 300 atoms in the unit cell. The dataset was generated from dispersion-inclusive density functional theory (DFT) relaxation trajectories of over 230,000 randomly generated molecular crystal structures of around 50,000 organic molecules. OMC25 comprises diverse chemical compounds capable of forming different intermolecular interactions and a wide range of crystal packing motifs. We provide detailed information on the dataset's construction, composition, structure, and properties. To demonstrate the quality and use cases of OMC25, we further trained and evaluated state-of-the-art open-source machine learning interatomic potentials. By making this dataset publicly available, we aim to accelerate the development of more accurate and efficient machine learning models for molecular crystals.

physics.chem-ph↗
arXiv2025

Learning Smooth and Expressive Interatomic Potentials for Physical Property Prediction

Machine learning interatomic potentials (MLIPs) have become increasingly effective at approximating quantum mechanical calculations at a fraction of the computational cost. However, lower errors on held out test sets do not always translate to improved results on downstream physical property prediction tasks. In this paper, we propose testing MLIPs on their practical ability to conserve energy during molecular dynamic simulations. If passed, improved correlations are found between test errors and their performance on physical property prediction tasks. We identify choices which may lead to models failing this test, and use these observations to improve upon highly-expressive models. The resulting model, eSEN, provides state-of-the-art results on a range of physical property prediction tasks, including materials stability prediction, thermal conductivity prediction, and phonon calculations.

physics.comp-ph↗
arXiv2025

Huge Stress-induced Adiabatic Temperature Change in a High-Toughness All-d-metal Heusler Alloy

The elastocaloric effect (eCE), referring to the thermal effect triggered by a uniaxial stress, provides a promising and versatile routine for green and high efficient thermal management. However, current eCE materials generally suffer from relatively low eCE and poor mechanical properties, hindering their practical applications. Here, we report a exceptionally huge eCE with a directly measured adiabatic temperature change of up to 57.2 K in a dual-phase all-d-metal Heusler Mn50Ni37.5Ti12.5 polycrystalline alloy, revealing an extra contribution to the latent heat during the stress-induced martensitic transformation from B2 to L10, and breaking the record of adiabatic temperature change for elastocaloric alloys. Moreover, thanks to the combined strengthening effect of d-d hybridization and well-dispersed secondary cubic γ phase, the alloy can endure a uniaxial stress up to 1760 MPa. Such an abnormal huge eCE is attributed to the combination of the enhanced entropy change associated with a stress-induced B2 to L10 martensitic transformation under higher stress, in contrast with the thermally induced B2 to 5-layer modulated structure one, and the high transformation fraction due to the multi-point nucleation facilitated by the γ phase dispersed in the main phase. This work provides insight into making full use of the transformation heat to enhance the caloric effect for high-efficient thermal management systems.

cond-mat.mtrl-sci↗
arXiv2025

Holographic homogeneous superfluid on the sphere

In this paper, we extend the study of holographic superfluids from planar topology to spherical topology, inspired by recent studies on Bose-Einstein condensation (BEC) on shell-shaped geometry. We investigate the superfluid phase transition from normal fluid and its Quasi-Normal Modes (QNMs) on the sphere. It turns out that the critical temperature for the superfluid phase transition on the sphere is higher than that in the planar case. We investigated four different solutions in the backgrounds of large and small black holes. The calculation of free energy selects the most stable solution. Finally, after calculating the quasi-normal modes and their dynamic behavior, we obtained three different channels similar to the planar superfluid case, along with the ``first" hydrodynamic excitation mode.

hep-th↗
arXiv2024

Dynamical behaviour of soliton train in holographic superfluids at zero temperature

We construct a soliton train configuration with holographic superfluid model under AdS soliton background. We investigate the stability of a soliton train using Bloch waves under two distinct quantization schemes. Upon imposing a minor perturbation on the soliton train system, it has been observed that there exist two elastic modes and one phonon mode. Most importantly, we find, under soliton train background, that there is a rich phase diagram concerning the chemical potential under standard quantization. Nevertheless, there are no unstable modes under alternative quantization.

hep-th↗
arXiv2024

Caching Content Placement and Beamforming Co-design for IRS-Aided MIMO Systems with Imperfect CSI

