arXiv subjects

Liu Chang

Publications and source records attributed to Liu Chang.

8 recordsLinked to original sources

arXiv2026

Single-Chord Augmentation of Weighted Cycles for Algebraic Connectivity and Network Coherence

Ring-like communication graphs appear in UAV formations, cyclic patrols, perimeter monitoring, and other multi-agent tasks in which agents exchange information mainly with neighboring vehicles along a closed route. When measurement and actuation noise are persistent, a useful augmentation should improve both the convergence rate of consensus and the steady-state disagreement level. This paper studies the addition of a single weighted chord to a connected weighted cycle. The central observation is that a chord is not just a generic rank-one edge update: it splits the cycle into two complementary resistance arcs, and this resistance split governs both the algebraic-connectivity gain and the Kirchhoff-index reduction. We first derive exact chord-induced effective-resistance and Kirchhoff-index update formulas, giving a closed-form coherence objective. We then prove that, under bounded conductances and small resistance discrepancy, near-antipodal resistance-balanced chords are near-optimal for algebraic-connectivity improvement; an i.i.d. bounded-conductance model yields the same conclusion with high probability. Finally, because the best convergence-rate chord and the best coherence chord need not coincide, we formulate the design as a finite Pareto problem and introduce RBAPS and AW-RBAPS, two resistance-balanced screening rules that retain only linear or near-linear candidate sets. Numerical experiments show that AW-RBAPS remains effective beyond the formal moderate-heterogeneity regime and approximates the exhaustive Pareto front with mean hypervolume ratio $0.9987$ while evaluating about $10.1\%$ of admissible chords.

math.OC↗

arXiv2026

Thermal conductance across bonded SiOx-SiOx interfaces in hybrid bonding process

Hybrid bonding is a pivotal technology for enabling three dimensional integrated circuits. Among the foremost challenges facing 3D IC implementation is thermal management, where a deep understanding of heat conduction across bonded interfaces is essential for addressing heat dissipation and reliability issues. Nevertheless, the thermal conductance of bonded dielectric-dielectric interfaces remains poorly understood. In this study, we employ the low-temperature bonding technique integral to hybrid bonding to fabricate SiO-SiO interfaces and investigate their thermal boundary conductance using time domain thermoreflectance. Structural characterizations show high quality bonded interfaces. By fitting the data with an equivalent multilayer thermal model, we establish a lower limit TBC of 150 MW/m2-K for the SiO-SiO interfaces, which corresponds to a thermal resistance lower than that of a 9.2-nm-thick dielectric layer. These findings offer valuable insights into thermal transport in hybrid-bonded structures and provide critical guidance for the thermal design of advanced packaging solutions.

cond-mat.mes-hall↗

arXiv2025

Chung's LIL for the linear stochastic fractional heat equation at origin

Consider the linear stochastic fractional heat equation with vanishing initial condition: $$ \frac{\partial u (t,x)}{\partial t}=-(-\Delta)^{\frac{\alpha}2}u (t,x) + \dot{W}(t,x),\quad t> 0,\, x\in \mathbb R, $$ where $-(-\Delta)^{\frac{\alpha}{2}}$ denotes the fractional Laplacian with power $\alpha\in (1,2]$, and the driving noise $\dot W$ is a centered Gaussian field which is white in time and has the covariance of a fractional Brownian motion with Hurst parameter $H\in\left(\frac {2-\alpha}2,1\right)$. We establish Chung's law of the iterated logarithm for the solution at $t=0$.

math.PR↗

arXiv2025

Research on Graph-Retrieval Augmented Generation Based on Historical Text Knowledge Graphs

