arXiv subjects

Zhenhua Ning

Publications and source records attributed to Zhenhua Ning.

11 recordsLinked to original sources

arXiv2026

A Hydrogen-Like Model for Pion and Kaon Masses Based on Dirac Quark-Hamiltonians and Numerical Methods

We consider a relativistic hydrogen-like model for meson mass spectra. The model is based on a Lagrangian with a new general Yang-Mills symmetry. The strong interactions involve a fourth-order field equation that generates a linear confining potential. Notably, this model for meson masses requires quarks to carry only a single `confining charge' $f_c$ rather than three color charges. We classify meson mass spectra into sub-spectra defined by isospin, G-parity, total angular momentum and parity. By applying a numerical solver to the Dirac Hamiltonians--incorporating two short-range confining potentials, we obtain energy eigenvalues in natural units. The model has three coupling constants and one parameter. It provides a robust fit of 31 pions and kaons masses (from $\approx 140 MeV$ to $\approx 2,300 MeV$) to within $\approx 18\%$ of relative percentage error. The model suggests that the confining charge $f_c$=0.045/MeV = 8.87 fm plays the role of the basic length in the quark interactions.

hep-ph↗

arXiv2026

Beyond Heuristics: Learnable Density Control for 3D Gaussian Splatting

While 3D Gaussian Splatting (3DGS) has demonstrated impressive real-time rendering performance, its efficacy remains constrained by a reliance on heuristic density control. Despite numerous refinements to these handcrafted rules, such methods inherently lack the flexibility to adapt to diverse scenes with complex geometries. In this paper, we propose a paradigm shift for density control from rigid heuristics to fully learnable policies. Specifically, we introduce \textbf{LeGS}, a framework that reformulates density control as a parameterized policy network optimized via Reinforcement Learning (RL). Central to our approach is the tailored effective reward function grounded in sensitivity analysis, which precisely quantifies the marginal contribution of individual Gaussians to reconstruction quality. To maintain computational tractability, we derive a closed-form solution that reduces the complexity of reward calculation from $O(N^2)$ to $O(N)$. Extensive experiments on the Mip-NeRF 360, Tanks \& Temples, and Deep Blending datasets demonstrate that \textbf{LeGS} significantly outperforms state-of-the-art methods, striking a superior balance between reconstruction quality and efficiency. The code will be released at https://github.com/AaronNZH/LeGS

cs.CV↗

arXiv2025

Enhancing Spatial Reasoning in Multimodal Large Language Models through Reasoning-based Segmentation

Recent advances in point cloud perception have demonstrated remarkable progress in scene understanding through vision-language alignment leveraging large language models (LLMs). However, existing methods may still encounter challenges in handling complex instructions that require accurate spatial reasoning, even if the 3D point cloud data provides detailed spatial cues such as size and position for identifying the targets. To tackle this issue, we propose Relevant Reasoning Segmentation (R$^2$S), a reasoning-based segmentation framework. The framework emulates human cognitive processes by decomposing spatial reasoning into two sequential stages: first identifying relevant elements, then processing instructions guided by their associated visual priors. Furthermore, acknowledging the inadequacy of existing datasets in complex reasoning tasks, we introduce 3D ReasonSeg, a reasoning-based segmentation dataset comprising 25,185 training samples and 3,966 validation samples with precise annotations. Both quantitative and qualitative experiments demonstrate that the R$^2$S and 3D ReasonSeg effectively endow 3D point cloud perception with stronger spatial reasoning capabilities, and we hope that they can serve as a new baseline and benchmark for future work.

