arXiv subjects

Jin Hu

Publications and source records attributed to Jin Hu.

At least 37 records · Page 2Linked to original sources

arXiv2026

Observation of a structurally driven, reversible topological phase transition in a distorted square net material

Topological materials hold immense promise for exhibiting exotic quantum phenomena, yet achieving controllable topological phase transitions remains challenging. Here, we demonstrate a structurally driven, reversible topological phase transition in the distorted square net material GdPS, induced via in situ potassium dosing. Using angle-resolved photoemission spectroscopy and first principles calculations, we demonstrate a cascade of topological phases in the sub-surface P layer: from a large, topologically trivial band gap to a gapless Dirac cone state with a 2 eV dispersion, and finally to a two-dimensional topological insulator as inferred from theory. This evolution is driven by subtle structural distortions in the first P layer caused by potassium adsorption, which in turn contribute to the band gap closure and topological phase transition. Furthermore, the ability to manipulate the topology of a sub-surface layer in GdPS offers a unique route for exploring and controlling topological states in bulk materials.

cond-mat.mtrl-sci↗

arXiv2026

Relaxation time approximation revisited and non-analytical structure in retarded correlators

In this paper, we give a rigorous mathematical justification for the relaxation time approximation (RTA) model. We find that only the RTA with an energy-independent relaxation time can be justified in the case of hard interactions. Accordingly, we propose an alternative approach to restore the collision invariance lacking in traditional RTA. Besides, we provide a general statement on the non-analytical structures in the retarded correlators within the kinetic description. For hard interactions, hydrodynamic poles are the long-lived modes. Whereas for soft interactions, commonly encountered in relativistic kinetic theory, the gapless eigenvalue spectrum of linearized collision operator leads to gapless branch-cuts. We note that particle mass and inhomogeneous perturbations would complicate the above-mentioned non-analytical structures.

hep-ph↗

arXiv2025

Rectifying Latent Space for Generative Single-Image Reflection Removal

Single-image reflection removal is a highly ill-posed problem, where existing methods struggle to reason about the composition of corrupted regions, causing them to fail at recovery and generalization in the wild. This work reframes an editing-purpose latent diffusion model to effectively perceive and process highly ambiguous, layered image inputs, yielding high-quality outputs. We argue that the challenge of this conversion stems from a critical yet overlooked issue, i.e., the latent space of semantic encoders lacks the inherent structure to interpret a composite image as a linear superposition of its constituent layers. Our approach is built on three synergistic components, including a reflection-equivariant VAE that aligns the latent space with the linear physics of reflection formation, a learnable task-specific text embedding for precise guidance that bypasses ambiguous language, and a depth-guided early-branching sampling strategy to harness generative stochasticity for promising results. Extensive experiments reveal that our model achieves new SOTA performance on multiple benchmarks and generalizes well to challenging real-world cases.

cs.CV↗

arXiv2025

Pre-emptive parametric kill switch for evaporative atomic sources in vacuum

A robust pre-emptive kill switch for cold atom experiments is introduced to significantly reduce costly system reassembly or replacement. The design incorporates upper (alarm) and lower (evaporation) event detection mechanisms based on predefined thresholds. Meanwhile, a duty cycle timing methodology is used to avert unintentional activation of the dispenser in circumstances where pulse signals occur. The circuit employs generic components, a modular design, and formalized logic, ensuring cost-effectiveness, making the design suitable for school laboratories and other research environments. This design is highly versatile and can be applied to other sensitive devices beyond dispensers, such as heating filaments, titanium sublimation pumps, tungsten lamps, and comparable systems.

physics.atom-ph↗

arXiv2025

Evolution of Magnetoresistance in the magnetic topological semimetals NdSbxTe2-x

Magnetic topological semimetals LnSbTe (Ln = lanthanide elements) provide a platform to study the interplay of structure, magnetism, topology, and electron correlations. Varying Sb and Te compositions in LnSbxTe2-x can effectively control the electronic, magnetic, and transport properties. Here, we report the evolution of transport properties with Sb and Te contents in NdSbxTe2-x, (0 < x < 1). Our work reveals nonmonotonic evolution in magnetoresistance with varying composition stoichiometry. Specifically, reducing Sb content x leads to strong negative magnetoresistance up to 99.9%. Such a strong magnetoresistance, which is likely attributed to the interplay between structure, magnetism, and electronic bands, establishes this material as a promising platform for investigating topological semimetal for future device applications.

