Computational and Statistical Physics Approaches for Complex Systems and Social Phenomena
A special issue of Entropy (ISSN 1099-4300). This special issue belongs to the section "Statistical Physics".
Deadline for manuscript submissions: closed (29 February 2020) | Viewed by 20457
Special Issue Editor
Interests: theoretical physics with focus on critical phenomena and phase transitions
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear colleagues,
Since the 80s, methods in statistical physics have been used in various domains other than physics such as biology and neuroscience. They are also used nowadays in social sciences such as politics, economics, and sociology [1-5]. Computational methods, which have been widely developed in physics and mathematics thanks to the extremely rapid increase of computer capacity, contribute a great deal to the study of properties of the so-called complex systems [4-6]. Complex systems do not mean only systems with complicated interactions in physics; they also mean current interdisciplinary systems involving different components in scales and nature with poorly defined mutual interactions. The word “complex systems” is used as a broad term to describe problems that need interdisciplinary approaches. They include climate systems, the human brain, social conflicts, and economic issues. These interdisciplinary approaches are borrowed from statistical physics, information theory, nonlinear dynamics, sociology, economics, and biology. Novel phenomena such as self-organized entities, adaptation, feedback loops, spontaneous order, emergence, and nonlinearity are a few striking features.
This Special Issue focuses on investigations of complex systems using methods from statistical physics and computer simulations. Statistical physics is found to be a very efficient tool to study the behavior of human individuals in society, provided appropriate interactions between them are different from those between particles [see for example discussions in Ref. 4 and 5]. In addition, the interpretation of physical parameters in terms of human behavior is also a challenge for the time to come.
We invite contributions to this Special Issue from researchers who study complex systems with the use of statistical physics and computational methods such as Monte Carlo simulation. Contributions may be original papers or reviews.
Prof. Dr. Hung T. Diep
Guest Editor
References
- Galam, S. Sociophysics: A Physicist’s Modeling of Psycho-Political Phenomena; Springer Science & Business Media: New York, NY, USA, 2012.
- Barnes, T.J.; Wilson, M.W. Big data, social physics, and spatial analysis: The early years. Big Data Soc. 2014, 1–14.
- Schweitzer, F. Sociophysics. Phys. Today 2018, 71, 40.
- Diep, H.T.; Kaufman, M.; Kaufman, S. Dynamics of Two-Group Conflicts: A Statistical Model. Phys. A Stat. Mech. Appl. 2017, 469, 183–199.
- Kaufman, M.; Diep, H.T.; Kaufman, S. Sociophysics of Intractable Conflicts: Three-Group Dynamics. Phys. A Stat. Mech. Appl. 2019, 517, 175–187.
- Stauffer, D. Sociophysics simulations. Comput. Sci. Eng. 2003, 5, 71–75.
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Keywords
- Statistical physics approaches for complex system Computer simulations for complex systems
- Computational methods for social sciences
- Sociophysics
- Nonlinearity and synchronization in complex systems
- Self-organized systems
- Complex systems in politics, economics, environment
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