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Isomorphisms of the 4-valent generalized Cayley graphs of Z3p Z3p的四价广义Cayley图的同构
IF 3.4 2区 数学 Q1 MATHEMATICS, APPLIED Pub Date : 2026-06-15 Epub Date: 2026-01-02 DOI: 10.1016/j.amc.2025.129931
Qianfen Liao , Yangming Li , Weijun Liu
<div><div>For an odd prime <em>p</em> ≠ 3, the cyclic group <em>Z</em><sub>3<em>p</em></sub>≅<em>Z</em><sub>3</sub> × <em>Z<sub>p</sub></em>, where <span><math><mrow><msub><mi>Z</mi><mn>3</mn></msub><mo>=</mo><mrow><mo>〈</mo><msub><mi>w</mi><mn>1</mn></msub><mo>〉</mo></mrow></mrow></math></span> and <span><math><mrow><msub><mi>Z</mi><mi>p</mi></msub><mo>=</mo><mrow><mo>〈</mo><msub><mi>w</mi><mn>2</mn></msub><mo>〉</mo></mrow></mrow></math></span>. Let <em>β</em><sub>1</sub> and <em>β</em><sub>2</sub> be involutory automorphisms of <em>Z</em><sub>3<em>p</em></sub> defined by <span><math><mrow><msup><mrow><mo>(</mo><msub><mi>w</mi><mn>1</mn></msub><mo>,</mo><msub><mi>w</mi><mn>2</mn></msub><mo>)</mo></mrow><msub><mi>β</mi><mn>1</mn></msub></msup><mo>=</mo><mrow><mo>(</mo><msubsup><mi>w</mi><mn>1</mn><mrow><mo>−</mo><mn>1</mn></mrow></msubsup><mo>,</mo><msub><mi>w</mi><mn>2</mn></msub><mo>)</mo></mrow></mrow></math></span> and <span><math><mrow><msup><mrow><mo>(</mo><msub><mi>w</mi><mn>1</mn></msub><mo>,</mo><msub><mi>w</mi><mn>2</mn></msub><mo>)</mo></mrow><msub><mi>β</mi><mn>2</mn></msub></msup><mo>=</mo><mrow><mo>(</mo><msub><mi>w</mi><mn>1</mn></msub><mo>,</mo><msubsup><mi>w</mi><mn>2</mn><mrow><mo>−</mo><mn>1</mn></mrow></msubsup><mo>)</mo></mrow></mrow></math></span>. Then the elements of sets <span><math><mrow><msub><mstyle><mi>Δ</mi></mstyle><mn>1</mn></msub><mo>=</mo><mrow><mo>{</mo><mrow><mo>{</mo><mrow><mo>(</mo><msub><mi>s</mi><mn>1</mn></msub><mo>,</mo><msub><mi>s</mi><mn>2</mn></msub><mo>)</mo></mrow><mo>,</mo><mrow><mo>(</mo><msub><mi>s</mi><mn>1</mn></msub><mo>,</mo><msubsup><mi>s</mi><mn>2</mn><mrow><mo>−</mo><mn>1</mn></mrow></msubsup><mo>)</mo></mrow><mo>,</mo><mrow><mo>(</mo><msub><mi>s</mi><mn>1</mn></msub><mo>,</mo><msub><mi>s</mi><mn>3</mn></msub><mo>)</mo></mrow><mo>,</mo><mrow><mo>(</mo><msub><mi>s</mi><mn>1</mn></msub><mo>,</mo><msubsup><mi>s</mi><mn>3</mn><mrow><mo>−</mo><mn>1</mn></mrow></msubsup><mo>)</mo></mrow><mo>}</mo></mrow><mo>∣</mo><msub><mi>s</mi><mn>1</mn></msub><mo>∈</mo><msub><mi>Z</mi><mn>3</mn></msub><mo>,</mo><msub><mi>s</mi><mn>2</mn></msub><mo>≠</mo><msub><mi>s</mi><mn>3</mn></msub><mspace></mspace><mtext>and</mtext><mspace></mspace><msub><mi>s</mi><mn>2</mn></msub><mo>,</mo><msub><mi>s</mi><mn>3</mn></msub><mo>≠</mo><msub><mi>e</mi><mn>2</mn></msub><mo>}</mo></mrow></mrow></math></span> and <span><math><mrow><msub><mstyle><mi>Δ</mi></mstyle><mn>2</mn></msub><mo>=</mo><mrow><mo>{</mo><mrow><mo>{</mo><mrow><mo>(</mo><msub><mi>w</mi><mn>1</mn></msub><mo>,</mo><msub><mi>t</mi><mn>1</mn></msub><mo>)</mo></mrow><mo>,</mo><mrow><mo>(</mo><msubsup><mi>w</mi><mn>1</mn><mrow><mo>−</mo><mn>1</mn></mrow></msubsup><mo>,</mo><msub><mi>t</mi><mn>1</mn></msub><mo>)</mo></mrow><mo>,</mo><mrow><mo>(</mo><msub><mi>w</mi><mn>1</mn></msub><mo>,</mo><msub><mi>t</mi><mn>2</mn></msub><mo>)</mo></mrow><mo>,</mo><mrow><mo>(</mo><msubsup><mi>w</mi><mn>1</mn><mrow><mo>−</mo><mn>1</mn></mrow></msubsup><mo>,</mo><msub><mi>t</mi><mn>2<
