arXiv subjects

Zhigang Song

Publications and source records attributed to Zhigang Song.

At least 19 recordsLinked to original sources

arXiv2026

Artificial-atom arrays in moire superlattices for quantum optics

Solid-state platforms are particularly attractive for quantum optics because they facilitate on-chip integration and are compatible with established semiconductor and photonic technologies. However, a major challenge in solid-state quantum optics is the fabrication of arrays of identical emitters, such as quantum dots. In this work, we propose moire superlattices as a novel solid-state platform for manipulating light at the single-photon level. Moire superlattices form arrays of artificial-atom states characterized by nearly identical optical transition energies, tunable spacing, and highly adjustable electronic structures. They naturally operate as atomically thin, scalable, periodic emitters, making them ideal for quantum applications. Additionally, the extensive materials database of moire superlattices offers spectral coverage spanning a broad range of optical wavelengths.

physics.optics↗

arXiv2026

ProUIE: A Macro-to-Micro Progressive Learning Method for LLM-based Universal Information Extraction

LLM-based universal information extraction (UIE) methods often rely on additional information beyond the original training data, which increases training complexity yet often yields limited gains. To address this, we propose ProUIE, a Macro-to-Micro progressive learning approach that improves UIE without introducing any external information. ProUIE consists of three stages: (i) macro-level Complete Modeling (CM), which learns NER, RE, and EE along their intrinsic difficulty order on the full training data to build a unified extraction foundation, (ii) meso-level Streamlined Alignment (SA), which operates on sampled data with simplified target formats, streamlining and regularizing structured outputs to make them more concise and controllable, and (iii) micro-level Deep Exploration (DE), which applies GRPO with stepwise fine-grained rewards (SFR) over structural units to guide exploration and improve performance. Experiments on 36 public datasets show that ProUIE consistently improves unified extraction, outperforming strong instruction-tuned baselines on average for NER and RE while using a smaller backbone, and it further demonstrates clear gains in large-scale production-oriented information extraction.

cs.CL↗

arXiv2025

Unconventional Geometric Phase in Twisted Junction of Cuprates

Originally introduced in optics, the Pancharatnam-Berry phase is a general concept of geometric phase defined for any two interfering polarization states. In electronic systems, however, its counterpart has long been overlooked due to the absence of electron polarization. Here, using large-scale first-principles calculations, we investigate the electronic structure of twisted bilayer Bi2Sr2CaCu2O8. We find spontaneous spin polarization and the emergence of hidden flat bands at the interface between atomic layers. Most notably, we discover an unconventional geometric phase analogous to the Pancharatnam-Berry phase in optics. This electronic geometric phase exerts opposite effects on superconducting currents of opposite chirality, enabling twisted cuprates to act as a filter for chiral superconducting current-even if the ground state itself is non-chiral.

cond-mat.supr-con↗

arXiv2025

Fusion of Multi-scale Heterogeneous Pathology Foundation Models for Whole Slide Image Analysis

Whole slide image (WSI) analysis has emerged as an increasingly essential technique in computational pathology. Recent advances in the pathology foundation models (FMs) have demonstrated significant advantages in deriving meaningful patch-level or slide-level multi-scale features from WSIs. However, current pathology FMs have exhibited substantial heterogeneity caused by diverse private training datasets and different network architectures. This heterogeneity introduces performance variability when we utilize the features from different FMs in the downstream tasks. To fully explore the advantages of multiple FMs effectively, in this work, we propose a novel framework for the fusion of multi-scale heterogeneous pathology FMs, called FuseCPath, yielding a model with a superior ensemble performance. The main contributions of our framework can be summarized as follows: (i) To guarantee the representativeness of the training patches, we propose a multi-view clustering-based method to filter out the discriminative patches via multiple FMs' embeddings. (ii) To effectively fuse the patch-level FMs, we devise a cluster-level re-embedding strategy to online capture patch-level local features. (iii) To effectively fuse the slide-level FMs, we devise a collaborative distillation strategy to explore the connections between slide-level FMs. Extensive experiments demonstrate that the proposed FuseCPath achieves state-of-the-art performance across multiple tasks on diverse datasets.

cs.CV↗

arXiv2025

A Multidimensional Self-Adaptive Numerical Simulation Framework for Semiconductor Boltzmann Transport Equation

