arXiv subjects

Yan He

Publications and source records attributed to Yan He.

At least 37 records · Page 2Linked to original sources

arXiv2025

Two-component atomic Fermi superfluid with spin-orbital coupling in thin spherical-shell geometry

We present a theory of two-component atomic Fermi superfluid with tunable pairing interaction in a thin spherical shell subject to spin-orbit coupling (SOC). By incorporating SOC into the Fermi superfluid in the BCS-Bose Einstein condensation (BEC) crossover, we obtain the energy spectrum and equations of state. While the order parameter and chemical potential are suppressed by SOC on the BCS side, the former remains positive but the latter may be pushed to negative values by SOC. Meanwhile, the compressibility exhibits kinks as the pairing interaction or SOC varies, indicating singular behavior of higher-derivatives of the free energy despite the presence of the superfluid order parameter. The minimum of the energy dispersion indicates a decoupling of the energy gap from the order parameter, and the compressibility kinks occur when the energy gap approaches zero. We found the particle-hole mixing in the Fermi superfluid essential for the compressibility kinks since a Fermi gas with the same SOC but no pairing interaction only exhibits complicated dispersions but no singular behavior. Therefore, our results show that a combination of superfluid, SOC, and geometry can lead to interesting phenomena. We also discuss possible experimental realizations and implications.

cond-mat.quant-gas↗

arXiv2025

A Prototype-Guided Coarse Annotations Refining Approach for Whole Slide Images

The fine-grained annotations in whole slide images (WSIs) show the boundaries of various pathological regions. However, generating such detailed annotation is often costly, whereas the coarse annotations are relatively simpler to produce. Existing methods for refining coarse annotations often rely on extensive training samples or clean datasets, and fail to capture both intra-slide and inter-slide latent sematic patterns, limiting their precision. In this paper, we propose a prototype-guided approach. Specifically, we introduce a local-to-global approach to construct non-redundant representative prototypes by jointly modeling intra-slide local semantics and inter-slide contextual relationships. Then a prototype-guided pseudo-labeling module is proposed for refining coarse annotations. Finally, we employ dynamic data sampling and re-finetuning strategy to train a patch classifier. Extensive experiments on three publicly available WSI datasets, covering lymph, liver, and colorectal cancers, demonstrate that our method significantly outperforms existing state-of-the-art (SOTA) methods. The code will be available.

cs.CV↗

arXiv2025

The Uhlmann Phase Winding in Bose-Einstein Condensates at Finite Temperature

We investigate the Uhlmann phase, a generalization of the celebrated Berry phase, for Bose-Einstein condensates (BECs) at finite temperature. The Uhlmann phase characterizes topological properties of mixed states, in contrast to the Berry phase which is defined for pure states at zero temperature. Using the $SU(1,1)$ symmetry of the Bogoliubov Hamiltonian, we derive a general formula for the Uhlmann phase of BECs. Numerical calculations reveal that the Uhlmann phase can differ from the Berry phase in the zero-temperature limit, contrary to previous studies. As the temperature increases, the Uhlmann phase exhibits a winding behavior, and we relate the total winding degree to the Berry phase. This winding indicates that the Uhlmann phase takes values on a Riemann surface. Furthermore, we propose an experimental scheme to measure the Uhlmann phase of BECs by purifying the density matrix using an atomic interferometer.

cond-mat.quant-gas↗

arXiv2025

Trinity: A Modular Humanoid Robot AI System

In recent years, research on humanoid robots has garnered increasing attention. With breakthroughs in various types of artificial intelligence algorithms, embodied intelligence, exemplified by humanoid robots, has been highly anticipated. The advancements in reinforcement learning (RL) algorithms have significantly improved the motion control and generalization capabilities of humanoid robots. Simultaneously, the groundbreaking progress in large language models (LLM) and visual language models (VLM) has brought more possibilities and imagination to humanoid robots. LLM enables humanoid robots to understand complex tasks from language instructions and perform long-term task planning, while VLM greatly enhances the robots' understanding and interaction with their environment. This paper introduces \textcolor{magenta}{Trinity}, a novel AI system for humanoid robots that integrates RL, LLM, and VLM. By combining these technologies, Trinity enables efficient control of humanoid robots in complex environments. This innovative approach not only enhances the capabilities but also opens new avenues for future research and applications of humanoid robotics.

