Mathematical Physics for Artificial Intelligence
A special issue of Modern Mathematical Physics (ISSN 3042-5034).
Deadline for manuscript submissions: 10 November 2025 | Viewed by 169
Special Issue Editors
2. School of Science, Beijing University of Posts and Telecommunications, Beijing, China
Interests: complex systems; nonlinear dynamics; statistical physics; systems biology; intelligence science; mathematical physics; integrable systems
2. Beijing Computational Science Research Center, Beijing 100193, China
Interests: theoretical and mathematical physics—fundamental aspects of quantum mechanics, quantum theories for information, statistical thermodynamics of complex systems and science of reliability; entropy and complex system; quantum physics
Special Issue Information
Dear Colleagues,
The newly launched Journal, Modern Mathematical Physics, is dedicated to advancing research at the intersection of mathematics and physics, encompassing a broad spectrum of theoretical and applied studies.
In 2024, the Nobel Prizes in physics and chemistry were awarded to AI-related research, which is a big surprise to traditional professionals in these fields. Nevertheless, the study of brains, artificial intelligence, and more broadly, complex systems, indeed challenges us with unprecedented pace and difficulty, embracing almost all branches in science and engineering. It is of utmost importance to understand the designing principles, working mechanism, training procedure, and security guidelines underlying intelligence—an emergent phenomenon out of interactions among components of a physical systems, which surely requires new tools originated from disparate areas including, but not limited to, statistical learning, dynamical systems, functional approximation, optimal transport, information geometry, complex networks, thermodynamics, statistical physics, phase transitions, etc.
In this Special Issue, we solicit original research or review papers on the study of mathematical physics for artificial intelligence, which explain its emergence, the learning process, or the resulting machine with mathematics or physical principles. We hope that a compilation of this Special Issue will provide a broad audience with insights from traditional science and guiding inspiration for future research in artificial intelligence.
Prof. Dr. Yueheng Lan
Prof. Dr. Chang-Pu Sun
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. Modern Mathematical Physics is an international peer-reviewed open access quarterly 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 1000 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
- artificial intelligence
- mathematical physics
- statistical learning
- Bayesian deduction
- statistical physics
- information theory
Benefits of Publishing in a Special Issue
- Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
- Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
- Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
- External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
- e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.
Further information on MDPI's Special Issue polices can be found here.
