arXiv subjects

Jiawen Zhang

Publications and source records attributed to Jiawen Zhang.

At least 73 records · Page 4Linked to original sources

arXiv2025

Probing orbital magnetism of a kagome metal CsV3Sb5 by a tuning fork resonator

The recently discovered kagome metal CsV$_3$Sb$_5$ exhibits a complex phase diagram that encompasses frustrated magnetism, topological charge density wave (CDW), and superconductivity. One CDW state that breaks time-reversal symmetry was proposed in this compound, while the exact nature of the putative magnetic state remains elusive. To examine the thermodynamic state of CsV$_3$Sb$_5$ and assess the character of the associated magnetism, we conducted tuning fork resonator measurements of magnetotropic susceptibility over a broad range of angles, magnetic fields, and temperature. We found a cascade of phase transition in the CDW phase. Of particular interest is a highly anisotropic magnetic structure that arises below about 30~K, with a magnetic moment along the $c$-axis that has an extremely small magnitude. This magnetic state demonstrates extremely slow dynamics and small saturate field, all suggest that electronic phase below 30~K breaks time reversal symmetry and has an unconventional origin.

cond-mat.mtrl-sci↗

arXiv2025

Room-temperature dislocation plasticity in ceramics: Methods, Materials, and Mechanisms

Dislocation-mediated plastic deformation in ceramic materials has sparked renewed research interest due to the technological potential of dislocations. Despite the long research history of dislocations as one-dimensional lattice defects in crystalline solids, the understanding of plastically deformable ceramics at room temperature seems lacking. The conventional view holds that ceramics are brittle, difficult to deform at room temperature and exhibit no dislocation plasticity except in small-scale testing such as nanoindentation and nano-micropillar compression. In this review, we attempt to gather the evidence and reports of room-temperature dislocation plasticity in ceramics beyond the nano-/microscale, with a focus on meso-macroscale plasticity. First, we present a mechanical deformation toolbox covering various experimental approaches for assessing the dislocation plasticity, with a focus on bulk plasticity. Second, we provide a materials toolbox listing 44 ceramic compounds that have been reported to exhibit dislocation plasticity at meso-/macroscale under ambient conditions. Finally, we discuss the mechanics of dislocations in ceramics, aiming to establish a foundation for predicting and discovering additional ceramics capable of room-temperature plastic deformation, thereby advancing the development of prospective dislocation-based technologies.

cond-mat.mtrl-sci↗

arXiv2025

Impact of dislocation densities on the microscale strength of single-crystal strontium titanate

Dislocations in ceramics at room temperature are attracting increasing research interest. Dislocations may bring a new perspective for tuning physical and mechanical properties in advanced ceramics. Here, we investigate the dislocation density dependent micromechanical properties of single-crystal SrTiO3 by tuning the dislocation densities (from ~10 to the power of 10 per square meter up to ~10 to the power of 14 per square meter). Using micropillar compression tests, we find the samples exhibit a transition from brittle fracture (if no dislocation is present in the pillars) to plastic yield (with pre-engineered dislocations in the pillars). While within the regime of plastic deformation, the yield strength and plastic flow behavior exhibit a strong dependence on the dislocation density. The yield strength first decreases and then increases with the increase of dislocation densities. Detailed examination via post-mortem transmission electron microscopy reveals a complex evolution of dislocation structure, highlighting the critical role played by dislocations in regulating the brittle/ductile behavior in SrTiO3 at room temperature. Our findings shed new light on dislocation-mediated mechanical properties in ceramics and may provide designing guidelines for the prospective dislocation-based devices.

cond-mat.mtrl-sci↗

arXiv2025

Realizing a topological diode effect on the surface of a topological Kondo insulator