When offloading links encounter deep fading and obstruction, edge caching cannot fully enhance wireless network performance and improve the QoS of edge nodes, as it fails to effectively reduce backhaul burden. The emerging technology of intelligent reflecting surfaces (IRS) compensates for this disadvantage by creating a smart and reconfigurable wireless environment. Subsequently, we jointly design content placement and active/passive beamforming to minimize network costs under imperfect channel state information (CSI) in the IRS-oriented edge caching system. This minimization problem is decomposed into two subproblems. The content placement subproblem is addressed by applying KKT optimality conditions. We then develop the alternating optimization method to resolve precoder and reflection beamforming. Specifically, we reduce transmission power by first fixing the phase shift, reducing the problem to a convex one relative to the precoder, which is solved through convex optimization. Next, we fix the precoder and resolve the resulting reflection beamforming problem using the penalty convex-concave procedure (CCP) method. Results demonstrate that our proposed method outperforms uniform caching and random phase approaches in reducing transmission power and saving network costs. Eventually, the proposed approach offers potential improvements in the caching optimization and transmission robustness of wireless communication with imperfect CSI.

eess.SP↗
arXiv2023

A density version of Waring-Goldbach problem

In this paper, we study a density version of the Waring-Goldbach problem. Suppose that A is a subset of the primes, and the lower density of A in the primes is larger than 1-1/2k. We prove that every sufficiently large natural number n satisfying the necessary congruence condition can be expressed as a sum of s terms of the k-th powers of primes from set A, where s is a positive integer dependent on k.

math.NT↗
arXiv2023

Long-lead forecasts of wintertime air stagnation index in southern China using oceanic memory effects

Stagnant weather condition is one of the major contributors to air pollution as it is favorable for the formation and accumulation of pollutants. To measure the atmosphere's ability to dilute air pollutants, Air Stagnation Index (ASI) has been introduced as an important meteorological index. Therefore, making long-lead ASI forecasts is vital to make plans in advance for air quality management. In this study, we found that autumn Niño indices derived from sea surface temperature (SST) anomalies show a negative correlation with wintertime ASI in southern China, offering prospects for a prewinter forecast. We developed an LSTM-based model to predict the future wintertime ASI. Results demonstrated that multivariate inputs (past ASI and Niño indices) achieve better forecast performance than univariate input (only past ASI). The model achieves a correlation coefficient of 0.778 between the actual and predicted ASI, exhibiting a high degree of consistency.

physics.ao-ph↗
arXiv2022

Ultrathin quantum light source enabled by a nonlinear van der Waals crystal with vanishing interlayer-electronic-coupling

Interlayer electronic coupling in two-dimensional (2D) materials enables tunable and emergent properties by stacking engineering. However, it also brings significant evolution of electronic structures and attenuation of excitonic effects in 2D semiconductors as exemplified by quickly degrading excitonic photoluminescence and optical nonlinearities in transition metal dichalcogenides when monolayers are stacked into van der Waals structures. Here we report a novel van der Waals crystal, niobium oxide dichloride, featuring a vanishing interlayer electronic coupling and scalable second harmonic generation intensity of up to three orders higher than that of exciton-resonant monolayer WS2. Importantly, the strong second-order nonlinearity enables correlated parametric photon pair generation, via a spontaneous parametric down-conversion (SPDC) process, in flakes as thin as ~46 nm. To our knowledge, this is the first SPDC source unambiguously demonstrated in 2D layered materials, and the thinnest SPDC source ever reported. Our work opens an avenue towards developing van der Waals material-based ultracompact on-chip SPDC sources, and high-performance photon modulators in both classical and quantum optical technologies.

physics.optics↗
arXiv2021

Resource conversion between operational coherence and multipartite entanglement in many-body systems

We establish a set of resource conversion relationships between quantum coherence and multipartite entanglement in many-body systems, where the operational measures of resource cost and distillation are focused. Under the multipartite incoherent operation, the initial coherence of single-party system bounds the maximal amounts of corresponding operational entanglement in an arbitrary bipartite partition as well as the genuine multipartite entanglement in many-body systems. Furthermore, the converted multipartite entanglement can be transferred to its subsystems and restored to coherence of a single party by means of local incoherent operations and classical communication, which constitutes a protocol of resource interconversion within the full incoherent operation scenario. As an example, we present a scheme for cyclic interconversion between coherence and genuine multipartite entanglement in three-qubit systems without loss. Moreover, we analyze the property of bipartite and multipartite genuine multi-level entanglement by the initial coherence and investigate multipartite resource dynamics in the conversion.

quant-ph↗