From Symmetry to Fluctuations: Topics and Advances in Statistical Mechanics and Probability Theory
A special issue of Symmetry (ISSN 2073-8994). This special issue belongs to the section "Physics".
Deadline for manuscript submissions: 30 October 2025 | Viewed by 617
Special Issue Editor
Interests: systems out of equilibrium; nonlinear phenomena; complex systems; Monte Carlo simulation
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
This Special Issue aims to consolidate leading developments at the interface of statistical mechanics and probability theory, unified under the central theme of symmetry and fluctuation. These two foundational concepts play a pivotal role in our understanding of complex systems, ranging from microscopic particle ensembles to macroscopic emergent behavior, and they continue to inspire rich mathematical structures and physical insights. The issue will highlight how symmetry principles, such as invariance under transformations, conservation laws, and group actions, shape the behavior of stochastic systems and determine equilibrium and dynamical properties. Equally central are typical and rare fluctuations, which encode the probabilistic structure of these systems and offer a powerful lens for understanding phenomena far from equilibrium.
We invite you to contribute to reflecting on the fluctuation to symmetry interplay in statistical mechanics and probability theory, from rigorous theoretical analysis to innovative applications, including but not limited to the following:
- Symmetry and invariance in probabilistic and statistical mechanical models;
- Spontaneous symmetry breaking and emergent phenomena in phase transitions;
- Fluctuation theorems and non-equilibrium thermodynamics;
- Large deviation theory, concentration inequalities, and stochastic stability;
- Interacting particle systems, random fields, and spin models;
- Markov processes, stochastic dynamics, and ergodic behavior;
- Random matrix theory and applications in complex systems;
- Dynamical processes in maximum caliber principles;
- Quantum statistical mechanics and entropic principles;
- Applications in data science, machine learning, and inference via statistical mechanics.
Dr. Sergio Curilef
Guest Editor
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 100 words) can be sent to the Editorial Office for announcement on this website.
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-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Symmetry 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 2400 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.
Keywords
- symmetry and invariance in probabilistic and statistical mechanical models
- spontaneous symmetry breaking and emergent phenomena in phase transitions
- fluctuation theorems and non-equilibrium thermodynamics
- large deviation theory, concentration inequalities, and stochastic stability
- interacting particle systems, random fields, and spin models
- markov processes, stochastic dynamics, and ergodic behavior
- random matrix theory and applications in complex systems
- dynamical processes in maximum caliber principles
- quantum statistical mechanics and entropic principles
- applications in data science, machine learning, and inference via statistical mechanics
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