中国物理B ›› 2026, Vol. 35 ›› Issue (6): 60504-060504.doi: 10.1088/1674-1056/ae27b6

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Studying relationships from the perspective of chaos theory

Xiyu Ren(任玺谕)1, Xianying Xu(徐宪莹)1,†, Xiaodong Liu(刘晓东)2,‡, Minghui Zhang(张明会)1, Santo Banerjee3, Suo Gao(高锁)1, and Jun Mou(牟俊)1   

  1. 1 School of Information Science and Engineering, Dalian Polytechnic University, Dalian 116034, China;
    2 School of Innovation and Entrepreneurship, Dalian Polytechnic University, Dalian 116034, China;
    3 Department of Mathematical Sciences, Giuseppe Luigi Lagrange, Politecnico di Torino, Corso Duca degli Abruzzi 24, Torino, Italy
  • 收稿日期:2025-10-23 修回日期:2025-11-17 接受日期:2025-12-04 发布日期:2026-06-05
  • 通讯作者: Xianying Xu, Xiaodong Liu E-mail:xuxiany@dlpu.edu.cn;liuxiaod@dlpu.edu.cn
  • 基金资助:
    This work was supported by the National Natural Science Foundation of China (Grant No. 62571079), the Doctoral Research Startup Fund Program Project of Liaoning Province (Grant No. 2025-BS-0471), the Basic scientific research projects in department of education of Liaoning Province (Grant No. LJ212410152011), and the Research startup fund project for introducing talents of Dalian Polytechnic University (Grant No. LJBKY2025070).

Studying relationships from the perspective of chaos theory

Xiyu Ren(任玺谕)1, Xianying Xu(徐宪莹)1,†, Xiaodong Liu(刘晓东)2,‡, Minghui Zhang(张明会)1, Santo Banerjee3, Suo Gao(高锁)1, and Jun Mou(牟俊)1   

  1. 1 School of Information Science and Engineering, Dalian Polytechnic University, Dalian 116034, China;
    2 School of Innovation and Entrepreneurship, Dalian Polytechnic University, Dalian 116034, China;
    3 Department of Mathematical Sciences, Giuseppe Luigi Lagrange, Politecnico di Torino, Corso Duca degli Abruzzi 24, Torino, Italy
  • Received:2025-10-23 Revised:2025-11-17 Accepted:2025-12-04 Published:2026-06-05
  • Contact: Xianying Xu, Xiaodong Liu E-mail:xuxiany@dlpu.edu.cn;liuxiaod@dlpu.edu.cn
  • Supported by:
    This work was supported by the National Natural Science Foundation of China (Grant No. 62571079), the Doctoral Research Startup Fund Program Project of Liaoning Province (Grant No. 2025-BS-0471), the Basic scientific research projects in department of education of Liaoning Province (Grant No. LJ212410152011), and the Research startup fund project for introducing talents of Dalian Polytechnic University (Grant No. LJBKY2025070).

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摘要： The study of relationship emotions, a set of emotional and psychological responses that arise in a relationship, can help develop more humanized artificial intelligence, improve human–computer interaction, and even create more immersive experiences in virtual and augmented reality. Due to the nonlinear and feedback-driven nature of relational affect, which aligns closely with chaos theory, and the ability of leaky integrate-and-fire (LIF) neuron models to simulate dopaminerelated electrical activity in brain nuclei, this study innovatively integrates both approaches. By linking the membrane potential signals of LIF neurons to relational affect equations, it achieves a refined modeling of the mechanisms underlying relational affect generation. This paper adds the LIF neuron model to the relationship emotion model to construct a new LIF relationship emotion model (LRM). The effect of the parameters in the LRM on the relationship emotions generated by the model is investigated using numerical analysis. This includes the firing behavior produced by LIF neurons and a study of relationship emotions produced by different initial relationship emotion states under the same conditions. Finally, the feasibility of LRM is verified using a digital signal processing (DSP) platform. This process not only verifies the feasibility of LRM but also provides new ideas and methods for future research in affective computing and human–computer interaction.

关键词: relationship, emotion, chaos, neural network, DSP platform

Abstract: The study of relationship emotions, a set of emotional and psychological responses that arise in a relationship, can help develop more humanized artificial intelligence, improve human–computer interaction, and even create more immersive experiences in virtual and augmented reality. Due to the nonlinear and feedback-driven nature of relational affect, which aligns closely with chaos theory, and the ability of leaky integrate-and-fire (LIF) neuron models to simulate dopaminerelated electrical activity in brain nuclei, this study innovatively integrates both approaches. By linking the membrane potential signals of LIF neurons to relational affect equations, it achieves a refined modeling of the mechanisms underlying relational affect generation. This paper adds the LIF neuron model to the relationship emotion model to construct a new LIF relationship emotion model (LRM). The effect of the parameters in the LRM on the relationship emotions generated by the model is investigated using numerical analysis. This includes the firing behavior produced by LIF neurons and a study of relationship emotions produced by different initial relationship emotion states under the same conditions. Finally, the feasibility of LRM is verified using a digital signal processing (DSP) platform. This process not only verifies the feasibility of LRM but also provides new ideas and methods for future research in affective computing and human–computer interaction.

Key words: relationship, emotion, chaos, neural network, DSP platform

中图分类号:  (Control of chaos, applications of chaos)

  • 05.45.Gg
05.45.Jn (High-dimensional chaos)