cond-mat.mtrl-sci↗

arXiv2025

Exploring Semantic-constrained Adversarial Example with Instruction Uncertainty Reduction

Recently, semantically constrained adversarial examples (SemanticAE), which are directly generated from natural language instructions, have become a promising avenue for future research due to their flexible attacking forms. To generate SemanticAEs, current methods fall short of satisfactory attacking ability as the key underlying factors of semantic uncertainty in human instructions, such as referring diversity, descriptive incompleteness, and boundary ambiguity, have not been fully investigated. To tackle the issues, this paper develops a multi-dimensional instruction uncertainty reduction (InSUR) framework to generate more satisfactory SemanticAE, i.e., transferable, adaptive, and effective. Specifically, in the dimension of the sampling method, we propose the residual-driven attacking direction stabilization to alleviate the unstable adversarial optimization caused by the diversity of language references. By coarsely predicting the language-guided sampling process, the optimization process will be stabilized by the designed ResAdv-DDIM sampler, therefore releasing the transferable and robust adversarial capability of multi-step diffusion models. In task modeling, we propose the context-encoded attacking scenario constraint to supplement the missing knowledge from incomplete human instructions. Guidance masking and renderer integration are proposed to regulate the constraints of 2D/3D SemanticAE, activating stronger scenario-adapted attacks. Moreover, in the dimension of generator evaluation, we propose the semantic-abstracted attacking evaluation enhancement by clarifying the evaluation boundary, facilitating the development of more effective SemanticAE generators. Extensive experiments demonstrate the superiority of the transfer attack performance of InSUR. Moreover, we realize the reference-free generation of semantically constrained 3D adversarial examples for the first time.

cs.AI↗

arXiv2025

DynamicPAE: Generating Scene-Aware Physical Adversarial Examples in Real-Time

Physical adversarial examples (PAEs) are regarded as whistle-blowers of real-world risks in deep-learning applications, thus worth further investigation. However, current PAE generation studies show limited adaptive attacking ability to diverse and varying scenes, revealing the urgent requirement of dynamic PAEs that are generated in real time and conditioned on the observation from the attacker. The key challenge in generating dynamic PAEs is learning the sparse relation between PAEs and the observation of attackers under the noisy feedback of attack training. To address the challenge, we present DynamicPAE, the first generative framework that enables scene-aware real-time physical attacks. Specifically, to address the noisy feedback problem that obfuscates the exploration of scene-related PAEs, we introduce the residual-guided adversarial pattern exploration technique. Residual-guided training, which relaxes the attack training with a reconstruction task, is proposed to enrich the feedback information, thereby achieving a more comprehensive exploration of PAEs. To address the alignment problem between the trained generator and the real-world scenario, we introduce the distribution-matched attack scenario alignment, consisting of the conditional-uncertainty-aligned data module and the skewness-aligned objective re-weighting module. The former aligns the training environment with the incomplete observation of the real-world attacker. The latter facilitates consistent stealth control across different attack targets with the skewness controller. Extensive digital and physical evaluations demonstrate the superior attack performance of DynamicPAE, attaining a 2.07 $\times$ boost (58.8% average AP drop under attack) on representative object detectors (e.g., DETR) over state-of-the-art static PAE generating methods. Overall, our work opens the door to end-to-end modeling of dynamic PAEs.

cs.CV↗

arXiv2025

Anisotropic linear waves and breakdown of the momentum expansion in spin magnetohydrodynamics