This research addresses the numerical simulation of the Boltzmann transport equation for semiconductor devices by proposing a multidimensional self-adaptive numerical simulation framework. This framework is applied to two important generalized forms of the equation: a parabolic equation with singular properties on the unit disk and a continuity equation. The study enhances the alignment of numerical simulations with physical characteristics through polar coordinate transformation and variable drift-diffusion coefficients. Innovatively, a multidimensional adaptive mesh partitioning strategy for radius-angle-time is designed and combined with an adjustable finite difference scheme to construct a highly adaptive numerical simulation method. In the construction of discrete schemes, the Swartztrauber-Sweet method and the control volume method are employed to effectively eliminate the origin singularity caused by polar coordinate transformation. On the programming front, a parallelized MATLAB algorithm is developed to optimize code execution efficiency. Numerical comparative experiments demonstrate that the adaptive method improves the accuracy of the parabolic equation by 1 to 7 times and that of the continuity equation by 10% to 70% while maintaining computational efficiency, significantly enhancing numerical simulation accuracy with high stability. Furthermore, this study systematically verifies the algorithm's convergence, stability, and parameter sensitivity using error visualization and other means. It also explores optimal parameters and establishes tuning optimization criteria. The research provides theoretical support for high-precision and highly adaptive methods in semiconductor device simulation, demonstrating outstanding advantages in handling singular regions.

math.NA↗

arXiv2024

Band Oscillation Correlated with Tc for Superconductors

Previous theoretical studies on superconductivity were focused on the static states and adiabatic processes. Quantum mechanics simulations of time-dependent processes in superconductors were rarely performed previously. Here we use real-time time-dependent density functional theory to show a new phenomenon that the electron-phonon excitation is coherent and mode-selective, resulting in a periodic band oscillation. Surprisingly, the predicted oscillation frequency of charges or bands here are strongly correlated with a broad range of superconductivity transition temperatures of various main families of superconductors, including cuprates, Fe-based, hydrides, and WTe2. This shed light on the pairing mechanism in unconventional superconductors, paving the way for the design of higher temperature superconductors.

cond-mat.supr-con↗

arXiv2024

Twist-induced spin splitting and spin-Hall-like effect in antiferromagnetic bilayers

Momentum-resolved spin-polarized bands are a key ingredient in many proposed spintronic devices, but their existence often relies on lattice commensurability or strong spin-orbit coupling. By a large-scale DFT calculation (up to 4212 atoms), we propose a way to realize strongly spin-polarized bands in the absence of these ingredients by twisting monolayers of van der Waals magnetic semiconductor CrSBr. Furthermore, due to the highly anisotropic electronic transport in this material, the twist-induced electronic transport becomes strongly coupled to the spin transport. We show that an in-plane electric field induces a transverse spin current, manifesting a twist-tunable spin-Hall effect in the absence of spin-orbit coupling. Using highthroughput computations, we also identify 231 other material candidates out of a set of 6000 magnetic two-dimensional materials, which satisfy the necessary conditions to realize this behavior, paving the way to widespread application of twist-tunable spin transport.

cond-mat.mtrl-sci↗

arXiv2024

Solid-state qubits in moire superlattices

Qubits are the fundamental units in quantum computing, but they are also pivotal for advancements in quantum communication and sensing. Currently, there are a variety of platforms for qubits, including cold atoms, superconducting circuits, point defects, and semiconductor quantum dots. In these systems, each qubit requires individual preparation, making identical replication a challenging task. Constructing and maintaining stable, scalable qubits remains a formidable challenge, especially for solid-state qubits. The race to identify the best one remains inconclusive, making the search for new qubits a welcome endeavor. Our study introduces moir\'e superlattices of twisted bilayer materials as a promising platform for qubits due to their tunability, natural patterns, and extensive materials library. Our first-principles calculations reveal that when the twist angle between the two layers is sufficiently small, these materials foster identical, localized quantum wells within the moir\'e superlattices. Each quantum well accommodates a few dispersionless bands and localized states, akin to the discrete energy levels of an alkali atom. Existing experimental techniques allow for individual initialization, manipulation, and readout of the local quantum states. The vast array of 2D materials provides a multitude of potential candidates for qubit exploration in such systems. Due to their inherent scalability and uniformity, our proposed qubits present significant advantages over conventional solid-state qubit systems.

quant-ph↗

arXiv2024

Terahertz chiral photonic-crystal cavities for Dirac gap engineering in graphene

Strong coupling between matter and vacuum electromagnetic fields in a cavity can induce novel quantum phases in thermal equilibrium via symmetry breaking. Particularly intriguing is the coupling with circularly polarized cavity fields, which can break time-reversal symmetry (TRS) and lead to topological bands. This has spurred significant interest in developing chiral cavities that feature broken TRS, especially in the terahertz (THz) frequency range, where various large-oscillator-strength resonances exist. Here, we present a design for high-quality-factor THz chiral photonic-crystal cavities (PCCs) that achieves broken TRS using a magnetoplasma in a lightly doped semiconductor. We incorporate ab initio density functional theory calculations into the derived microscopic model, allowing a realistic estimate of the vacuum-induced gap in graphene when coupled to our chiral cavity. Our calculations show an enhancement in the light-matter interaction due to Dirac nodes and predict an energy gap on the order of 1 meV. The THz chiral PCCs offer a promising platform for exploring cavity-dressed condensed matter with broken TRS.