对于奇素数p ≠ 3,得到循环群Z3p = Z3 × Zp,其中Z3= < w1 >, Zp= < w2 >。设β1和β2为Z3p的对折自同构,定义为(w1,w2)β1=(w1−1,w2)和(w1,w2)β2=(w1,w2−1)。则集合的元素Δ1={{(s1,s2),(s1,s2−1),(s1,s3),(s1,s3−1)}∣s1∈Z3,s2≠s3ands2,s3≠e2}和Δ2={{(w1,t1),(w1 - 1,t1),(w1,t2),(w1 - 1,t2)}∣t1,t2∈Zpandt1≠t2}分别构成Z3p关于β1和β2的广义Cayley子集。本文证明了对于i=1和2,当S, T ∈ Δi,则GC(Z3p, S, βi)和GC(Z3p, T, βi)是同态的当且仅当它们是广义Cayley同态。
{"title":"Isomorphisms of the 4-valent generalized Cayley graphs of Z3p","authors":"Qianfen Liao ,&nbsp;Yangming Li ,&nbsp;Weijun Liu","doi":"10.1016/j.amc.2025.129931","DOIUrl":"10.1016/j.amc.2025.129931","url":null,"abstract":"&lt;div&gt;&lt;div&gt;For an odd prime &lt;em&gt;p&lt;/em&gt; ≠ 3, the cyclic group &lt;em&gt;Z&lt;/em&gt;&lt;sub&gt;3&lt;em&gt;p&lt;/em&gt;&lt;/sub&gt;≅&lt;em&gt;Z&lt;/em&gt;&lt;sub&gt;3&lt;/sub&gt; × &lt;em&gt;Z&lt;sub&gt;p&lt;/sub&gt;&lt;/em&gt;, where &lt;span&gt;&lt;math&gt;&lt;mrow&gt;&lt;msub&gt;&lt;mi&gt;Z&lt;/mi&gt;&lt;mn&gt;3&lt;/mn&gt;&lt;/msub&gt;&lt;mo&gt;=&lt;/mo&gt;&lt;mrow&gt;&lt;mo&gt;〈&lt;/mo&gt;&lt;msub&gt;&lt;mi&gt;w&lt;/mi&gt;&lt;mn&gt;1&lt;/mn&gt;&lt;/msub&gt;&lt;mo&gt;〉&lt;/mo&gt;&lt;/mrow&gt;&lt;/mrow&gt;&lt;/math&gt;&lt;/span&gt; and &lt;span&gt;&lt;math&gt;&lt;mrow&gt;&lt;msub&gt;&lt;mi&gt;Z&lt;/mi&gt;&lt;mi&gt;p&lt;/mi&gt;&lt;/msub&gt;&lt;mo&gt;=&lt;/mo&gt;&lt;mrow&gt;&lt;mo&gt;〈&lt;/mo&gt;&lt;msub&gt;&lt;mi&gt;w&lt;/mi&gt;&lt;mn&gt;2&lt;/mn&gt;&lt;/msub&gt;&lt;mo&gt;〉&lt;/mo&gt;&lt;/mrow&gt;&lt;/mrow&gt;&lt;/math&gt;&lt;/span&gt;. Let &lt;em&gt;β&lt;/em&gt;&lt;sub&gt;1&lt;/sub&gt; and &lt;em&gt;β&lt;/em&gt;&lt;sub&gt;2&lt;/sub&gt; be involutory automorphisms of &lt;em&gt;Z&lt;/em&gt;&lt;sub&gt;3&lt;em&gt;p&lt;/em&gt;&lt;/sub&gt; defined by &lt;span&gt;&lt;math&gt;&lt;mrow&gt;&lt;msup&gt;&lt;mrow&gt;&lt;mo&gt;(&lt;/mo&gt;&lt;msub&gt;&lt;mi&gt;w&lt;/mi&gt;&lt;mn&gt;1&lt;/mn&gt;&lt;/msub&gt;&lt;mo&gt;,&lt;/mo&gt;&lt;msub&gt;&lt;mi&gt;w&lt;/mi&gt;&lt;mn&gt;2&lt;/mn&gt;&lt;/msub&gt;&lt;mo&gt;)&lt;/mo&gt;&lt;/mrow&gt;&lt;msub&gt;&lt;mi&gt;β&lt;/mi&gt;&lt;mn&gt;1&lt;/mn&gt;&lt;/msub&gt;&lt;/msup&gt;&lt;mo&gt;=&lt;/mo&gt;&lt;mrow&gt;&lt;mo&gt;(&lt;/mo&gt;&lt;msubsup&gt;&lt;mi&gt;w&lt;/mi&gt;&lt;mn&gt;1&lt;/mn&gt;&lt;mrow&gt;&lt;mo&gt;−&lt;/mo&gt;&lt;mn&gt;1&lt;/mn&gt;&lt;/mrow&gt;&lt;/msubsup&gt;&lt;mo&gt;,&lt;/mo&gt;&lt;msub&gt;&lt;mi&gt;w&lt;/mi&gt;&lt;mn&gt;2&lt;/mn&gt;&lt;/msub&gt;&lt;mo&gt;)&lt;/mo&gt;&lt;/mrow&gt;&lt;/mrow&gt;&lt;/math&gt;&lt;/span&gt; and &lt;span&gt;&lt;math&gt;&lt;mrow&gt;&lt;msup&gt;&lt;mrow&gt;&lt;mo&gt;(&lt;/mo&gt;&lt;msub&gt;&lt;mi&gt;w&lt;/mi&gt;&lt;mn&gt;1&lt;/mn&gt;&lt;/msub&gt;&lt;mo&gt;,&lt;/mo&gt;&lt;msub&gt;&lt;mi&gt;w&lt;/mi&gt;&lt;mn&gt;2&lt;/mn&gt;&lt;/msub&gt;&lt;mo&gt;)&lt;/mo&gt;&lt;/mrow&gt;&lt;msub&gt;&lt;mi&gt;β&lt;/mi&gt;&lt;mn&gt;2&lt;/mn&gt;&lt;/msub&gt;&lt;/msup&gt;&lt;mo&gt;=&lt;/mo&gt;&lt;mrow&gt;&lt;mo&gt;(&lt;/mo&gt;&lt;msub&gt;&lt;mi&gt;w&lt;/mi&gt;&lt;mn&gt;1&lt;/mn&gt;&lt;/msub&gt;&lt;mo&gt;,&lt;/mo&gt;&lt;msubsup&gt;&lt;mi&gt;w&lt;/mi&gt;&lt;mn&gt;2&lt;/mn&gt;&lt;mrow&gt;&lt;mo&gt;−&lt;/mo&gt;&lt;mn&gt;1&lt;/mn&gt;&lt;/mrow&gt;&lt;/msubsup&gt;&lt;mo&gt;)&lt;/mo&gt;&lt;/mrow&gt;&lt;/mrow&gt;&lt;/math&gt;&lt;/span&gt;. Then the elements of sets &lt;span&gt;&lt;math&gt;&lt;mrow&gt;&lt;msub&gt;&lt;mstyle&gt;&lt;mi&gt;Δ&lt;/mi&gt;&lt;/mstyle&gt;&lt;mn&gt;1&lt;/mn&gt;&lt;/msub&gt;&lt;mo&gt;=&lt;/mo&gt;&lt;mrow&gt;&lt;mo&gt;{&lt;/mo&gt;&lt;mrow&gt;&lt;mo&gt;{&lt;/mo&gt;&lt;mrow&gt;&lt;mo&gt;(&lt;/mo&gt;&lt;msub&gt;&lt;mi&gt;s&lt;/mi&gt;&lt;mn&gt;1&lt;/mn&gt;&lt;/msub&gt;&lt;mo&gt;,&lt;/mo&gt;&lt;msub&gt;&lt;mi&gt;s&lt;/mi&gt;&lt;mn&gt;2&lt;/mn&gt;&lt;/msub&gt;&lt;mo&gt;)&lt;/mo&gt;&lt;/mrow&gt;&lt;mo&gt;,&lt;/mo&gt;&lt;mrow&gt;&lt;mo&gt;(&lt;/mo&gt;&lt;msub&gt;&lt;mi&gt;s&lt;/mi&gt;&lt;mn&gt;1&lt;/mn&gt;&lt;/msub&gt;&lt;mo&gt;,&lt;/mo&gt;&lt;msubsup&gt;&lt;mi&gt;s&lt;/mi&gt;&lt;mn&gt;2&lt;/mn&gt;&lt;mrow&gt;&lt;mo&gt;−&lt;/mo&gt;&lt;mn&gt;1&lt;/mn&gt;&lt;/mrow&gt;&lt;/msubsup&gt;&lt;mo&gt;)&lt;/mo&gt;&lt;/mrow&gt;&lt;mo&gt;,&lt;/mo&gt;&lt;mrow&gt;&lt;mo&gt;(&lt;/mo&gt;&lt;msub&gt;&lt;mi&gt;s&lt;/mi&gt;&lt;mn&gt;1&lt;/mn&gt;&lt;/msub&gt;&lt;mo&gt;,&lt;/mo&gt;&lt;msub&gt;&lt;mi&gt;s&lt;/mi&gt;&lt;mn&gt;3&lt;/mn&gt;&lt;/msub&gt;&lt;mo&gt;)&lt;/mo&gt;&lt;/mrow&gt;&lt;mo&gt;,&lt;/mo&gt;&lt;mrow&gt;&lt;mo&gt;(&lt;/mo&gt;&lt;msub&gt;&lt;mi&gt;s&lt;/mi&gt;&lt;mn&gt;1&lt;/mn&gt;&lt;/msub&gt;&lt;mo&gt;,&lt;/mo&gt;&lt;msubsup&gt;&lt;mi&gt;s&lt;/mi&gt;&lt;mn&gt;3&lt;/mn&gt;&lt;mrow&gt;&lt;mo&gt;−&lt;/mo&gt;&lt;mn&gt;1&lt;/mn&gt;&lt;/mrow&gt;&lt;/msubsup&gt;&lt;mo&gt;)&lt;/mo&gt;&lt;/mrow&gt;&lt;mo&gt;}&lt;/mo&gt;&lt;/mrow&gt;&lt;mo&gt;∣&lt;/mo&gt;&lt;msub&gt;&lt;mi&gt;s&lt;/mi&gt;&lt;mn&gt;1&lt;/mn&gt;&lt;/msub&gt;&lt;mo&gt;∈&lt;/mo&gt;&lt;msub&gt;&lt;mi&gt;Z&lt;/mi&gt;&lt;mn&gt;3&lt;/mn&gt;&lt;/msub&gt;&lt;mo&gt;,&lt;/mo&gt;&lt;msub&gt;&lt;mi&gt;s&lt;/mi&gt;&lt;mn&gt;2&lt;/mn&gt;&lt;/msub&gt;&lt;mo&gt;≠&lt;/mo&gt;&lt;msub&gt;&lt;mi&gt;s&lt;/mi&gt;&lt;mn&gt;3&lt;/mn&gt;&lt;/msub&gt;&lt;mspace&gt;&lt;/mspace&gt;&lt;mtext&gt;and&lt;/mtext&gt;&lt;mspace&gt;&lt;/mspace&gt;&lt;msub&gt;&lt;mi&gt;s&lt;/mi&gt;&lt;mn&gt;2&lt;/mn&gt;&lt;/msub&gt;&lt;mo&gt;,&lt;/mo&gt;&lt;msub&gt;&lt;mi&gt;s&lt;/mi&gt;&lt;mn&gt;3&lt;/mn&gt;&lt;/msub&gt;&lt;mo&gt;≠&lt;/mo&gt;&lt;msub&gt;&lt;mi&gt;e&lt;/mi&gt;&lt;mn&gt;2&lt;/mn&gt;&lt;/msub&gt;&lt;mo&gt;}&lt;/mo&gt;&lt;/mrow&gt;&lt;/mrow&gt;&lt;/math&gt;&lt;/span&gt; and &lt;span&gt;&lt;math&gt;&lt;mrow&gt;&lt;msub&gt;&lt;mstyle&gt;&lt;mi&gt;Δ&lt;/mi&gt;&lt;/mstyle&gt;&lt;mn&gt;2&lt;/mn&gt;&lt;/msub&gt;&lt;mo&gt;=&lt;/mo&gt;&lt;mrow&gt;&lt;mo&gt;{&lt;/mo&gt;&lt;mrow&gt;&lt;mo&gt;{&lt;/mo&gt;&lt;mrow&gt;&lt;mo&gt;(&lt;/mo&gt;&lt;msub&gt;&lt;mi&gt;w&lt;/mi&gt;&lt;mn&gt;1&lt;/mn&gt;&lt;/msub&gt;&lt;mo&gt;,&lt;/mo&gt;&lt;msub&gt;&lt;mi&gt;t&lt;/mi&gt;&lt;mn&gt;1&lt;/mn&gt;&lt;/msub&gt;&lt;mo&gt;)&lt;/mo&gt;&lt;/mrow&gt;&lt;mo&gt;,&lt;/mo&gt;&lt;mrow&gt;&lt;mo&gt;(&lt;/mo&gt;&lt;msubsup&gt;&lt;mi&gt;w&lt;/mi&gt;&lt;mn&gt;1&lt;/mn&gt;&lt;mrow&gt;&lt;mo&gt;−&lt;/mo&gt;&lt;mn&gt;1&lt;/mn&gt;&lt;/mrow&gt;&lt;/msubsup&gt;&lt;mo&gt;,&lt;/mo&gt;&lt;msub&gt;&lt;mi&gt;t&lt;/mi&gt;&lt;mn&gt;1&lt;/mn&gt;&lt;/msub&gt;&lt;mo&gt;)&lt;/mo&gt;&lt;/mrow&gt;&lt;mo&gt;,&lt;/mo&gt;&lt;mrow&gt;&lt;mo&gt;(&lt;/mo&gt;&lt;msub&gt;&lt;mi&gt;w&lt;/mi&gt;&lt;mn&gt;1&lt;/mn&gt;&lt;/msub&gt;&lt;mo&gt;,&lt;/mo&gt;&lt;msub&gt;&lt;mi&gt;t&lt;/mi&gt;&lt;mn&gt;2&lt;/mn&gt;&lt;/msub&gt;&lt;mo&gt;)&lt;/mo&gt;&lt;/mrow&gt;&lt;mo&gt;,&lt;/mo&gt;&lt;mrow&gt;&lt;mo&gt;(&lt;/mo&gt;&lt;msubsup&gt;&lt;mi&gt;w&lt;/mi&gt;&lt;mn&gt;1&lt;/mn&gt;&lt;mrow&gt;&lt;mo&gt;−&lt;/mo&gt;&lt;mn&gt;1&lt;/mn&gt;&lt;/mrow&gt;&lt;/msubsup&gt;&lt;mo&gt;,&lt;/mo&gt;&lt;msub&gt;&lt;mi&gt;t&lt;/mi&gt;&lt;mn&gt;2&lt;","PeriodicalId":55496,"journal":{"name":"Applied Mathematics and Computation","volume":"519 ","pages":"Article 129931"},"PeriodicalIF":3.4,"publicationDate":"2026-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145886438","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Maximum augmented Zagreb index on polyomino chains 多链上的最大增广Zagreb指数
IF 3.4 2区 数学 Q1 MATHEMATICS, APPLIED Pub Date : 2026-06-15 Epub Date: 2026-01-03 DOI: 10.1016/j.amc.2025.129929
Manuel Montes-y-Morales, Saylé Sigarreta, Hugo Cruz-Suárez
In this paper, we present a dynamic programming approach for identifying extremal polyomino chains with respect to degree–based indices. This approach provides an explicit recurrence, and a constructive algorithm that enable both the computation of an extremal polyomino chain in linear time with respect to the number of squares, and the enumeration of all maximal configurations. As a main application, we focus on the problem posed in 2016 by characterizing the polyomino chains that maximize the Augmented Zagreb Index (AZI) for any fixed number of squares. The results presented in this paper are aligned with previous contributions, and establish a constructive methodology for solving extremal problems in chemical graph theory. A link to the implementation code is provided in the last section.
在本文中,我们提出了一种动态规划方法来识别基于度的指数的极值多聚链。这种方法提供了一种显式递归式和一种构造算法,该算法既可以计算线性时间内关于平方数的极值多项式链,又可以枚举所有最大构型。作为一个主要应用,我们专注于2016年提出的问题,通过表征对任意固定数量的平方最大化增广萨格勒布指数(AZI)的多聚链。本文提出的结果与以前的贡献一致,并为解决化学图论中的极值问题建立了建设性的方法。最后一节提供了实现代码的链接。
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引用次数: 0
A second-order unconditionally energy stable scheme for the Lifshitz-Petrich model integrated with observational data 结合观测资料的Lifshitz-Petrich模型的二阶无条件能量稳定格式
IF 3.4 2区 数学 Q1 MATHEMATICS, APPLIED Pub Date : 2026-06-01 Epub Date: 2025-12-27 DOI: 10.1016/j.amc.2025.129914
Xiaochuan Hu , Junseok Kim , Yibao Li
