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Qiyun Xu

Publications and source records attributed to Qiyun Xu.

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Saturated and Anisotropic Magnetostriction in an Altermagnet

Magnetostriction, a fundamental phenomenon bridging magnetism and mechanics, has enabled a broad spectrum of applications. For almost two centuries, it has been mainly investigated for ferromagnets. Regarding the magnetostriction of antiferromagnets (AFMs), limitedly known examples for both conventional collinear AFMs and noncollinear AFMs predominantly exhibit non-saturating magnetic-field dependence. Herein, we report an easily saturated magnetostriction effect in a prototypical altermagnet - MnTe, which is an emerging class of collinear AFMs with special crystal symmetries. For high-quality MnTe single crystals, the magnetostriction saturates under a moderate field of ~0.7 T with an intriguing two-fold-symmetry anisotropy. First-principles calculations reveal that the saturated and anisotropic magnetostriction originates from symmetry-allowed coupling between elastic strain and its N\'eel order parameter. These findings break the traditional wisdom on antiferromagnetic magnetostriction.

cond-mat.mtrl-sci

Moiré-modulated $Γ$ valley in twisted bilayer and twisted double-bilayer MoTe$_2$

Twisted MoTe$_2$ hosts intriguing correlated quantum phenomena including the fractional quantum anomalous Hall effect in twisted bilayer (t-BL) MoTe$_2$ near 3.7$^\circ$, which is sensitive to the twist angle and moiré superlattices. Here, we directly visualize the twist-angle-modulated electronic structure of t-BL and twisted double-bilayer (t-DBL) near this critical angle. We find that the moiré superlattice not only modifies the relative energy between $Γ$ and K valleys in t-BL MoTe$_2$, but also strongly reconstructs the $Γ$ valley for both t-BL and t-DBL. Specifically, the deep $p_z$-derived band at $Γ$ exhibits a distinct splitting that systematically varies with increasing twist angle. Theoretical analysis suggests that this modulation arises from the twist-angle-dependent lattice relaxation, especially interfacial corrugations. Our work directly visualizes the moiré-modulated electronic structure and provides key spectroscopic information of lattice relaxation and interlayer interactions underlying the physics of twisted MoTe$_2$.

cond-mat.str-el

UGPhysics: A Comprehensive Benchmark for Undergraduate Physics Reasoning with Large Language Models

Large language models (LLMs) have demonstrated remarkable capabilities in solving complex reasoning tasks, particularly in mathematics. However, the domain of physics reasoning presents unique challenges that have received significantly less attention. Existing benchmarks often fall short in evaluating LLMs' abilities on the breadth and depth of undergraduate-level physics, underscoring the need for a comprehensive evaluation. To fill this gap, we introduce UGPhysics, a large-scale and comprehensive benchmark specifically designed to evaluate UnderGraduate-level Physics (UGPhysics) reasoning with LLMs. UGPhysics includes 5,520 undergraduate-level physics problems in both English and Chinese, covering 13 subjects with seven different answer types and four distinct physics reasoning skills, all rigorously screened for data leakage. Additionally, we develop a Model-Assistant Rule-based Judgment (MARJ) pipeline specifically tailored for assessing answer correctness of physics problems, ensuring accurate evaluation. Our evaluation of 31 leading LLMs shows that the highest overall accuracy, 49.8% (achieved by OpenAI-o1-mini), emphasizes the necessity for models with stronger physics reasoning skills, beyond math abilities. We hope UGPhysics, along with MARJ, will drive future advancements in AI for physics reasoning. Codes and data are available at https://github.com/YangLabHKUST/UGPhysics .

cs.CL