cs.RO↗

arXiv2025

Design-Agnostic Distributed Timing Fault Injection Monitor With End-to-End Design Automation

Fault injection attacks induce hardware failures in circuits and exploit these faults to compromise the security of the system. It has been demonstrated that FIAs can bypass system security mechanisms, cause faulty outputs, and gain access to secret information. Certain types of FIAs can be mounted with little effort by tampering with clock signals and or the chip operating conditions. To mitigate such low cost, yet powerful attacks, we propose a fully synthesizable and distributable in situ fault injection monitor that employs a delay locked loop to track the pulsewidth of the clock. We further develop a fully automated design framework to optimize and implement the FIA monitors at any process node. Our design is fabricated and verified in 65 nm CMOS technology with a small footprint of 1500 um2. It can lock to clock frequencies from 2 MHz to 1.26 GHz while detecting all 12 types of possible clock glitches, as well as timing FIA injections via the supply voltage, electromagnetic signals, and chip temperature.

eess.SY↗

arXiv2024

Two-component repulsive atomic Fermi gases in a thin spherical shell

We present possible ground-state structures of two-component atomic Fermi gases with repulsive interactions in a thin spherical shell geometry by implementing a self-consistent Hartree-Fock approximation. The system exhibits a miscible-immiscible transition from a homogeneous mixture to two-chunk phase separation as the interaction strength crosses a critical value. While the critical value is relatively insensitive to population imbalance for equal-mass mixtures, it decreases with the mass ratio when mass-imbalance is present. The interaction may be tuned by the two-body scattering length or the radius of the sphere, thereby allowing the system to cross the transition by varying different parameters. When the atoms on the sphere are rotating, three-chunk sandwich structures emerge in mass-imbalanced mixtures as a consequence of maximal angular momentum along the rotation axis. Some indications of geometric effects and possible experimental implications are also discussed.

cond-mat.quant-gas↗

arXiv2024

IGroupSS-Mamba: Interval Group Spatial-Spectral Mamba for Hyperspectral Image Classification

Hyperspectral image (HSI) classification has garnered substantial attention in remote sensing fields. Recent Mamba architectures built upon the Selective State Space Models (S6) have demonstrated enormous potential in long-range sequence modeling. However, the high dimensionality of hyperspectral data and information redundancy pose challenges to the application of Mamba in HSI classification, suffering from suboptimal performance and computational efficiency. In light of this, this paper investigates a lightweight Interval Group Spatial-Spectral Mamba framework (IGroupSS-Mamba) for HSI classification, which allows for multi-directional and multi-scale global spatial-spectral information extraction in a grouping and hierarchical manner. Technically, an Interval Group S6 Mechanism (IGSM) is developed as the core component, which partitions high-dimensional features into multiple non-overlapping groups at intervals, and then integrates a unidirectional S6 for each group with a specific scanning direction to achieve non-redundant sequence modeling. Compared to conventional applying multi-directional scanning to all bands, this grouping strategy leverages the complementary strengths of different scanning directions while decreasing computational costs. To adequately capture the spatial-spectral contextual information, an Interval Group Spatial-Spectral Block (IGSSB) is introduced, in which two IGSM-based spatial and spectral operators are cascaded to characterize the global spatial-spectral relationship along the spatial and spectral dimensions, respectively. IGroupSS-Mamba is constructed as a hierarchical structure stacked by multiple IGSSB blocks, integrating a pixel aggregation-based downsampling strategy for multiscale spatial-spectral semantic learning from shallow to deep stages. Extensive experiments demonstrate that IGroupSS-Mamba outperforms the state-of-the-art methods.