cs.CV↗

arXiv2025

Spin dynamics in itinerant antiferromagnet SrCr$_2$As$_2$

SrCr$_2$As$_2$ is an itinerant antiferromagnet in the same structural family as the SrFe$_2$As$_2$ high-temperature superconductors. We report our calculations of exchange-coupling parameters $J_{ij}$ for SrCr$_2$As$_2$ using a static linear-response method based on first-principles electronic-structure calculations. We find that the dominant nearest-neighbor exchange coupling $J_{\rm{1}} > 0$ is antiferromagnetic whereas the next-nearest-neighbor interaction $J_{\rm{2}} < 0$ is ferromagnetic with $J_{\rm{2}}$/$J_{\rm{1}}$~=~$-0.68$, reinforcing the checkerboard in-plane magnetic structure. Thus, unlike other transition-metal arsenides based on Mn, Fe, or Co, we find no competing magnetic interactions in SrCr$_2$As$_2$, which aligns with experimental findings. Moreover, the orbital resolution of exchange interactions shows that $J_1$ and $J_2$ are dominated by direct exchange mediated by the Cr $d$ orbitals. To validate the calculations we conduct inelastic neutron-scattering measurements on powder samples that show steeply dispersive magnetic excitations arising from the magnetic $Γ$ points and persisting up to energies of at least 175 meV. The spin-wave spectra are then modeled using the Heisenberg Hamiltonian with the theoretically-calculated exchange couplings. The calculated neutron-scattering spectra are in good agreement with the experimental data.

cond-mat.supr-con↗

arXiv2025

Giant coercivity and enhanced intrinsic anomalous Hall effect at vanishing magnetization in a compensated kagome ferrimagnet

Ferrimagnets that can be driven to magnetic compensation show promise for use in spintronics as they exhibit a finite anomalous Hall effect at zero magnetic field without having a significant magnetic moment. Compensated ferrimagnet spintronic devices with both a large anomalous Hall effect and a high coercivity would be simultaneously easy to read and difficult to erase. The kagome ferrimagnet TbMn$_6$Sn$_6$ has been reported to host a large intrinsic anomalous Hall effect. Here, we demonstrate that doping the Mn sites with Cr drives the system towards magnetic compensation. For nearly compensated compositions at low temperatures, giant coercive fields exceeding 14 T are observed. Additionally, Cr doping significantly enhances the intrinsic anomalous Hall effect, which can be attributed to a shift in the Fermi level. Our results extend the range of unique magnetic states observed in kagome materials, demonstrating that chemical doping is an effective strategy to tune and realize these states.

cond-mat.str-el↗

arXiv2024

Three-dimensional nature of anomalous Hall conductivity in YMn6Sn6-xGax, x ~ 0.55

The unique connectivity of kagome lattices gives rise to topological properties, such as flat bands and Dirac cones. When combined with ferromagnetism and a chemical potential near the 2D Dirac points, this structure offers the potential to realize the highly sought-after topological Chern magnetotransport. Recently, there was considerable excitement surrounding this possibility in the ferrimagnetic kagome metal TbMn$_\mathbf{6}$Sn$_\mathbf{6}$. However, density functional theory (DFT) calculations reveal that the 2D Chern gap lies well above the Fermi energy, challenging its relevance in the observed anomalous Hall conductivity. Here, we investigate YMn$_\mathbf{6}$Sn$_\mathbf{5.45}$Ga$_\mathbf{0.55}$, a compound with similar crystallographic, magnetic, and electronic properties to TbMn$_\mathbf{6}$Sn$_\mathbf{6}$. Our findings show that the intrinsic anomalous Hall conductivity in this material, while comparable in magnitude to that in TbMn$_\mathbf{6}$Sn$_\mathbf{6}$, is fully three-dimensional, thus providing experimental evidence that Hall conductivity in this class of materials does not originate from 2D Chern gaps. Additionally, we confirm that the newly proposed empirical scaling relation for extrinsic Hall conductivity is universally governed by spin fluctuations.

cond-mat.mtrl-sci↗

arXiv2024

Magnetic interactions and excitations in SrMnSb$_2$

The magnetic interactions in the antiferromagnetic (AFM) Dirac semimetal candidate SrMnSb$_2$ are investigated using \textit{ab initio} linear response theory and inelastic neutron scattering (INS). Our calculations reveal that the first two nearest in-plane couplings ($J_1$ and $J_2$) are both AFM in nature, indicating a significant degree of spin frustration, which aligns with experimental observations. The orbital resolution of exchange interactions shows that $J_1$ and $J_2$ are dominated by direct and superexchange, respectively. In a broader context, a rigid-band model suggests that electron doping fills the minority spin channel and results in a decrease in the AFM coupling strength for both $J_1$ and $J_2$. To better compare with INS measurements, we calculate the spin wave spectra within a linear spin wave theory, utilizing the computed exchange parameters. Although the calculated spin wave spectra somewhat overestimate the magnon bandwidth, they exhibit overall good agreement with measurements from INS experiments.