In this paper, we introduce a modified Lifshitz-Petrich model that incorporates a data assimilation term. This model is used to investigate the nucleation of quasicrystalline structures in polycrystalline materials by leveraging information from observational data. Guided by the principle of feedback control, the data assimilation term drives the solution toward the observational data sampled from the reference process. Using the second-order backward differentiation formula and the scalar auxiliary variable method, we introduce an efficient numerical scheme for the modified Lifshitz-Petrich model. We employ the Fourier spectral method to achieve second-order accuracy and high computational efficiency. And we prove the numerical discrete energy is unconditionally stable. A series of numerical experiments are conducted to evaluate the efficiency and robustness of the proposed method.
在本文中,我们引入了一个包含数据同化项的改进Lifshitz-Petrich模型。该模型利用观测数据的信息来研究多晶材料中准晶结构的成核。在反馈控制原理的指导下,数据同化项将解推向从参考过程中采样的观测数据。利用二阶后向微分公式和标量辅助变量法,给出了修正Lifshitz-Petrich模型的有效数值格式。我们采用傅里叶谱方法来达到二阶精度和较高的计算效率。并证明了数值离散能量是无条件稳定的。通过一系列数值实验验证了该方法的有效性和鲁棒性。
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引用次数: 0
Impact of interaction diversity and interlayer coupling on the evolution of human-AI cooperation 交互多样性和层间耦合对人类-人工智能合作进化的影响
IF 3.4 2区 数学 Q1 MATHEMATICS, APPLIED Pub Date : 2026-06-01 Epub Date: 2025-12-29 DOI: 10.1016/j.amc.2025.129894
Bo Gao , Pengfei Zuo , Chengyi Xia , Tianyi Zhang , Suyalatu Dong , Chunyang Liu
In the context of a digitized society characterized by profound human-artificial intelligence (AI) interaction, the evolutionary dynamics of cooperative behavior confront novel challenges. This study develops a two-layer network evolutionary game model that couples a human decision-making layer with an AI system layer, aiming to investigate how bidirectional interlayer coupling mechanisms influence the emergence and sustainability of cooperation. We find that interlayer coupling facilitates the emergence and stabilization of cooperative behavior across both the AI and human layers. However, the efficacy of this facilitative effect is highly contingent upon the relative dependency configurations between two networks. When interaction diversity (link-strategy) is introduced within the AI layer, the system’s resilience to the temptation of defection is markedly enhanced, resulting in elevated levels of cooperation. Conversely, excessive interaction diversity within the human layer may, under certain conditions, undermine cooperative coordination, particularly in scenarios characterized by high interlayer dependency. Moreover, the AI layer exhibits substantial adaptive capacity, maintaining relatively stable behavioral patterns across varying human decision-making regimes, thereby enabling the emergence of a robust mixed equilibrium of cooperation and defection. This study proposes a computational model to explore the evolutionary dynamics of cooperation in human-AI collaborative environments, offering new insights into AI governance, multi-agent system design, and related domains.
