arXiv subjects

Zhi Tan

Publications and source records attributed to Zhi Tan.

6 recordsLinked to original sources

arXiv2026

The origin of ferroelectricity, polarization and high resistivity in Aurivillius CaBi2B2O9 (B = Ta, Nb)

Aurivillius layered oxides are important candidates for high-temperature ferroelectric and piezoelectric application. In this work, we combine group theoretic analysis with first-principles calculations to systematically investigate the origin of ferroelectric phase transition, polarization, piezoelectric response, and intrinsic electrical insulation of the two-layer Aurivillius ferroelectrics CaBi$_{2}$B$_{2}$O$_{9}$ (B = Ta, Nb). The results show that the \textit{A2$_1$am} ferroelectric phase arises from the cooperative condensation of a polar mode and nonpolar oxygen octahedral rotation/tilting modes, whose the $\Gamma_5^-$X$_2^+$X$_3^-$ trilinear coupling substantially lowers the total energy and deepens the ferroelectric potential well. The spontaneous polarization and anisotropic piezoelectric response are governed primarily by the cooperative displacements of the Bi$_{2}$O$_{2}$ layers and Ta/NbO$_{6}$ octahedra, with Bi ions providing an indispensable contribution to both responses. More importantly, the polar distortion can be traced to the relative in-plane displacement between adjacent the Bi$_{2}$O$_{2}$ layer and the perovskite-like block. Because this displacement is intrinsic to the alternating Bi$_{2}$O$_{2}$/perovskite-block stacking topology and is independent of the number of perovskite layers, we identify interlayer sliding as a general, layer-number-independent structural mechanism for ferroelectricity in Aurivillius oxides. Our findings establish a unified microscopic picture linking structural distortions, ferroelectric polarization, piezoelectric response, and electronic insulation in CaBi$_{2}$B$_{2}$O$_{9}$ (B = Ta, Nb), and provide theoretical guidance for designing layered ferroelectric oxides with high Curie temperatures and robust insulating behavior.

cond-mat.mtrl-sci↗

arXiv2026

Learning Taxonomic Trees with Hierarchical Representation Regularization for Large Multimodal Models

Taxonomies provide key information about the semantic relationships between concepts and the inherent organization of vision and language. Despite their impressive capabilities, large multimodal models (LMMs) often lack taxonomic knowledge, leading to low hierarchical visual recognition (HVR) consistency. These models typically only rely on language modeling objectives during fine-tuning and lack explicit taxonomy-aware regularization. To address this, we propose Hierarchical Representation Regularization ($HiR^2$), a simple plug-and-play regularizer that improves hierarchical consistency in LMMs. Specifically, we introduce a semantic-aware visual tree construction framework that extracts coarse-to-fine visual features from intermediate LLM layers guided by textual cues. The regularizer combines two complementary objectives: a taxonomic entailment loss that enforces hierarchy via hyperbolic entailment cones in the Lorentz model, and a discriminative dispersive loss that promotes angular separation of semantically similar embeddings on the unit sphere without disturbing the radial hierarchical structure. Extensive experiments demonstrate that $HiR^2$ effectively captures taxonomic structures across diverse LMMs and fine-tuning methods. Code is available at https://github.com/PKU-ICST-MIPL/HiR2_ICML2026.

cs.CV↗

arXiv2026

Taxonomy-Aware Representation Alignment for Hierarchical Visual Recognition with Large Multimodal Models