cs.CV↗

arXiv2024

A novel machine learning method to detect double-$Λ$ hypernuclear events in nuclear emulsions

A novel method was developed to detect double-$Λ$ hypernuclear events in nuclear emulsions using machine learning techniques. The object detection model, the Mask R-CNN, was trained using images generated by Monte Carlo simulations, image processing, and image-style transformation based on generative adversarial networks. Despite being exclusively trained on $\prescript{6\ }{ΛΛ}{\rm{He}}$ events, the model achieved a detection efficiency of 93.8$\%$ for $\prescript{6\ }{ΛΛ}{\rm{He}}$ and 82.0$\%$ for $\prescript{5\ }{ΛΛ}{\rm{H}}$ events in the produced images. In addition, the model demonstrated its ability to detect the $\prescript{6\ }{ΛΛ}{\rm{He}}$ event named the Nagara event, which is the only uniquely identified double-$Λ$ hypernuclear event reported to date. It also exhibited a proper segmentation of the event topology. Furthermore, after analyzing 0.2$\%$ of the entire emulsion data from the J-PARC E07 experiment utilizing the developed approach, six new candidates for double-$Λ$ hypernuclear events were detected, suggesting that more than 2000 double-strangeness hypernuclear events were recorded in the entire dataset. This method is sufficiently effective for mining more latent double-$Λ$ hypernuclear events recorded in nuclear emulsion sheets by reducing the time required for manual visual inspection by a factor of five hundred.

hep-ex↗

arXiv2024

3DSS-Mamba: 3D-Spectral-Spatial Mamba for Hyperspectral Image Classification

Hyperspectral image (HSI) classification constitutes the fundamental research in remote sensing fields. Convolutional Neural Networks (CNNs) and Transformers have demonstrated impressive capability in capturing spectral-spatial contextual dependencies. However, these architectures suffer from limited receptive fields and quadratic computational complexity, respectively. Fortunately, recent Mamba architectures built upon the State Space Model integrate the advantages of long-range sequence modeling and linear computational efficiency, exhibiting substantial potential in low-dimensional scenarios. Motivated by this, we propose a novel 3D-Spectral-Spatial Mamba (3DSS-Mamba) framework for HSI classification, allowing for global spectral-spatial relationship modeling with greater computational efficiency. Technically, a spectral-spatial token generation (SSTG) module is designed to convert the HSI cube into a set of 3D spectral-spatial tokens. To overcome the limitations of traditional Mamba, which is confined to modeling causal sequences and inadaptable to high-dimensional scenarios, a 3D-Spectral-Spatial Selective Scanning (3DSS) mechanism is introduced, which performs pixel-wise selective scanning on 3D hyperspectral tokens along the spectral and spatial dimensions. Five scanning routes are constructed to investigate the impact of dimension prioritization. The 3DSS scanning mechanism combined with conventional mapping operations forms the 3D-spectral-spatial mamba block (3DMB), enabling the extraction of global spectral-spatial semantic representations. Experimental results and analysis demonstrate that the proposed method outperforms the state-of-the-art methods on HSI classification benchmarks.

cs.CV↗

arXiv2024

Structure and scaling of Kitaev chain across a quantum critical point in real space

The spatial Kibble-Zurek mechanism (KZM) is applied to the Kitaev chain with inhomogeneous pairing interactions that vanish in half of the lattice and result in a quantum critical point separating the superfluid and normal-gas phases in real space. The weakly-interacting BCS theory predicts scaling behavior of the penetration of the pair wavefunction into the normal-gas region different from conventional power-law results due to the non-analytic dependence of the BCS order parameter on the interaction. The Bogoliubov-de Gennes (BdG) equation produces numerical results confirming the scaling behavior and hints complications in the strong-interaction regime. The limiting case of the step-function quench shows the dominance of the BCS coherence length in absence of additional length scale. Furthermore, the energy spectrum and wavefunctions from the BdG equation show abundant in-gap states from the normal-gas region in addition to the topological edge states.

