Computational and Statistical Physics Approaches for Complex Systems and Social Phenomena, Fourth Edition

Dear Colleagues,

Understanding social phenomena such as politics, economics, and social conflicts is challenging because they share several properties of complex systems. They entail numerous interdependent agents interacting dynamically through processes characterized by uncertainty and unpredictability of outcomes, as well as difficulty linking causes to effects. Complex systems are nonlinear, and exhibit self-organization, adaptation, feedback loops, spontaneous order, and emergence. As a consequence, they give rise to “wicked problems”—unanticipated negative consequences of decisions—whose outcomes are difficult to analyze or predict with traditional, discipline-based methodologies. The 2021 Nobel Prize in Physics awarded to Profs. Giorgio Parisi, Suykuro Manabe, and Klaus Hasselmann for their “groundbreaking contributions to our understanding of complex systems” attests to the current focus and promise of methods for studying complexity.

The study of complex social systems requires interdisciplinary approaches, borrowing tools from statistical physics, information theory, and nonlinear dynamics, and applying them to sociology and economics. Statistical physics, in particular, can help overcome some of the obstacles to the study of complex social systems. The computational methods of statistical physics have been used in disciplines other than physics, such as biology and neuroscience. Taking advantage of the extremely rapid increase in computational capacity, the applicability of these models has expanded to other social fields. These models have been used in such diverse fields as labor relations, communication through social media, politics, and social polarization. There have been efforts to apply statistical physics methods to understand and solve current problems such as the social polarization of societies.

Trend-based predictions are common in social sciences. However, relying on “all else being equal” linear methods cannot effectively contend with complex systems. Their results are predictably wrong, except over very short time spans. Decisions based on such predictions are not particularly robust: any deviation of reality from assumptions can seriously undermine the decisions based on them. Statistical physics models have been used instead, to anticipate possible futures through scenarios. Anticipatory scenarios, increasingly applied in the politics, business, and social and urban planning, have enabled decision makers to develop robust strategies for responding to emerging problems, rather than make rigid plans that are bound to fail in complex contexts.

This Special Issue focuses on investigations of complex social systems using statistical physics simulation methods. These approaches are rooted in analogies between the behaviors of physics particles and the behaviors of human agents interacting in social spaces. We note that such analogies, seldom perfect, challenge the interpretation of physical parameters in terms of human behavior. This challenge is in need of further research.

We invite contributions to this Special Issue from researchers who study complex systems through the use of statistical physics computational methods, such as Monte Carlo simulations. The contributions may be original papers or reviews.

Prof. Dr. Hung T. Diep
Prof. Dr. Miron Kaufman
Prof. Dr. Sanda Kaufman
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the Special Issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Entropy is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.