Introducing the concept of topology into material science has sparked a revolution from classic electronic and optoelectronic devices to topological quantum devices. The latter has potential for transferring energy and information with unprecedented efficiency. Here, we demonstrate a topological diode effect on the surface of a three-dimensional material, SmB6, a candidate topological Kondo insulator. The diode effect is evidenced by pronounced rectification and photogalvanic effects under electromagnetic modulation and radiation at radio frequency. Our experimental results and modeling suggest that these prominent effects are intimately tied to the spatially inhomogeneous formation of topological surface states (TSS) at the intermediate temperature. This work provides a manner of breaking the mirror symmetry (in addition to the inversion symmetry), resulting in the formation of pn-junctions between puddles of metallic TSS. This effect paves the way for efficient current rectifiers or energy-harvesting devices working down to radio frequency range at low temperature, which could be extended to high temperatures using other topological insulators with large bulk gap.

cond-mat.str-el↗

arXiv2025

Emergent ferromagnetic ladder excitations in heavy fermion superconductor CeSb$_{2}$

Low-dimensional spin fluctuations play a crucial role in unconventional superconductors, with quasi-one-dimensional spin excitations potentially linked with spin-triplet superconductivity. The heavy fermion superconductor CeSb$_2$ exhibits an unusual large inverted S-shaped upper critical field that suggests a possible triplet pairing state within its pressure-induced superconducting dome. Using inelastic neutron scattering, we discover quasi-one-dimensional magnetic excitations in CeSb$_2$ emerging from nearly square Ce layers with minor orthorhombic deformation. We show that the data are well described by a ferromagnetic spin ladder model, where the "rungs" of the ladder straddle Ce bilayers. Moreover, we find that diffuse excitations akin to those in the ordered phase persist well above $T_{\rm N}$, suggesting that quasi-one-dimensional ferromagnetic paramagnons may significantly contribute to the unusual superconductivity that appears under pressure once magnetic order is suppressed.

cond-mat.supr-con↗

arXiv2025

Orientation-dependent superconductivity and electronic structure of the rare-earth metal/KTaO3 interfaces

The recent discovery of orientation-dependent superconductivity in KTaO3-based interfaces has attracted considerable interest, while the underlying origin remains an open question. Here we report a different approach to tune the interfacial electron gas and superconductivity by forming interfaces between rare-earth (RE) metals (RE being La, Ce, Eu) and KTaO3 substrates with different orientations. We found that the interfacial superconductivity is strongest for the Eu/KTaO3 interfaces, becomes weaker in La/KTaO3 and is absent in Ce/KTaO3. Using in-situ photoemission, we observed distinct valence bands associated with RE metals, as well as a pronounced orientation dependence in the interfacial electronic structure, which can be linked to the orientation-dependent superconductivity. The photoemission spectra show similar double-peak structures for the (111) and (110) oriented interfaces, with an energy separation close to the LO4 phonon of KTaO3. Detailed analyses suggest that this double-peak structure could be attributed to electron-phonon coupling, which might be important for the interfacial superconductivity.

cond-mat.supr-con↗

arXiv2025

SHAPE : Self-Improved Visual Preference Alignment by Iteratively Generating Holistic Winner

Large Visual Language Models (LVLMs) increasingly rely on preference alignment to ensure reliability, which steers the model behavior via preference fine-tuning on preference data structured as ``image - winner text - loser text'' triplets. However, existing approaches often suffer from limited diversity and high costs associated with human-annotated preference data, hindering LVLMs from fully achieving their intended alignment capabilities. We present \projectname, a self-supervised framework capable of transforming the already abundant supervised text-image pairs into holistic preference triplets for more effective and cheaper LVLM alignment, eliminating the need for human preference annotations. Our approach facilitates LVLMs in progressively enhancing alignment capabilities through iterative self-improvement. The key design rationale is to devise preference triplets where the winner text consistently improves in holisticness and outperforms the loser response in quality, thereby pushing the model to ``strive to the utmost'' of alignment performance through preference fine-tuning. For each given text-image pair, SHAPE introduces multiple visual augmentations and pairs them with a summarized text to serve as the winner response, while designating the original text as the loser response. Experiments across \textbf{12} benchmarks on various model architectures and sizes, including LLaVA and DeepSeek-VL, show that SHAPE achieves significant gains, for example, achieving +11.3\% on MMVet (comprehensive evaluation), +1.4\% on MMBench (general VQA), and +8.0\% on POPE (hallucination robustness) over baselines in 7B models. Notably, qualitative analyses confirm enhanced attention to visual details and better alignment with human preferences for holistic descriptions.