physics.optics↗

arXiv2024

Intrinsic localized excitons in MoSe$_2$/CrSBr heterostructures

We present a comprehensive investigation of optical properties in MoSe$_2$/CrSBr heterostructures, unveiling the presence of localized excitons represented by a new emission feature, X$^*$. We demonstrate through temperature- and power-dependent photoluminescence spectroscopy that X$^*$ originates from excitons confined by intrinsic defects within the CrSBr layer. The valley polarization of X$^*$ and trion peaks displays opposite polarity under a magnetic field, which closely correlates with the magnetic order of CrSBr. This is attributed to spin-dependent charge transfer mechanisms across the heterointerface, supported by density functional theory calculations revealing a type-II band alignment and spin-polarized band structures. Furthermore, the strong in-plane anisotropy of CrSBr induces unique polarization-dependent responses in MoSe$_2$ emissions. Our study highlights the crucial role of defects in shaping excitonic properties. It offers valuable insights into spectral-resolved proximity effects in van der Waals heterostructures between semiconductor and magnet, contributing to advancing spintronic and valleytronic devices.

cond-mat.mes-hall↗

arXiv2024

CAMEL2: Enhancing weakly supervised learning for histopathology images by incorporating the significance ratio

Histopathology image analysis plays a crucial role in cancer diagnosis. However, training a clinically applicable segmentation algorithm requires pathologists to engage in labour-intensive labelling. In contrast, weakly supervised learning methods, which only require coarse-grained labels at the image level, can significantly reduce the labeling efforts. Unfortunately, while these methods perform reasonably well in slide-level prediction, their ability to locate cancerous regions, which is essential for many clinical applications, remains unsatisfactory. Previously, we proposed CAMEL, which achieves comparable results to those of fully supervised baselines in pixel-level segmentation. However, CAMEL requires 1,280x1,280 image-level binary annotations for positive WSIs. Here, we present CAMEL2, by introducing a threshold of the cancerous ratio for positive bags, it allows us to better utilize the information, consequently enabling us to scale up the image-level setting from 1,280x1,280 to 5,120x5,120 while maintaining the accuracy. Our results with various datasets, demonstrate that CAMEL2, with the help of 5,120x5,120 image-level binary annotations, which are easy to annotate, achieves comparable performance to that of a fully supervised baseline in both instance- and slide-level classifications.

cs.CV↗

arXiv2023

Vacuum-Induced Symmetry Breaking of Chiral Enantiomer Formation in Chemical Reactions

A material with symmetry breaking inside can transmit the symmetry breaking to its vicinity by vacuum electromagnetic fluctuations. Here, we show that vacuum quantum fluctuations proximate to a parity-symmetry-broken material can induce a chirality-dependent spectral shift of chiral molecules, resulting in a chemical reaction process that favors producing one chirality over the other. We calculate concrete examples and evaluate the chirality production rate with experimentally realizable parameters, showing the promise of selecting chirality with symmetry-broken vacuum quantum fluctuations.

quant-ph↗

arXiv2023

Flat-band spin density wave in twisted bilayer materials

Twisting is a novel technique for creating strongly correlated effects in two-dimensional bilayered materials, and can tunably generate nontrivial topological properties, magnetism, and superconductivity. Magnetism is particularly significant as it can both compete with superconductivity and lead to the emergence of nontrivial topological states. However, the origin of magnetism in twisted structures remains a subject of controversy. Using self-developed large-scale electronic structure calculations, we propose the magnetism in these twisted bilayer systems originates from spin splitting induced by the enhanced ratio of the exchange interaction to band dispersion.

