Special Issue "Information Theory and Stochastics for Multiscale Nonlinear Systems"
A special issue of Entropy (ISSN 1099-4300).
Deadline for manuscript submissions: closed (30 September 2019).
Interests: applied mathematics; stochastic nonlinear modeling; prediction; data assimilation; information theory; uncertainty quantification; climate atmosphere and ocean; statistical physics
Interests: uncertainty quantification; information theory; effective data assimilation and prediction; stochastic models; efficient statistical algorithms; non-Gaussian phenomena and extreme events
Interests: uncertainty quantification; information theory; model reduction; statistical mechanics and nonlinear PDEs; multi-scale systems and applications in material science and energy research
Complex multiscale nonlinear stochastic dynamical systems are ubiquitous complex systems in geoscience, engineering, neural and material sciences. They are a grand challenge in contemporary science and engineering. Key issues are their basic mathematical structural properties and qualitative features, their statistical prediction, uncertainty quantification (UQ) and sensitivity, their data assimilation (also known as state estimation or filtering), and coping with the inevitable model errors that arise in approximating such complex systems. These model errors arise through both the curse of small ensemble size for large systems and the lack of physical understanding. Effective reduced nonlinear stochastic models in recent years often blended ideas from information theory, Bayesian statistics, and statistical physics in an emerging paradigm for these grand challenges, including extreme events prediction. In addition to multiscale nonlinear stochastic differential equations, multiscale Markov jump process and Markov chains are also important in applications using this paradigm.
This Special Issue focuses on original and new results concerning information theory, stochastic modeling and complex multiscale nonlinear systems in the paradigm as described above. Contributions for this Special Issue can involve one or several disciplines including mathematics, Bayesian statistics, statistical physics and applications.Prof. Andrew J. Majda
Dr. Nan Chen
Prof. Markos A. Katsoulakis
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 papers will be 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 1600 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.
- complex multiscale nonlinear stochastic dynamical systems
- uncertainty quantification
- data assimilation
- stochastic models
- extreme events
- Bayesian statistics
- model error