在以人类与人工智能(AI)深度互动为特征的数字化社会背景下,合作行为的进化动力学面临着新的挑战。本研究建立了人类决策层与人工智能系统层耦合的两层网络进化博弈模型,旨在探讨双向层间耦合机制如何影响合作的产生和可持续性。我们发现,层间耦合促进了人工智能和人类层之间合作行为的出现和稳定。然而,这种促进效应的有效性在很大程度上取决于两个网络之间的相对依赖配置。当人工智能层引入交互多样性(链接策略)时,系统对背叛诱惑的抵御能力显著增强,从而提高了合作水平。相反,在某些条件下,人类层面内部过度的互动多样性可能会破坏合作协调,特别是在以高度层间依赖为特征的场景中。此外,人工智能层表现出大量的适应能力,在不同的人类决策机制中保持相对稳定的行为模式,从而使合作与背叛的强大混合均衡得以出现。本研究提出了一个计算模型来探索人类-人工智能协作环境中合作的进化动力学,为人工智能治理、多智能体系统设计和相关领域提供了新的见解。
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引用次数: 0
A posteriori-driven adaptive strategy for solving inverse Cauchy problems in diffusion-reaction models 扩散反应模型中求解逆柯西问题的后验驱动自适应策略
IF 3.4 2区 数学 Q1 MATHEMATICS, APPLIED Pub Date : 2026-06-01 Epub Date: 2025-12-24 DOI: 10.1016/j.amc.2025.129902
Hafida Hamdi , Mourad Nachaoui , Amal Bergam , Abdeljalil Nachaoui
This work addresses the inverse Cauchy problem for the modified Helmholtz equation using an alternating iterative approach. The central contribution lies in the design of novel local error indicators based on a posteriori analysis, which simultaneously assess the accuracy of the spatial discretization and the convergence behavior of the iterative algorithm. Unlike standard methods, our strategy leverages a comparative assessment of these indicators to drive an adaptive mesh refinement process. This adaptive framework ensures a more balanced distribution of computational resources, significantly reducing the numerical cost while maintaining high solution accuracy. The proposed methodology is validated through a series of synthetic and application-driven numerical experiments, demonstrating both its effectiveness and robustness in reconstructing inaccessible boundary data.
本文采用交替迭代的方法解决了修正亥姆霍兹方程的反柯西问题。其核心贡献在于基于后验分析设计了新的局部误差指标,同时评估了空间离散化的准确性和迭代算法的收敛性。与标准方法不同,我们的策略利用这些指标的比较评估来驱动自适应网格细化过程。这种自适应框架确保了计算资源的更均衡分布,在保持高解精度的同时显著降低了数值成本。通过一系列综合和应用驱动的数值实验,验证了该方法在重建不可达边界数据方面的有效性和鲁棒性。
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引用次数: 0
An alternating direction implicit method for 2D nonlinear Schrödinger equation with accelerated evaluation of Caputo derivative 二维非线性Schrödinger方程的交替方向隐式加速卡普托导数求值方法
IF 3.4 2区 数学 Q1 MATHEMATICS, APPLIED Pub Date : 2026-06-01 Epub Date: 2025-12-26 DOI: 10.1016/j.amc.2025.129905
Himanshu Kumar Dwivedi , Rajeev , Shengda Zeng
We propose an efficient time-space discretization for nonlinear fractional Schrödinger equations involving Caputo tempered derivatives. A new tempered Alikhanov scheme with parameter λ is introduced, together with a fast sum-of-exponentials (SOE) implementation, reducing complexity to O(MKtlogKt) and memory to O(MlogKt). Spatial derivatives are approximated using a compact scheme, and an alternating direction implicit formulation is derived with perturbation terms for stability. A graded time mesh resolves the initial singularity, while adaptive time-stepping ensures long-time efficiency. Stability and maximum-norm error bounds are established via a discrete Grönwall inequality. Numerical tests confirm the theoretical convergence and demonstrate substantial savings in CPU time and storage over classical methods. This work presents a novel nonuniform tempered Alikhanov time-stepping framework for nonlinear tempered fractional Schrödinger equation(NL-TFSEs), combining robustness, high accuracy, and computational scalability.