We formulate spin magnetohydrodynamics (MHD) by including the magnetic-flux and total angular momentum conservation laws in the hydrodynamic framework. To specify the local angular momentum conservation, we choose the totally antisymmetric spin current. The entropy-current analysis allows for ten dissipative first-order transport coefficients including anisotropic spin relaxation rates and the conversion rate between a vorticity (shear) to a symmetric stress (antisymmetric torque), as well as anisotropic viscosities and resistivities. By employing the linear-mode analysis, we solve the first-order spin MHD equations to determine the dispersion relations with the complete information of anisotropy retained. Our analytic solutions indicate that the small-momentum expansion is spoiled by blow up of the higher-order terms when the angle between the momentum and the magnetic field approaches the right angle. This also reveals the existence of another expansion parameter, and, in light of it, we provide solutions in an alternative series expression beyond the critical angle. We confirm that these two series expansions work well in the appropriate angle ranges as compared with numerical results. Building on our findings regarding the breakdown of the small-momentum expansion in first-order theory, we proceed to discussing how these first-order solutions are modified when we include the relaxation dynamics for dissipative modes with the Israel-Stewart framework. We find that, due to the presence of the critical behavior in the first-order solutions, there remains a diffusive window even after the relaxation dynamics is introduced.

hep-ph↗

arXiv2025

Analytical Solution of the Nonlinear Relativistic Boltzmann Equation

We provide an exact analytical solution to the nonlinear relativistic Boltzmann equation for a homogeneous, anisotropically scattering massless gas. Utilizing a BKW-like trial solution, we cast the Boltzmann equation into a set of nonlinear coupled equations for scalar moments, based on which the analytical solution is derived. One remarkable feature of our analytical solution lies in the nontrivial scattering angle dependence. We also show that this analytical solution admits a stable fixed point corresponding to the equilibrium solution as long as the parameters are physically feasible. Furthermore, a clear correspondence between our solution and the BKW solution pertaining to nonrelativistic Maxwell molecules is established, thereby clarifying the non-existence of a BKW-type solution in the relativistic domain for massive particles.

hep-ph↗

arXiv2025

NTIRE 2025 Image Shadow Removal Challenge Report

This work examines the findings of the NTIRE 2025 Shadow Removal Challenge. A total of 306 participants have registered, with 17 teams successfully submitting their solutions during the final evaluation phase. Following the last two editions, this challenge had two evaluation tracks: one focusing on reconstruction fidelity and the other on visual perception through a user study. Both tracks were evaluated with images from the WSRD+ dataset, simulating interactions between self- and cast-shadows with a large number of diverse objects, textures, and materials.

cs.CV↗

arXiv2025

Normal mode analysis within a mutilated relaxation time approximation

In this paper, we present a detailed analysis of normal modes based on the Boltzmann equation within the mutilated relaxation time approximation (RTA). Using this linearized effective kinetic description, our analysis encompasses a complete order calculation in wavenumber k, extending the conventional hydrodynamic mode analysis to intermediate and short-wavelength regions. Furthermore, our linear mode analysis can provide a natural classification of kinetic modes into collective modes and non-collective single-particle excitations. In the case of an energy-independent relaxation time, the behavior of hydrodynamic onset transitions is recovered (Romatschke in Eur Phys J C 76:352, 2016). However, for the case with an energy-dependent relaxation time, the distinct classification becomes less clear, as the location of hydrodynamic modes is not well separated from non-hydrodynamic modes.

hep-ph↗

arXiv2025

ShadowHack: Hacking Shadows via Luminance-Color Divide and Conquer

Shadows introduce challenges such as reduced brightness, texture deterioration, and color distortion in images, complicating a holistic solution. This study presents \textbf{ShadowHack}, a divide-and-conquer strategy that tackles these complexities by decomposing the original task into luminance recovery and color remedy. To brighten shadow regions and repair the corrupted textures in the luminance space, we customize LRNet, a U-shaped network with a rectified attention module, to enhance information interaction and recalibrate contaminated attention maps. With luminance recovered, CRNet then leverages cross-attention mechanisms to revive vibrant colors, producing visually compelling results. Extensive experiments on multiple datasets are conducted to demonstrate the superiority of ShadowHack over existing state-of-the-art solutions both quantitatively and qualitatively, highlighting the effectiveness of our design. Our code will be made publicly available.

cs.CV↗

arXiv2025

Quantum oscillation studies of the nodal line semimetal Ni3In2S2-xSex

Ternary shandite compounds with the general formula T3M2X2 (T = Ni, Co, Rh or Pd; M = Sn, In or Pb and X = S or Se) have emerged as a large pool of topological semimetals. This family of compounds hosts different topological phases for various combinations of T, M and X. This paper reports the observation of quantum oscillations under the high magnetic fields in Ni3In2S2-xSex single crystals. Angular dependence of oscillation frequency suggests an evolution of the Fermi surface from three-dimensional to two-dimensional on Se substitution for S in Ni3In2S2. The effective mass obtained for each composition by fitting the oscillation amplitude with the Lifshitz-Kosevich formula, shows no significant change, suggesting that the topological phase might be relatively robust against enhanced SOC upon Se doping in Ni3In2S2.