cs.CV↗

arXiv2025

Unify and Anchor: A Context-Aware Transformer for Cross-Domain Time Series Forecasting

The rise of foundation models has revolutionized natural language processing and computer vision, yet their best practices to time series forecasting remains underexplored. Existing time series foundation models often adopt methodologies from these fields without addressing the unique characteristics of time series data. In this paper, we identify two key challenges in cross-domain time series forecasting: the complexity of temporal patterns and semantic misalignment. To tackle these issues, we propose the ``Unify and Anchor" transfer paradigm, which disentangles frequency components for a unified perspective and incorporates external context as domain anchors for guided adaptation. Based on this framework, we introduce ContexTST, a Transformer-based model that employs a time series coordinator for structured representation and the Transformer blocks with a context-informed mixture-of-experts mechanism for effective cross-domain generalization. Extensive experiments demonstrate that ContexTST advances state-of-the-art forecasting performance while achieving strong zero-shot transferability across diverse domains.

cs.LG↗

arXiv2025

Three-dimensional mapping of the altermagnetic spin splitting in CrSb

Altermagnetism, a kind of collinear magnetism that is characterized by a momentum-dependent band and spin splitting without net magnetization, has recently attracted considerable interest. Finding altermagnetic materials with large splitting near the Fermi level necessarily requires three-dimensional k-space mapping. While this is crucial for spintronic applications and emergent phenomena, it remains challenging. Here, using synchrotron-based angle-resolved photoemission spectroscopy (ARPES), spin-resolved ARPES and model calculations, we uncover a large altermagnetic splitting, up to ~1.0 eV, near the Fermi level in CrSb. We verify its bulk-type g-wave altermagnetism through systematic three-dimensional k-space mapping, which unambiguously reveals the altermagnetic symmetry and associated nodal planes. Spin-resolved ARPES measurements further verify the spin polarizations of the split bands near Fermi level. Tight-binding model analysis indicates that the large altermagnetic splitting arises from strong third-nearest-neighbor hopping mediated by Sb ions. The large band/spin splitting near Fermi level in metallic CrSb, together with its high TN (up to 705 K) and simple spin configuration, paves the way for exploring emergent phenomena and spintronic applications based on altermagnets.

cond-mat.mtrl-sci↗

arXiv2025

Dislocations and plasticity of KTaO$_3$ perovskite modeled with a new interatomic potential

Potassium tantalate KTaO3 is a cubic, paraelectric perovskite ceramic that exhibits surprising ductility at room temperature as most recently reported. Much like strontium titanate (SrTiO3), plastic deformation is accommodated by dislocations gliding in {110} planes. In this work we propose a new interatomic potential for KTaO3, and apply it to model dislocations with <110> Burgers vector. We demonstrate that dislocations dissociate, and finely characterize their core structure and Peierls potential. Dislocations of edge character can carry a positive or negative electric charge, but we show that charge-neutral configurations are energetically more favorable. We also perform high-resolution electron microscopy to validate our simulation methodology. Comparing our results with other ductile perovskites, we confirm KTaO3 to be ductile, but stiffer than SrTiO3.