A high-performing, general-purpose visual understanding model should map visual inputs to a taxonomic tree of labels, identify novel categories beyond the training set for which few or no publicly available images exist. Large Multimodal Models (LMMs) have achieved remarkable progress in fine-grained visual recognition (FGVR) for known categories. However, they remain limited in hierarchical visual recognition (HVR) that aims at predicting consistent label paths from coarse to fine categories, especially for novel categories. To tackle these challenges, we propose Taxonomy-Aware Representation Alignment (TARA), a simple yet effective strategy to inject taxonomic knowledge into LMMs. TARA leverages representations from biology foundation models (BFMs) that encode rich biological relationships through hierarchical contrastive learning. By aligning the intermediate representations of visual features with those of BFMs, LMMs are encouraged to extract discriminative visual cues well structured in the taxonomy tree. Additionally, we align the representations of the first answer token with the ground-truth label, flexibly bridging the gap between contextualized visual features and categories of varying granularity according to user intent. Experiments demonstrate that TARA consistently enhances LMMs' hierarchical consistency and leaf node accuracy, enabling reliable recognition of both known and novel categories within complex biological taxonomies. Code is available at https://github.com/PKU-ICST-MIPL/TARA_CVPR2026.

cs.CV↗

arXiv2025

Strongly tilted field induced fractional quantized-drift in non-interacting system

Fractional quantized response appears to be a distinctive characteristic in interacting topological systems. Here, we discover a novel phenomenon of tilt-induced fractional quantize drift in non-interacting system constructed by a time-modulated superlattice subjected to a external time-independent gradient potential. Depending on the tilt strength, Rabi oscillations between adjacent lowest enegy bands caused by Landau-Zener tunneling, can induce that the one-cycle-averaged drift displacement is fraction, which is relate to the ratio of the sum of Chern numbers of multiple bands to the number of energy bands involved in Landau Zener tunneling. As representative examples, we construct fractional (1/3, 1/2) quantize drift only via adjusting period of lattice. The numerical simulations allow us to consider a realistic setup amenable of an experimental realization. Our findings will expand the research implications of both fractional quantize response and topological materials.

cond-mat.quant-gas↗

arXiv2025

Adaptive cold-atom magnetometry mitigating the trade-off between sensitivity and dynamic range

Cold-atom magnetometers can achieve an exceptional combination of superior sensitivity and high spatial resolution. One key challenge these quantum sensors face is improving the sensitivity within a given timeframe while preserving a high dynamic range. Here, we experimentally demonstrate an adaptive entanglement-free cold-atom magnetometry with both superior sensitivity and high dynamic range. Employing a tailored adaptive Bayesian quantum estimation algorithm designed for Ramsey interferometry using coherent population trapping (CPT), cold-atom magnetometry facilitates adaptive high-precision detection of a direct-current (d.c.) magnetic field with high dynamic range. Through implementing a sequence of correlated CPT-Ramsey interferometry, the sensitivity significantly surpasses the standard quantum limit with respect to total interrogation time. We yield a sensitivity of 6.8$\pm$0.1 picotesla per square root of hertz over a range of 145.6 nanotesla, exceeding the conventional frequentist protocol by 3.3$\pm$0.1 decibels. Our study opens avenues for the next generation of adaptive cold-atom quantum sensors, wherein real-time measurement history is leveraged to improve their performance.

quant-ph↗

arXiv2024

Transverse Bending Mimicry of Longitudinal Piezoelectricity

The origin of frequently observed ultrahigh electric-induced longitudinal strain, ranging from 1% to 26%, remains an open question. Recent evidence suggests that this phenomenon is linked to the bending deformation of samples, but the mechanisms driving this bending and the strong dependence of nominal strain on sample thickness have yet to be fully understood. Here, we demonstrate that the bending in piezoceramics can be induced by non-zero gradient of d31 acrcoss thickness direction. Our calculations show that in standard perovskite piezoceramics, such as KNbO3, a 0.69% concentration of oxygen vacancies results in a 6.3 pC/N change in d31 by inhibiting polarization rotation, which is sufficient to produce ultrahigh nominal strain in thin samples. The gradients of defect concentration, composition, and stress can all cause sufficient inhomogeneity in the distribution of d31, leading to the bending effect. We propose several approaches to distinguish true electric-induced strain from bending-induced effects. Our work provides clarity on the origin of nominal ultrahigh electricinduced strain and offers valuable insights for advancing piezoelectric materials.

cond-mat.mtrl-sci↗