我们提出了一种有效的非线性分数阶Schrödinger方程的时间-空间离散化方法。引入了一种新的带λ参数的调质Alikhanov格式,以及快速的指数和(SOE)实现,将复杂度降低到O(MKtlogKt),内存降低到O(MlogKt)。利用紧格式对空间导数进行了近似,并导出了带有扰动项的交替方向隐式公式。渐变时间网格解决了初始奇异性,自适应时间步进保证了长时间效率。稳定性和最大范数误差边界是通过一个离散Grönwall不等式建立的。数值测试证实了理论的收敛性,并证明了与经典方法相比,在CPU时间和存储方面有很大的节省。本文提出了一种新的非均匀回火Alikhanov时间步进框架,用于非线性回火分数阶Schrödinger方程(NL-TFSEs),该框架结合了鲁棒性、高精度和计算可扩展性。
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引用次数: 0
Efficient diffusion for high order non-oscillatory entropy stable schemes 高阶非振荡熵稳定格式的有效扩散
IF 3.4 2区 数学 Q1 MATHEMATICS, APPLIED Pub Date : 2026-06-01 Epub Date: 2025-12-26 DOI: 10.1016/j.amc.2025.129901
Anuradha Sahu , Prashant Kumar Pandey , Ritesh Kumar Dubey
This paper proposes an efficient approach to construct non-oscillatory entropy stable fluxes (F^) by adding an efficient diffusion term to the entropy conservative fluxes. Computation of proposed diffusion term does not require restrictive and logically expensive sign stability condition on high order reconstruction process or flux sign stability on high order fluxes. The diffusion term is defined as the absolute difference of non-oscillatory (F˘) and entropy conservative fluxes (F˜) multiplied with sign of jump in entropy variable. The amount of diffusion is adjusted using a limiter function without compromising the entropy stability of the resulting scheme which exhibits both high resolution and the non-oscillatory property. The proposed approach is tested on various standard benchmark test problems. Numerical results demonstrate the effectiveness of the method in achieving high resolution entropy stable schemes, Moreover the scheme maintains formal order of accuracy of the lower order flux used in defining the diffusion term.
本文提出了一种构造非振荡熵稳定通量(F^)的有效方法,即在熵保守通量中加入有效扩散项。所提出的扩散项的计算不需要高阶重建过程的限制性和逻辑上昂贵的符号稳定性条件,也不需要高阶通量上的通量符号稳定性条件。扩散项定义为非振荡(F ×)和熵保守通量(F ×)的绝对差乘以熵变量的跳跃符号。扩散量使用限制函数进行调整,而不影响所得到的方案的熵稳定性,该方案具有高分辨率和非振荡性质。该方法在各种标准基准测试问题上进行了测试。数值结果证明了该方法在获得高分辨率熵稳定格式方面的有效性,并且该格式保持了用于定义扩散项的低阶通量的形式精度。
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引用次数: 0
Finite-time trajectory tracking of multi-agent systems via higher-order dynamic networks with channel damage 基于高阶动态网络的多智能体系统有限时间轨迹跟踪
IF 3.4 2区 数学 Q1 MATHEMATICS, APPLIED Pub Date : 2026-06-01 Epub Date: 2025-12-27 DOI: 10.1016/j.amc.2025.129918
Junfeng Mao , Lilan Tu , Xianjia Wang , Fujuan Gao , Qiuyue Zhao
For multi-agent trajectory tracking, strong communication channels between agents are crucial for group motion. In this paper, using undirected and directed higher-order complex networks described by second-order simplicial complexes, we investigated finite-time trajectory tracking of multi-agent systems when communication channels are damaged. By introducing the effective and damaged rates to the first-order and second-order channels of the multi-agent networks, and employing Lyapunov stability theory, and finite-time control techniques, we proposed several theoretical sufficient conditions that enable multiple agents in the response networks with damaged channels to track the trajectories of multiple agents in the drive networks within finite time. Extensive numerical simulations were conducted not only to verify the feasibility and effectiveness of the proposed theoretical results, but also to explore the effects of first-order channel, second-order channel, random damage, deliberate damage, one-time damage, and cascade damage on the finite-time tracking performance of multi-agent systems. We found that damage to first-order channels significantly impacts the tracking performance of multi-agent systems, while damage to second-order channels has a comparatively smaller impact. Deliberate damage is more detrimental to multi-agent systems than random damage. Random damage triggers significant phase fluctuations in tracking time. The directionality makes the network more vulnerable to channel damage.