cond-mat.str-el↗

arXiv2023

The bulk van der Waals layered magnet CrSBr is a quasi-1D material

Correlated quantum phenomena in one-dimensional (1D) systems that exhibit competing electronic and magnetic order are of strong interest for studying fundamental interactions and excitations, such as Tomonaga-Luttinger liquids and topological orders and defects with properties completely different from the quasiparticles expected in their higher-dimensional counterparts. However, clean 1D electronic systems are difficult to realize experimentally, particularly magnetically ordered systems. Here, we show that the van der Waals layered magnetic semiconductor CrSBr behaves like a quasi-1D material embedded in a magnetically ordered environment. The strong 1D electronic character originates from the Cr-S chains and the combination of weak interlayer hybridization and anisotropy in effective mass and dielectric screening with an effective electron mass ratio of $m^e_X/m^e_Y \sim 50$. This extreme anisotropy experimentally manifests in strong electron-phonon and exciton-phonon interactions, a Peierls-like structural instability and a Fano resonance from a van Hove singularity of similar strength of metallic carbon nanotubes. Moreover, due to the reduced dimensionality and interlayer coupling, CrSBr hosts spectrally narrow (1 meV) excitons of high binding energy and oscillator strength that inherit the 1D character. Overall, CrSBr is best understood as a stack of weakly hybridized monolayers and appears to be an experimentally attractive candidate for the study of exotic exciton and 1D correlated many-body physics in the presence of magnetic order.

cond-mat.mes-hall↗

arXiv2022

Strong structural and electronic coupling in metavalent PbS moire superlattices

Moire superlattices are twisted bilayer materials, in which the tunable interlayer quantum confinement offers access to new physics and novel device functionalities. Previously, moire superlattices were built exclusively using materials with weak van der Waals interactions and synthesizing moire superlattices with strong interlayer chemical bonding was considered to be impractical. Here using lead sulfide (PbS) as an example, we report a strategy for synthesizing of moire superlattices coupled by strong chemical bonding. We use water-soluble ligands as a removable template to obtain free-standing ultra-thin PbS nanosheets and assemble them into direct-contact bilayers with various twist angles. Atomic-resolution imaging shows the moire periodic structural reconstruction at superlattice interface, due to the strong metavalent coupling. Electron energy loss spectroscopy and theoretical calculations collectively reveal the twist angle26 dependent electronic structure, especially the emergent separation of flat bands at small twist angles. The localized states of flat bands are similar to well-arranged quantum dots, promising an application in devices. This study opens a new door to the exploration of deep energy modulations within moire superlattices alternative to van der Waals twistronics.

cond-mat.mtrl-sci↗

arXiv2022

Sensing the local magnetic environment through optically active defects in a layered magnetic semiconductor

Atomic-level defects in van der Waals (vdW) materials are essential building blocks for quantum technologies and quantum sensing applications. The layered magnetic semiconductor CrSBr is an outstanding candidate for exploring optically active defects owing to a direct gap in addition to a rich magnetic phase diagram including a recently hypothesized defect-induced magnetic order at low temperature. Here, we show optically active defects in CrSBr that are probes of the local magnetic environment. We observe spectrally narrow (1 meV) defect emission in CrSBr that is correlated with both the bulk magnetic order and an additional low temperature defect-induced magnetic order. We elucidate the origin of this magnetic order in the context of local and non-local exchange coupling effects. Our work establishes vdW magnets like CrSBr as an exceptional platform to optically study defects that are correlated with the magnetic lattice. We anticipate that controlled defect creation allows for tailor-made complex magnetic textures and phases with the unique ingredient of direct optical access.

cond-mat.mes-hall↗

arXiv2021

MACCIF-TDNN: Multi aspect aggregation of channel and context interdependence features in TDNN-based speaker verification

Most of the recent state-of-the-art results for speaker verification are achieved by X-vector and its subsequent variants. In this paper, we propose a new network architecture which aggregates the channel and context interdependence features from multi aspect based on Time Delay Neural Network (TDNN). Firstly, we use the SE-Res2Blocks as in ECAPA-TDNN to explicitly model the channel interdependence to realize adaptive calibration of channel features, and process local context features in a multi-scale way at a more granular level compared with conventional TDNN-based methods. Secondly, we explore to use the encoder structure of Transformer to model the global context interdependence features at an utterance level which can capture better long term temporal characteristics. Before the pooling layer, we aggregate the outputs of SE-Res2Blocks and Transformer encoder to leverage the complementary channel and context interdependence features learned by themself respectively. Finally, instead of performing a single attentive statistics pooling, we also find it beneficial to extend the pooling method in a multi-head way which can discriminate features from multiple aspect. The proposed MACCIF-TDNN architecture can outperform most of the state-of-the-art TDNN-based systems on VoxCeleb1 test sets.

cs.SD↗

arXiv2021

Eshelby-twisted 3D moire superlattices

Twisted bilayers of van der Waals materials have recently attracted great attention due to their tunable strongly correlated phenomena. Here, we investigate the chirality-specific physics in 3D moiré superlattices induced by Eshelby twist. Our direct DFT calculations reveal helical rotation leads to optical circular dichroism, and chirality-specific nonlinear Hall effect, even though there is no magnetization or magnetic field. Both these phenomena can be reversed by changing the structural chirality. This provides a way to constructing chirality-specific materials.

cond-mat.mtrl-sci↗