cond-mat.mtrl-sci↗

arXiv2025

SecPE: Secure Prompt Ensembling for Private and Robust Large Language Models

With the growing popularity of LLMs among the general public users, privacy-preserving and adversarial robustness have become two pressing demands for LLM-based services, which have largely been pursued separately but rarely jointly. In this paper, to the best of our knowledge, we are among the first attempts towards robust and private LLM inference by tightly integrating two disconnected fields: private inference and prompt ensembling. The former protects users' privacy by encrypting inference data transmitted and processed by LLMs, while the latter enhances adversarial robustness by yielding an aggregated output from multiple prompted LLM responses. Although widely recognized as effective individually, private inference for prompt ensembling together entails new challenges that render the naive combination of existing techniques inefficient. To overcome the hurdles, we propose SecPE, which designs efficient fully homomorphic encryption (FHE) counterparts for the core algorithmic building blocks of prompt ensembling. We conduct extensive experiments on 8 tasks to evaluate the accuracy, robustness, and efficiency of SecPE. The results show that SecPE maintains high clean accuracy and offers better robustness at the expense of merely $2.5\%$ efficiency overhead compared to baseline private inference methods, indicating a satisfactory ``accuracy-robustness-efficiency'' tradeoff. For the efficiency of the encrypted Argmax operation that incurs major slowdown for prompt ensembling, SecPE is 35.4x faster than the state-of-the-art peers, which can be of independent interest beyond this work.

cs.CR↗

arXiv2025

Structural and Physical Properties of the Heavy Fermion Metal Ce$_2$NiAl$_6$Si$_5$

Strongly correlated electrons at the verge of quantum criticality give rise to unconventional phases of matter and behaviors, with the discovery of new quantum critical materials driving synergistic advances in both experiments and theory. In this work, we report the structural and physical properties of a new quaternary Ce-based heavy fermion compound, Ce$_2$NiAl$_6$Si$_5$, synthesized using the self-flux method. This compound forms a layered tetragonal structure (space group $P4/nmm$), with square nets of Ce atoms separated by Si-Al or Ni-Si-Ge layers. Specific heat measurements show a low temperature Sommerfeld coefficient of 1.4 J/mol-Ce K$^{2}$, with a reduced entropy indicative of significant Kondo interactions. Below 0.6 K, an upturn in resistivity and a deviation in magnetic susceptibility suggest the appearance of magnetic ordering or the development of dynamic magnetic correlations, which is further supported by a bulge in specific heat around 0.4 K. These results suggest that Ce$_2$NiAl$_6$Si$_5$ is a layered heavy fermion metal, naturally located in proximity to a spin-density-wave quantum critical point.

cond-mat.str-el↗

arXiv2024

A weight-free characterisation of Yu's Property A

In this short note, we give a complete answer to the question of when the generalised Følner sets exhibiting property A can be chosen to be subsets of the space itself. More precisely, we prove that this holds for any discrete metric space of bounded geometry.

math.MG↗

arXiv2024

HEP-NAS: Towards Efficient Few-shot Neural Architecture Search via Hierarchical Edge Partitioning

One-shot methods have significantly advanced the field of neural architecture search (NAS) by adopting weight-sharing strategy to reduce search costs. However, the accuracy of performance estimation can be compromised by co-adaptation. Few-shot methods divide the entire supernet into individual sub-supernets by splitting edge by edge to alleviate this issue, yet neglect relationships among edges and result in performance degradation on huge search space. In this paper, we introduce HEP-NAS, a hierarchy-wise partition algorithm designed to further enhance accuracy. To begin with, HEP-NAS treats edges sharing the same end node as a hierarchy, permuting and splitting edges within the same hierarchy to directly search for the optimal operation combination for each intermediate node. This approach aligns more closely with the ultimate goal of NAS. Furthermore, HEP-NAS selects the most promising sub-supernet after each segmentation, progressively narrowing the search space in which the optimal architecture may exist. To improve performance evaluation of sub-supernets, HEP-NAS employs search space mutual distillation, stabilizing the training process and accelerating the convergence of each individual sub-supernet. Within a given budget, HEP-NAS enables the splitting of all edges and gradually searches for architectures with higher accuracy. Experimental results across various datasets and search spaces demonstrate the superiority of HEP-NAS compared to state-of-the-art methods.

cs.LG↗

arXiv2024

ElasTST: Towards Robust Varied-Horizon Forecasting with Elastic Time-Series Transformer