cond-mat.supr-con↗

arXiv2024

Mobility edges in non-Hermitian models with slowly varying quasi-periodic disorders

We investigate the appearance of mobility edges in a one-dimensional non-Hermitian tight-banding model with alternating hopping constants and slowly varying quasi-periodic on-site potentials. Due to the presence of slowly varying exponent, the parity-time (PT) symmetry of this model is broken and its spectra is complex. It is found that the spectrum of this model can be divided into three different types of patterns depending on the magnitude of the quasi-periodic potential. As the amplitude of the potential increases from small to large, the initially well defined mobility edges become blurred gradually and then eventually disappear for large enough potential. This behavior of the mobility edges is also confirmed by a detailed study of the winding number of the complex spectra of this non-Hermitian model.

cond-mat.dis-nn↗

arXiv2023

Volume comparison theorem with respect to sigma-2 curvature

In this paper, we investigate the volume comparison theorem related to $σ_2$-curvature. In particular, we show that volume comparison theorem with respect to $σ_2$-curvature holds for metrics close to strictly stable positive Einstein metrics. By applying similar techniques, we derive the local rigidity theorem for strictly stable Ricci flat manifolds with respect to $σ_2$-curvature, which shows it admits no metric with positive $σ_2$-curvature near strictly stable Ricci-flat metrics.

math.DG↗

arXiv2023

Disorder effects on the Topological Superconductor with Hubbard Interactions

We study the two-dimensional disordered topological superconductor with Hubbard interactions. When the magnitude of the pairing potential is tuned to special values, this interacting model is exactly solvable even when disorders are imposed on the potential term or coupling constants. The topology of this model is investigated in detail by the real space Chern number formula, which computes the topological index of disordered systems to high precisions. It is found that the disorders can drive the system from topological trivial phase to a non-trivial phase, which generalizes the topological Anderson phenomena to interacting models. The self-consistent Born approximation is also employed to understand the influence of the disorders on the parameters of the interacting topological superconductor. It provide an alternative way to understand the topological transitions at weak disordered region.

cond-mat.dis-nn↗

arXiv2023

Vortex structure and spectrum of atomic Fermi superfluid in a spherical bubble trap

The structures of multiply quantized vortices (MQVs) of an equal-population atomic Fermi superfluid in a rotating spherical bubble trap approximated as a thin shell are analyzed by solving the Bogoliubov-de Gennes (BdG) equation throughout the BCS-Bose Einstein condensation (BEC) crossover. Consistent with the Poincare-Hopf theorem, a pair of vortices emerge at the poles of the rotation axis in the presence of azimuthal symmetry, and the compact geometry provides confinement for the MQVs. While the single-vorticity vortex structure is similar to that in a planar geometry, higher-vorticity vortices exhibit interesting phenomena at the vortex center, such as a density peak due to accumulation of a normal Fermi gas and reversed circulation of current due to in-gap states carrying angular momentum, in the BCS regime but not the BEC regime because of the subtle relations between the order parameter and density. The energy spectrum shows the number of the in-gap state branches corresponds to the vorticity of a vortex, and an explanation based on a topological correspondence is provided.

cond-mat.quant-gas↗

arXiv2023

ASCH-PUF: A "Zero" Bit Error Rate CMOS Physically Unclonable Function with Dual-Mode Low-Cost Stabilization

