Advances in Symmetry and Complex Systems

A special issue of Symmetry (ISSN 2073-8994). This special issue belongs to the section "Physics".

Deadline for manuscript submissions: 31 December 2024 | Viewed by 4706

Special Issue Editors

School of Journalism and Communication, Nanjing University, Nanjing 210000, China
Interests: complex networks; social physics

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Guest Editor
School of Physics, Nanjing University, Nanjing 210093, China
Interests: soft matter physics; statistical physics; active fluids; disordered hyperuniformity; critical phenomena

Special Issue Information

Dear Colleagues,

Complex systems are of interest throughout the fields of applied mathematics, statistical physics and computational science. Many important complex systems exhibit symmetry, a mathematical principle or physical phenomenon that, in recent years, has attracted widespread attention from interdisciplinary researchers. We aim to solicit contributions to complex systems or symmetry from a variety of different fields, including mathematics, physics and social science.

Dr. Keke Shang
Dr. Qunli Lei
Guest Editors

Manuscript Submission Information

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Keywords

  • complex systems
  • social physics
  • statistical physics
  • soft matter physics
  • symmetry
  • complex networks
  • null models
  • community detection
  • information or disease spreading
  • active fluids
  • disordered hyperuniformity
  • critical phenomena

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Published Papers (3 papers)

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Research

12 pages, 2673 KiB  
Article
Schwartz Symmetry Condition for Coherent Diffraction Imaging Patterns
by Eduardo X. Miqueles, Tiago Kalile and Yuri R. Tonin
Symmetry 2024, 16(4), 399; https://doi.org/10.3390/sym16040399 - 29 Mar 2024
Viewed by 953
Abstract
We demonstrate a symmetry condition for the mixed partial derivatives of measured data when performing a coherent diffraction imaging (CDI) experiment for differentiable samples under scientific investigation. The proposed condition can be used as a physical restriction to improve real data measurements and [...] Read more.
We demonstrate a symmetry condition for the mixed partial derivatives of measured data when performing a coherent diffraction imaging (CDI) experiment for differentiable samples under scientific investigation. The proposed condition can be used as a physical restriction to improve real data measurements and has been used within the most celebrated phase-retrieval inversion algorithms as an ad hoc constraint without proof. The symmetry relies on John’s ultrahyperbolic equation for the X-ray transform, which is also demonstrated to be valid in the imaging regime for CDI. The obtained conditions are easy to implement and can be used as a constraint by computational imaging methods. Full article
(This article belongs to the Special Issue Advances in Symmetry and Complex Systems)
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22 pages, 1329 KiB  
Article
Propagation Dynamics of an Epidemic Model with Heterogeneous Control Strategies on Complex Networks
by Yan Wang, Shanshan Chen, Dingguo Yu, Lixiang Liu and Ke-Ke Shang
Symmetry 2024, 16(2), 166; https://doi.org/10.3390/sym16020166 - 31 Jan 2024
Cited by 1 | Viewed by 1477
Abstract
Complex network theory involves network structure and dynamics; dynamics on networks and interactions between networks; and dynamics developed over a network. As a typical application of complex networks, the dynamics of disease spreading and control strategies on networks have attracted widespread attention from [...] Read more.
Complex network theory involves network structure and dynamics; dynamics on networks and interactions between networks; and dynamics developed over a network. As a typical application of complex networks, the dynamics of disease spreading and control strategies on networks have attracted widespread attention from researchers. We investigate the dynamics and optimal control for an epidemic model with demographics and heterogeneous asymmetric control strategies (immunization and quarantine) on complex networks. We derive the epidemic threshold and study the global stability of disease-free and endemic equilibria based on different methods. The results show that the disease-free equilibrium cannot undergo a Hopf bifurcation. We further study the optimal control strategy for the complex system and obtain its existence and uniqueness. Numerical simulations are conducted on scale-free networks to validate and supplement the theoretical results. The numerical results indicate that the asymmetric control strategies regarding time and degree of node for populations are superior to symmetric control strategies when considering control cost and the effectiveness of controlling infectious diseases. Meanwhile, the advantages of the optimal control strategy through comparisons with various baseline immunization and quarantine schemes are also shown. Full article
(This article belongs to the Special Issue Advances in Symmetry and Complex Systems)
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13 pages, 279 KiB  
Article
Distribution of Return Transition for Bohm-Vigier Stochastic Mechanics in Stock Market
by Chang Liu, Chuo Chang and Zhe Chang
Symmetry 2023, 15(7), 1431; https://doi.org/10.3390/sym15071431 - 17 Jul 2023
Viewed by 1097
Abstract
The Bohm-Vigier stochastic model is assumed as a natural generalization of the Black-Scholes model in stock market. The behavioral factor of stock market recognizes as a hidden sector in Bohmian mechanics. A Fokker-Planck equation description for the Bohm-Vigier stochastic model is presented. We [...] Read more.
The Bohm-Vigier stochastic model is assumed as a natural generalization of the Black-Scholes model in stock market. The behavioral factor of stock market recognizes as a hidden sector in Bohmian mechanics. A Fokker-Planck equation description for the Bohm-Vigier stochastic model is presented. We find the familiar Boltzmann distribution is a stationary solution of the Fokker-Planck equation for the Bohm-Vigier model. The return transition distribution of stock market, which corresponds with a time-dependent solution of the Fokker-Planck equation, is obtained. Full article
(This article belongs to the Special Issue Advances in Symmetry and Complex Systems)
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