在多智能体轨迹跟踪中,智能体之间的强通信通道对群体运动至关重要。本文利用二阶简单复数描述的无向和有向高阶复杂网络,研究了通信信道被破坏时多智能体系统的有限时间轨迹跟踪问题。通过引入多智能体网络的一阶和二阶通道的有效率和损坏率,利用Lyapunov稳定性理论和有限时间控制技术,提出了几个理论充分条件,使具有损坏通道的响应网络中的多个智能体能够在有限时间内跟踪驱动网络中多个智能体的轨迹。通过大量的数值模拟,不仅验证了所提理论结果的可行性和有效性,而且探讨了一阶通道、二阶通道、随机损伤、故意损伤、一次性损伤和级联损伤对多智能体系统有限时间跟踪性能的影响。我们发现,一阶通道的损坏显著影响多智能体系统的跟踪性能,而二阶通道的损坏影响相对较小。对多智能体系统来说,故意损害比随机损害更有害。随机损伤在跟踪时间中引起显著的相位波动。方向性使网络更容易受到信道损坏。
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引用次数: 0
On 2-distance integral Cayley graphs 关于2距离积分Cayley图
IF 3.4 2区 数学 Q1 MATHEMATICS, APPLIED Pub Date : 2026-05-15 Epub Date: 2025-12-10 DOI: 10.1016/j.amc.2025.129893
Xiaoqian Zhang, Weijun Liu, Lu Lu
The distance splitting field of distance matrix associated with a graph is the smallest field extension of Q that contains all of its distance eigenvalues. The extension degree is called its distance algebraic degree. A graph Γ is called k-distance integral if distance algebraic degree is equal to k. In this paper, we prove that the normal Cayley graph is distance algebraically integral over field K if and only if it is algebraically integral over K, and the Cayley graphs over cyclic groups is 2-distance integral if and only if it is 2-integral. Moreover, we construct k-distance integral Cayley graphs over cyclic groups, and classify the 2-distance integral abelian Cayley graphs with valency 2, 3, 4 and 5.
与图相关联的距离矩阵的距离分割域是包含其所有距离特征值的Q的最小域扩展。可拓度称为其距离代数度。当距离代数度等于k时,图Γ称为k距离积分。本文证明了正规Cayley图是k域上的距离代数积分当且仅当它是k域上的代数积分,证明了循环群上的Cayley图是2距离积分当且仅当它是2积分。此外,我们构造了循环群上的k距离积分Cayley图,并对2、3、4、5价的2距离积分abelian Cayley图进行了分类。
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引用次数: 0
Memory-based evolutionary prisoner’s dilemma game with neighbor screening mechanism 具有邻居筛选机制的基于记忆的进化囚徒困境博弈
IF 3.4 2区 数学 Q1 MATHEMATICS, APPLIED Pub Date : 2026-05-15 Epub Date: 2025-12-18 DOI: 10.1016/j.amc.2025.129903
Jinlong Ma , Guanghui Wang
Memory effects of individuals have been demonstrated to significantly promote cooperation, attracting widespread attention among scholars exploring the underlying dynamics of cooperative behavior. In this paper, we build a strategy updating framework by proposing a neighbor screening mechanism and combining particle swarm optimization algorithm in memory-based evolutionary prisoners’ dilemma game. Under the proposed mechanism, individuals may not imitate a neighbor with the only highest payoff from the current round when updating their strategy. Instead, individual evaluates the historical performance by his/her neighbors’ the frequency of choosing cooperation strategy and being chosen as an optimal neighbor and screen out the neighbors who do not meet the defined initial threshold. Moreover, a threshold adjustment parameter α is introduced to strengthen the flexible of the threshold. In addition, the proposed mechanism is compared in two situations: fixed memory and dynamic memory. Specifically, in the neighbor screening mechanism with dynamic memory, each individual’s memory will decay or remain unchanged according to the relationship between their current payoff and average payoff of all players in the local group. The simulation results reveal that the advantages of short memory length and dynamic memory in promoting cooperation. Furthermore, the synergistic effect between initial threshold and memory length better promotes cooperation. Additionally, a slight increase in the threshold adjustment parameter α promotes cooperation when the initial threshold is low. These findings shed light on how cooperation can be enhanced through specific rules.
个体的记忆效应已被证明对合作有显著的促进作用,这引起了研究合作行为潜在动力学的学者们的广泛关注。在基于记忆的进化囚徒困境博弈中,提出了一种邻居筛选机制,并结合粒子群优化算法构建了策略更新框架。在该机制下,个体在更新策略时可能不会模仿当前回合中唯一收益最高的邻居。个体通过其邻居选择合作策略的频率和被选为最优邻居的频率来评估其历史表现,并筛选出不符合定义的初始阈值的邻居。此外,引入阈值调整参数α,增强了阈值的灵活性。此外,本文还比较了固定记忆和动态记忆两种情况下所提出的机制。具体来说,在动态记忆的邻居筛选机制中,每个个体的记忆会根据其当前收益与本地群体中所有参与者的平均收益之间的关系而衰减或保持不变。仿真结果表明,短记忆长度和动态记忆在促进合作方面具有优势。此外,初始阈值与记忆长度之间的协同效应更好地促进了合作。此外,当初始阈值较低时,阈值调整参数α的轻微增加促进了合作。这些发现揭示了如何通过具体规则加强合作。
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Applied Mathematics and Computation
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