This article addresses domain knowledge gaps in general large language models for historical text analysis in the context of computational humanities and AIGC technology. We propose the Graph RAG framework, combining chain-of-thought prompting, self-instruction generation, and process supervision to create a The First Four Histories character relationship dataset with minimal manual annotation. This dataset supports automated historical knowledge extraction, reducing labor costs. In the graph-augmented generation phase, we introduce a collaborative mechanism between knowledge graphs and retrieval-augmented generation, improving the alignment of general models with historical knowledge. Experiments show that the domain-specific model Xunzi-Qwen1.5-14B, with Simplified Chinese input and chain-of-thought prompting, achieves optimal performance in relation extraction (F1 = 0.68). The DeepSeek model integrated with GraphRAG improves F1 by 11% (0.08-0.19) on the open-domain C-CLUE relation extraction dataset, surpassing the F1 value of Xunzi-Qwen1.5-14B (0.12), effectively alleviating hallucinations phenomenon, and improving interpretability. This framework offers a low-resource solution for classical text knowledge extraction, advancing historical knowledge services and humanities research.

cs.CL↗

arXiv2023

Dynamic Change of Amplitude for OCT Functional Imaging

Optical coherence tomography (OCT) is capable of non-destructively obtaining cross-sectional information of samples with micrometer spatial resolution, which plays an important role in ophthalmology and endovascular medicine. Measuring OCT amplitude can obtain three-dimensional structural information of the sample, such as the layered structure of the retina, but is of limited use for functional information such as tissue specificity, blood flow, and mechanical properties. OCT functional imaging techniques based on other optical field properties including phase, polarization state, and wavelength have emerged, such as Doppler OCT, optical coherence elastography, polarization-sensitive OCT, and visible-light OCT. Among them, functional imaging techniques based on dynamic changes of amplitude have significant robustness and complexity advantages, and achieved significant clinical success in label-free blood flow imaging. In addition, dynamic light scattering OCT for 3D blood flow velocity measurement, dynamic OCT with the ability to display label-free tissue/cell specificity, and OCT thermometry for monitoring the temperature field of thermophysical treatments are the frontiers in OCT functional imaging. In this paper, the principles and applications of the above technologies are summarized, the remaining technical challenges are analyzed, and the future development is envisioned.

physics.med-ph↗

arXiv2023

SikuGPT: A Generative Pre-trained Model for Intelligent Information Processing of Ancient Texts from the Perspective of Digital Humanities

The rapid advance in artificial intelligence technology has facilitated the prosperity of digital humanities research. Against such backdrop, research methods need to be transformed in the intelligent processing of ancient texts, which is a crucial component of digital humanities research, so as to adapt to new development trends in the wave of AIGC. In this study, we propose a GPT model called SikuGPT based on the corpus of Siku Quanshu. The model's performance in tasks such as intralingual translation and text classification exceeds that of other GPT-type models aimed at processing ancient texts. SikuGPT's ability to process traditional Chinese ancient texts can help promote the organization of ancient information and knowledge services, as well as the international dissemination of Chinese ancient culture.

cs.CL↗

arXiv2021

Systematic definition and classification of data anomalies in DBMS (English Version)

There is no unified definition of Data anomalies, which refers to the specific data operation mode that may violate the consistency of the database. Known data anomalies include Dirty Write, Dirty Read, Non-repeatable Read, Phantom, Read Skew and Write Skew, etc. In order to improve the efficiency of concurrency control algorithms, data anomalies are also used to define the isolation levels, because the weak isolation level can improve the efficiency of transaction processing systems. This paper systematically studies the data anomalies and the corresponding isolation levels. We report twenty-two new data anomalies that other papers have not reported, and all data anomalies are classified miraculously. Based on the classification of data anomalies, two new isolation levels systems with different granularity are proposed, which reveals the rule of defining isolation levels based on data anomalies and makes the cognition of data anomalies and isolation levels more concise.

cs.DB↗

arXiv2014

A brief introduction to giant magnetoresistance

Giant magnetoresistance (GMR) is a quantum mechanical magnetoresistance effect observed in thin film structures composed of alternating ferromagnetic and nonmagnetic layers. The effect manifests itself as a significant decrease (typically 10-80%) in electrical resistance in the presence of a magnetic field. The effect is exploited commercially by manufacturers of hard disk drives. The 2007 Nobel Prize in physics was awarded to Albert Fert and Peter Grunberg for the discovery of GMR.

cond-mat.mtrl-sci↗