Symmetry Beyond the Standard Model of High Energy Physics: Theory, Methods and Applications

Dear Colleagues,

Symmetry has long served as a guiding principle in the development of physical theories, from the formulation of the Standard Model of particle physics to the description of cosmological evolution. Yet, many questions remain unresolved within the SM of particle physics and cosmology, including the nature of dark matter and dark energy, the origin of mass hierarchies, the dynamics of the Higgs sector, the properties of neutrinos, and the quantum structure of gravity. Addressing these challenges requires theoretical innovation, new computational methodologies, and the integration of modern data-driven tools.

This Special Issue, “Symmetry Beyond the Standard Model of High Energy Physics: Theory, Methods and Applications”, aims to highlight the central role of symmetry in exploring physics beyond established frameworks. We welcome contributions on novel symmetry-breaking mechanisms, extended Higgs sectors and their phenomenology, neutrino physics and flavor symmetries, gauge and discrete symmetries, supersymmetry, dualities, conformal structures, and higher-dimensional approaches. Studies that connect theoretical advances with experimental and observational data are particularly encouraged, including collider phenomenology, precision tests of the Higgs boson, neutrino oscillations and CP violation, cosmological probes of symmetry-based models, and searches for new physics signatures.

In parallel with the theoretical and phenomenological work, this Special Issue aims to highlight the methodological innovations that are transforming high energy physics. Modern computational tools, advanced statistical techniques, and artificial intelligence (AI) approaches, to name a few, are now integral aspects for theory building, model testing, and data analysis. We invite contributions on computational high energy physics, Bayesian and frequentist statistical methods, uncertainty quantification, and high-dimensional data analysis. Particular attention will be given to emerging applications of AI and machine learning, including anomaly detection in collider and neutrino experiments, generative models for theoretical predictions, symbolic regression of Lagrangians, and numerical computations with large language models.

By bringing together perspectives from theory, phenomenology, computation, and AI, this Special Issue seeks to provide a comprehensive view of how symmetry continues to guide our understanding of nature at its most fundamental level. Contributions that bridge traditional high energy physics with modern data science, or that illustrate interdisciplinary applications of symmetry principles, will be especially valuable.

Potential topics to be included in this Special Issue consist of, but are not limited to, the following:

1. Symmetry principles.
2. Beyond the Standard Model.
3. Higgs physics and symmetry breaking.
4. Neutrino physics and flavor symmetries.
5. Gauge and discrete symmetries.
6. Supersymmetry and dualities.
7. Computational high energy physics.
8. Advanced statistics for physics.
9. Machine learning and AI methods.
10. Large language models in physics.

Prof. Dr. Hugo García-Tecocoatzi
Prof. Dr. Andrés Ramírez-Morales
Prof. Dr. Rodrigo Gamboa Goñi
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 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.

• symmetry principles
• beyond the standard model
• higgs physics and symmetry breaking
• neutrino physics and flavor symmetries
• gauge and discrete symmetries
• supersymmetry and dualities
• computational high energy physics
• advanced statistics for physics
• machine learning and ai methods
• large language models in physics