cond-mat.mtrl-sci↗

arXiv2025

Large Negative Magnetoresistance in off-Stochiometric Topological Material PrSbTe

Magnetic topological materials LnSbTe (Ln = lanthanide) have attracted intensive attention because of the presence of interplay between magnetism, topological, and electron correlations depending on the choices of magnetic Ln elements. Varying Sb and Te composition is an efficient approach to control structural, magnetic, and electronic properties. Here we report the composition-dependent properties in PrSbxTe2-x. We identified the tetragonal-to-orthorhombic structure transitions in this material system, and very large negative magnetoresistance in the x = 0.3 composition, which might be ascribed to the coupling between magnetism and transport. Such unusual magnetotransport enables PrSbxTe2-x topological materials as a promising platform for device applications.

cond-mat.mtrl-sci↗

arXiv2025

Large Negative Magnetoresistance in Antiferromagnetic Gd2Se3

Rare earth chalcogenides provide a great platform to study exotic quantum phenomena such as superconductivity and charge density waves. Among various interesting properties, the coupling between magnetism and electronic transport has attracted significant attention. Here, we report the investigation of such coupling in {alpha}-Gd2Se3 single crystals through magnetic, calorimetric, and transport property measurements. {alpha}-Gd2Se3 is found to display an antiferromagnetic ground state below 11 K with metamagnetic spin-flop transitions. The magnetic fluctuations remain strong above the transition temperature. Transport measurements reveal an overall metallic transport behavior with a large negative magnetoresistance of ~ 65% near the magnetic transition temperature, together with positive MR near the field-induced spin-flop transitions, which can be understood in terms of the suppression of spin scattering by the magnetic field.

cond-mat.mtrl-sci↗

arXiv2025

Transition balance in QCD nucleation

As an extended and more complete version of the primary QCD nucleation model presented in Ref. [1], the new model introduces explicitly the transition balance and formulates it in both macroscopic and microscopic descriptions. The microscopic description of the transition balance in QCD nucleation is implemented in a kinetic parton cascade model and tested for a first-order phase transition from gluons to pions in a one-dimensional expansion with Bjorken boost invariance.

hep-ph↗

arXiv2024

H-Matrix Accelerated Direct Matrix Solver for Maxwell's Equations using the Chebyshev-based Nyström Boundary Integral Equation Method

An H-matrix accelerated direct solver employing the high-order Chebyshev-based Boundary Integral Equation (CBIE) method has been formulated, tested, and profiled for performance on high contrast dielectric materials and electrically large perfect electric conductor objects. The matrix fill performance of the CBIE proves to be fast for small to moderately sized problems compared to its counterparts, e.g. the locally corrected Nyström (LCN) method, due to the way it handles the singularities by means of a global change of variable method. However, in the case of electrically large scattering problems, the matrix fill and factorization still dominate the solution time when using a direct solution approach. To address this issue, an H-Matrix framework is employed, effectively resolving the challenge and establishing the CBIE as a competitive high-order method for solving scattering problems with poorly conditioned matrix equations. The efficacy of this approach is demonstrated through extensive numerical results, showcasing its robustness to problems that are electrically large, near physical resonances, or that have large dielectric permittivities. The capability of the proposed solver for handling arbitrary geometries is also demonstrated by considering various scattering examples from complex CAD models.

math.NA↗

arXiv2024

First-order spin magnetohydrodynamics

Based on recent papers, we discuss the formulation of the first-order relativistic spin magnetohydrodynamics (MHD) with the totally antisymmetric spin current and properties of the anisotropic linear waves awaken near an equilibrium configuration. We show that there appears a critical angle in the momentum direction of the linear waves, where a pair of propagating modes turns into purely diffusive modes. Due to this critical behavior, polynomial solutions do not fully capture the angle dependence of the linear waves.

hep-ph↗