cond-mat.mtrl-sci↗

arXiv2023

Boosting Few-shot 3D Point Cloud Segmentation via Query-Guided Enhancement

Although extensive research has been conducted on 3D point cloud segmentation, effectively adapting generic models to novel categories remains a formidable challenge. This paper proposes a novel approach to improve point cloud few-shot segmentation (PC-FSS) models. Unlike existing PC-FSS methods that directly utilize categorical information from support prototypes to recognize novel classes in query samples, our method identifies two critical aspects that substantially enhance model performance by reducing contextual gaps between support prototypes and query features. Specifically, we (1) adapt support background prototypes to match query context while removing extraneous cues that may obscure foreground and background in query samples, and (2) holistically rectify support prototypes under the guidance of query features to emulate the latter having no semantic gap to the query targets. Our proposed designs are agnostic to the feature extractor, rendering them readily applicable to any prototype-based methods. The experimental results on S3DIS and ScanNet demonstrate notable practical benefits, as our approach achieves significant improvements while still maintaining high efficiency. The code for our approach is available at https://github.com/AaronNZH/Boosting-Few-shot-3D-Point-Cloud-Segmentation-via-Query-Guided-Enhancement

cs.CV↗

arXiv2018

Relative Cooling Power Enhancement by Tuning Magneto-structural Stability in Ni-Mn-In Heusler Alloys

Off-stoichiometric Ni$_2$MnIn Heusler alloys have drawn recent attention due to their large magnetocaloric entropy change associated with the first-order magneto-structural transition. Here we present crystal structural, calorimetric and magnetic studies of three compositions. Temperature-dependent X-ray diffraction shows clear structural transition from a 6M modulated monoclinic to a L2$_1$ cubic. A significant enhancement of relative cooling power (RCP) was achieved by tuning the magnetic and structural stability through minor compositional changes, with the measured results quantitatively close to the prediction as a function of the ratio between the martensitic transition ($T_m$) temperature and austenite Curie temperature ($T_C$) although the maximal magnetic induced entropy change ($ΔS_{max}$) reduction is observed in the same time. The results provided an evaluation guideline of RCPs as well as magnetic-induced entropy change in designing practical active materials.

cond-mat.mtrl-sci↗

arXiv2017

Spin Density wave instability in a ferromagnet

Ferromagnetic (FM) and incommensurate spin-density wave (ISDW) states are an unusual set of competing magnetic orders that are seldom observed in the same material without application of a polarizing magnetic field. We report, for the first time, the discovery of an ISDW state that is derived from a FM ground state through a Fermi surface (FS) instability in Fe$_3$Ga$_4$. This was achieved by combining neutron scattering experiments with first principles simulations. Neutron diffraction demonstrates that Fe$_3$Ga$_4$ is in an ISDW state at intermediate temperatures and that there is a conspicuous re-emergence of ferromagnetism above 360 K. First principles calculations show that the ISDW ordering wavevector is in excellent agreement with a prominent nesting condition in the spin-majority FS demonstrating the discovery of a novel instability for FM metals; ISDW formation due to Fermi surface nesting in a spin-polarized Fermi surface.

cond-mat.str-el↗

arXiv2017

TDDFT calculations for excitation spectra of III-V ternary alloys

We adopted the time-dependent density functional theory (TDDFT) within the linear augmented Slater-type orbitals (LASTO) basis and the cluster averaging method to compute the {\color{red}excitation} spectra of III-V ternary alloys with arbitrary concentration $x$. The TDDFT was carried out with the use of adiabatic meta-generalized gradient approximation (mGGA), which contains the $1/q^2$ singularity in the dynamical exchange-correlation kernel ($f_{XC,00}(\mathbf{q})$) as $q\rightarrow 0$. We found that by using wave functions obtained in local density approximation (LDA) while using mGGA to compute self-energy correction to the band structures, we can get {\color{red} good overall} agreement between theoretical results and experimental data for the excitation spectra. Thus, our studies provide some insight into the theoretical calculation of optical spectra of semiconductor alloys.

physics.comp-ph↗