arXiv subjects

Longfei Sun

Publications and source records attributed to Longfei Sun.

5 recordsLinked to original sources

arXiv2026

Enhancement of $J$$_c$ by Proton Irradiation in HgBa$_2$Ca$_2$Cu$_3$O$_8$$_+$$_\delta$ Single Crystals

Critical current density is the key parameter for the practical application of superconductivity. In this study, 3 MeV proton irradiation experiments were conducted on HgBa$_2$Ca$_2$Cu$_3$O$_8$$_+$$_\delta$ single crystals to introduce pinning centers. The critical current density is found to be strongly enhanced after the irradiation with its maximum at a dose of 1$\times$10$^{16}$/cm$^2$, where the self-field critical current density at 2 K is enhanced from 5.5 MA/cm$^2$ to 26 MA/cm$^2$. At 77 K, the self-field critical current density for all irradiated crystals is over 0.1 MA/cm$^2$. The power-law dependence of the critical current density on the magnetic field is observed after irradiation, with a large power-law exponent $\alpha$ close to 1. A monotonic magnetic field dependence of the normalized magnetic relaxation rate is observed, which could be attributed to the low irreversibility field caused by the large anisotropy in Hg1223 single crystals. Through the analysis of the pinning force density of the crystal before and after irradiation, a clear mechanism change has been observed.

cond-mat.supr-con↗

arXiv2026

Coding in a Bubble? Evaluating LLMs in Resolving Context Adaptation Bugs During Code Adaptation

Code adaptation is a fundamental but challenging task in software development, requiring developers to modify existing code for new contexts. A key challenge is to resolve Context Adaptation Bugs (CtxBugs), which occurs when code correct in its original context violates constraints in the target environment. Unlike isolated bugs, CtxBugs cannot be resolved through local fixes and require cross-context reasoning to identify semantic mismatches. Overlooking them may lead to critical failures in adaptation. Although Large Language Models (LLMs) show great potential in automating code-related tasks, their ability to resolve CtxBugs remains a significant and unexplored obstacle to their practical use in code adaptation. To bridge this gap, we propose CtxBugGen, a novel framework for generating CtxBugs to evaluate LLMs. Its core idea is to leverage LLMs' tendency to generate plausible but context-free code when contextual constraints are absent. The framework generates CtxBugs through a four-step process to ensure their relevance and validity: (1) Adaptation Task Selection, (2) Task-specific Perturbation,(3) LLM-based Variant Generation and (4) CtxBugs Identification. Based on the benchmark constructed by CtxBugGen, we conduct an empirical study with four state-of-the-art LLMs. Our results reveal their unsatisfactory performance in CtxBug resolution. The best performing LLM, Kimi-K2, achieves 55.93% on Pass@1 and resolves just 52.47% of CtxBugs. The presence of CtxBugs degrades LLMs' adaptation performance by up to 30%. Failure analysis indicates that LLMs often overlook CtxBugs and replicate them in their outputs. Our study highlights a critical weakness in LLMs' cross-context reasoning and emphasize the need for new methods to enhance their context awareness for reliable code adaptation.

cs.SE↗

arXiv2025

Increase of critical current density in FeSe superconductor by strain effect

Conventional $J_c$-enhancement methods like doping and irradiation often introduce extrinsic elements or defects, altering intrinsic properties. Here, we report a significant $J_c$ enhancement in FeSe single crystals through compressive strain applied using a glass-fiber-reinforced plastic substrate with anisotropic thermal contraction during cooling. Under zero field at 2 K, $J_{\text{c}}$ increases by a factor of $\sim$4 from $\sim 2.3 \times 10^{4}$ to $\sim 8.7 \times 10^{4}$ A cm$^{-2}$; at 5 T, it achieves an order-of-magnitude enhancement, rising from $\sim 1.0 \times 10^{3}$ to $\sim 1.0 \times 10^{4}$ A cm$^{-2}$. Analysis based on the Dew-Hughes model of the $f_{\text{p}}$(h) relationship shows that strain strengthens vortex pinning, and shifts the pinning mechanism from point-like pinning to combined point and surface pinnings. This work offers an effective method to enhance FeSe's current-carrying limitation, deepens understanding of iron-based superconductors' pinning mechanisms, and highlights strain engineering's potential for optimizing superconducting performance.

cond-mat.supr-con↗

arXiv2025

BDiff: Block-aware and Accurate Text-based Code Differencing

Code differencing is a fundamental technique in software engineering practice and research. While researchers have proposed text-based differencing techniques capable of identifying line changes over the past decade, existing methods exhibit a notable limitation in identifying edit actions (EAs) that operate on text blocks spanning multiple lines. Such EAs are common in developers' practice, such as moving a code block for conditional branching or duplicating a method definition block for overloading. Existing tools represent such block-level operations as discrete sequences of line-level EAs, compelling developers to manually correlate them and thereby substantially impeding the efficiency of change comprehension. To address this issue, we propose BDiff, a text-based differencing algorithm capable of identifying two types of block-level EAs and five types of line-level EAs. Building on traditional differencing algorithms, we first construct a candidate set containing all possible line mappings and block mappings. Leveraging the Kuhn-Munkres algorithm, we then compute the optimal mapping set that can minimize the size of the edit script (ES) while closely aligning with the original developer's intent. To validate the effectiveness of BDiff, we selected five state-of-the-art tools, including large language models (LLMs), as baselines and adopted a combined qualitative and quantitative approach to evaluate their performance in terms of ES size, result quality, and running time. Experimental results show that BDiff produces higher-quality differencing results than baseline tools while maintaining competitive runtime performance. Our experiments also show the unreliability of LLMs in code differencing tasks regarding result quality and their infeasibility in terms of runtime efficiency. We have implemented a web-based visual differencing tool.

cs.SE↗

arXiv2025

Effects of disorder on the quantum transport properties in topologically nontrivial metal PbTaSe$_{2}$

Weak antilocalization (WAL), an increase in the electrical conductivity at low temperatures associated with the suppression of electron localization due to quantum interference effects, is often observed in topological materials. In this study, we report the observation of WAL in topologically nontrivial metal PbTaSe$_{2}$ at low temperatures. In the pristine sample, we identified the presence of WAL, which is attributed to the topologically protected backscattering. In order to investigate the influence of disorder on the WAL, we successively introduced controlled amounts of disorder by H$^{+}$-irradiation. As disorder increases, the dip-like magnetoresistance caused by WAL changes to a linear magnetoresistance(MR), and eventually to a quadratic MR as the electronic system becomes highly localized. This research unveils the significance of disorder in shaping the quantum transport characteristics of topological materials.

cond-mat.mes-hall↗