Numerous industrial sectors necessitate models capable of providing robust forecasts across various horizons. Despite the recent strides in crafting specific architectures for time-series forecasting and developing pre-trained universal models, a comprehensive examination of their capability in accommodating varied-horizon forecasting during inference is still lacking. This paper bridges this gap through the design and evaluation of the Elastic Time-Series Transformer (ElasTST). The ElasTST model incorporates a non-autoregressive design with placeholders and structured self-attention masks, warranting future outputs that are invariant to adjustments in inference horizons. A tunable version of rotary position embedding is also integrated into ElasTST to capture time-series-specific periods and enhance adaptability to different horizons. Additionally, ElasTST employs a multi-scale patch design, effectively integrating both fine-grained and coarse-grained information. During the training phase, ElasTST uses a horizon reweighting strategy that approximates the effect of random sampling across multiple horizons with a single fixed horizon setting. Through comprehensive experiments and comparisons with state-of-the-art time-series architectures and contemporary foundation models, we demonstrate the efficacy of ElasTST's unique design elements. Our findings position ElasTST as a robust solution for the practical necessity of varied-horizon forecasting.

cs.LG↗

arXiv2024

ProbTS: Benchmarking Point and Distributional Forecasting across Diverse Prediction Horizons

Delivering precise point and distributional forecasts across a spectrum of prediction horizons represents a significant and enduring challenge in the application of time-series forecasting within various industries. Prior research on developing deep learning models for time-series forecasting has often concentrated on isolated aspects, such as long-term point forecasting or short-term probabilistic estimations. This narrow focus may result in skewed methodological choices and hinder the adaptability of these models to uncharted scenarios. While there is a rising trend in developing universal forecasting models, a thorough understanding of their advantages and drawbacks, especially regarding essential forecasting needs like point and distributional forecasts across short and long horizons, is still lacking. In this paper, we present ProbTS, a benchmark tool designed as a unified platform to evaluate these fundamental forecasting needs and to conduct a rigorous comparative analysis of numerous cutting-edge studies from recent years. We dissect the distinctive data characteristics arising from disparate forecasting requirements and elucidate how these characteristics can skew methodological preferences in typical research trajectories, which often fail to fully accommodate essential forecasting needs. Building on this, we examine the latest models for universal time-series forecasting and discover that our analyses of methodological strengths and weaknesses are also applicable to these universal models. Finally, we outline the limitations inherent in current research and underscore several avenues for future exploration.

cs.LG↗

arXiv2024

Tracial states on groupoid $C^*$-algebras and essential freeness

Let $\mathcal{G}$ be a locally compact Hausdorff étale groupoid. We call a tracial state $τ$ on a general groupoid $C^*$-algebra $C_ν^*(\mathcal{G})$ canonical if $τ=τ|_{C_0(\mathcal{G}^{(0)})} \circ E$, where $E:C^*_ν(\mathcal{G}) \to C_0(\mathcal{G}^{(0)})$ is the canonical conditional expectation. In this paper, we consider so-called fixed point traces on $C_c(\mathcal{G})$, and prove that $\mathcal{G}$ is essentially free if and only if any tracial state on $C_ν^*(\mathcal{G})$ is canonical and any fixed point trace is extendable to $C_ν^*(\mathcal{G})$. As applications, we obtain the following: 1) a group action is essentially free if every tracial state on the reduced crossed product is canonical and every isotropy group is amenable; 2) if the groupoid $\mathcal{G}$ is second countable, amenable and essentially free then every (not necessarily faithful) tracial state on the reduced groupoid $C^*$-algebra is quasidiagonal.

math.OA↗

arXiv2024

Building weight-free Følner sets for Yu's Property A in coarse geometry

In this note we study the natural question of when the generalised Følner sets exhibiting property A can be chosen to be subsets of the space itself. We show that for many property A spaces $X$, this is indeed possible. Specifically this holds: for all discrete bounded geometry metric spaces which coarsely have all components unbounded; for all countable discrete groups; and for all box spaces.

math.MG↗