Theory and Applications of Hyperbolic Diffusion and Shannon Entropy
A special issue of Entropy (ISSN 1099-4300). This special issue belongs to the section "Statistical Physics".
Deadline for manuscript submissions: 20 June 2024 | Viewed by 1207
Special Issue Editor
Interests: stochastic processes; disorder; non-equilibrium statistical mechanics; quantum open system
Special Issue Information
Dear Colleagues,
Diffusion is ubiquitous in science, while a model of instantaneous propagation for the process itself is a matter of discussion in the real natural world. Examples of finite-velocity diffusion are heat waves in simple and complex materials, transport in special relativity, biological space-dependent population models, competition, and coupled systems in ecological transport, run-and-tumble biological motion, the geophysical earth's climate problems, neuroscience and its transport electric brain behavior, and transport in electronic circuits and in guide waves, as well as in the socio-economic propagation of information models.
The use of the canonical Fick law to study the behavior of such a system has acquired significant importance in the pioneer works of transport theory, while the Cattaneo–Fick’s law is focused on considering the finite-velocity diffusion propagation. In a related context, the telegrapher’s equation—in the wave propagation approach—addresses the important interest of describing electromagnetic transport in conducting media from a theoretical and/or experimental viewpoint. Additionally, surface gravitational waves on random media are describes by the telegrapher’s equation.
The application of information theory to study these diffusion-like systems is an open statistics problem. Further progress on this matter calls for new statistical techniques based on the Shannon entropy theory, as well as for an improved understanding of the hyperbolic diffusion problem and the waves in the stochastic telegrapher’s equation for complex systems. Contributions addressing any of these issues are very welcome.
This Special Issue aims to be a forum for the presentation of improved techniques for these kinds of finite-velocity diffusion-like systems. The analysis and interpretation of the hyperbolic diffusion using statistical tools based on the Shannon information theory fall within the scope of this Special Issue.
Prof. Dr. Manuel O. Cáceres
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. 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.
Keywords
- finite-velocity diffusion
- wave telegrapher’s equation
- stochastic and random media
- statistics information theory
- complex transport
- random waves and dispersion
- physics
- chemistry
- biology
- earth sciences
- social sciences