Physically unclonable functions (PUFs) are increasingly adopted for low-cost and secure secret key and chip ID generations for embedded and IoT devices. Achieving 100% reproducible keys across wide temperature and voltage variations over the lifetime of a device is critical and conventionally requires large masking or Error Correction Code (ECC) overhead to guarantee. This paper presents an Automatic Self Checking and Healing (ASCH) stabilization technique for a state-of-the-art PUF cell design based on sub-threshold inverter chains. The ASCH system successfully removes all unstable PUF cells without the need for expensive temperature sweeps during unstable bit detection. By accurately finding all unstable bits without expensive temperature sweeps to find all unstable bits, ASCH achieves ultra-low bit error rate (BER), thus significantly reducing the costs of using ECC and enrollment. Our ASCH can operate in two modes, a static mode (S-ASCH) with a conventional pre-enrolled unstable bit mask and a dynamic mode (D-ASCH) that further eliminates the need for non-volatile memories (NVMs) for storing masks. The proposed ASCH-PUF is fabricated and evaluated in 65nm CMOS. The ASCH system achieves "0" Bit Error Rate (BER, < 1.77E-9) across temperature variations of -20°C to 125°C, and voltage variations of 0.7V to 1.4V, by masking 31% and 35% of all fabricated PUF bits in S-ASCH and D-ASCH mode respectively. The prototype achieves a measured throughput of 11.4 Gbps with 0.057 fJ/b core energy efficiency at 1.2V, 25°C.

cs.CR↗

arXiv2023

Winding real and order-parameter spaces via lump solitons of spinor BEC on sphere

The three condensate wavefunctions of a spinor BEC on a spherical shell can map the real space to the order-parameter space that also has a spherical geometry, giving rise to topological excitations called lump solitons. The homotopy of the mapping endows the lump solitons with quantized winding numbers counting the wrapping between the two spaces. We present several lump-soliton solutions to the nonlinear coupled equations minimizing the energy functional. The energies of the lump solitons with different winding numbers indicate coexistence of lumps with different winding numbers and a lack of advantage to break a higher-winding lump soliton into multiple lower-winding ones. Possible implications are discussed since the predictions are testable in cold-atom experiments.

cond-mat.quant-gas↗

arXiv2023

A study of the limits of imaging capability due to water scattering effects in underwater ghost imaging

Underwater ghost imaging is an effective means of underwater detection. In this paper, a theoretical and experimental study of underwater ghost imaging is carried out by combining the description of underwater optical field transmission with the inherent optical parameters of the water body. This paper utilizes the Wells model and the approximate S-S scattering phase function to create a model for optical transmission underwater. The second-order Glauber function of the optical field is then employed to analyze the scattering field's degradation during the transmission process. This analysis is used to evaluate the impact of the water body on ghost imaging. The simulation and experimental results verify that the proposed underwater ghost imaging model can better describe the degradation effect of water bodies on ghost imaging. A series of experiments comparing underwater ghost imaging at different detection distances are also carried out in this paper. In the experiments, cooperative targets can be imaged up to 65.2m (9.3AL, at attenuation coefficient c=0.1426m-1 and the scattering coefficient b=0.052m-1) and non-cooperative targets up to 41.2m (6.4AL, at c=0.1569m-1 and b=0.081m-1) . By equating the experimental maximum imaged attenuation length for cooperative targets to Jerlov-I water (b=0.002m-1 and a=0.046m-1), the system will have a maximum imaging distance of 193m. Underwater ghost imaging is expected to achieve longer-range imaging by optimizing the system emission energy and detection sensitivity.

physics.optics↗

arXiv2023

Geometric phases of Topological Systems under Quench Process

We study the time evolution of geometric phases of one dimensional topological models under the quench dynamics. Taking the Creutz ladder model as an example, it is found that the Berry phase is fixed as the parameter is suddenly tuned across the topological phase boundary, given that the chiral symmetry of the model is preserved. At finite temperature, the Uhlmann phase displays abrupt jumps between the two quantized values, which indicates the topological transition at certain times after the quench. Both the Berry and Uhlmann phase will deviate from quantized values if the chiral symmetry of the model is broken. The relation between the Uhlmann phase and Loshmidt rate function under the quench process is also discussed.

cond-mat.mes-hall↗