The Conference is organized in the following three Areas to cover all the Topics of Statistical Physics:
Area A: Foundations and Theoretical aspects of classical, quantum and relativistic statistical physics and thermodynamics. Mathematical aspects and methods, formalism, rigorous results, exact solutions, connections with the methods of high energy physics, string theory, mathematical statistics and information theory, information geometry, classical, quantum and relativistic transport theory, Boltzmann and Fokker-Planck kinetics, nonlinear kinetics, dynamical systems, relaxation phenomena, random systems, pattern formation, fractal systems, solitons, chaotic systems, strongly correlated electrons, soft quantum matter, mesoscopic quantum phenomena, fractional quantum Hall effect, low dimensional quantum field theory, quantum phase transitions, quantum information and entanglement, power laws, etc.
Area B: Applications to Physical Systems: quantum systems, soft condensed matter, liquid crystals, plasmas, fluids, surfaces and interfaces, disordered and glassy systems, percolation, spin glasses, structural glasses, jamming, critical phenomena and phase transitions,fluids and interfacial phenomena, molecular and ionic fluids, metastable liquids, hydrodynamic instabilities, turbulence, growth processes, wetting, surface effects, films, crystals, confined systems, surfaces and interfaces, chemical reactions, cold atoms, etc.
Area C: Applications to non-Physical Systems: Interdisciplinary applications of statistical physics, networks and graphs, applied networks, biophysics, genomics, environments, climate and earth models, seismology, linguistics, econophysics, social systems, traffic flow, algorithmic problems, complex systems, etc.
TGSI2017 is dedicated to the geometrical and topological foundations of information theory. It will complement the 2017, 2016, 2015 and 2013 edition of "Geometric science of information" and "Information Geometry and its Applications IV", by focusing on the advances of entropy and information functions in probability, geometry, homology, algebra, category theory and their expression in physic and data analysis. There have been rapid recent developments in several different research communities in this connection, with little interaction between them, and one of the goals of the conference is to bring these communities in contact.
The conferences will review many of the new developments involving the interplay of information and algebraic and differential geometry, number theory, probability and homology. The conference will emphasize the richness and diversity of information approaches and principles that arose in mathematics, physics, and statistical data analysis (...), and will pursue at the same time the perspective of establishing a coherent theory. It emphasizes an active participation of young researchers to discuss emerging topics of collaborative research.
As for GSI’13 and GSI’15, the objective of this SEE Conference GSI’17, hosted in Paris, is to bring together pure/applied mathematicians and engineers, with common interest for Geometric tools and their applications for Information analysis. It emphasizes an active participation of young researchers to discuss emerging areas of collaborative research on “Information Geometry Manifolds and Their Advanced Applications”. Current and ongoing uses of Information Geometry Manifolds in applied mathematics are the following: Advanced Signal/Image/Video Processing, Complex Data Modeling and Analysis, Information Ranking and Retrieval, Coding, Cognitive Systems, Optimal Control, Statistics on Manifolds, Machine & Deep Learning, Artificial Intelligence, Speech/sound recognition, natural language treatment, Big Data Analytics, etc., which are also substantially relevant for industry. The Conference will be therefore held in areas of priority/focused themes and topics of mutual interest with the aim to:
Provide an overview on the most recent state-of-the-art
Exchange mathematical information/knowledge/expertise in the area
Identify research areas/applications for future collaboration
Identify academic & industry labs expertise for further collaboration
One of the most frequently used scientific words, is the word “Entropy”. The reason is that it is related to two main scientific domains: physics and information theory. Its origin goes back to the start of physics (thermodynamics), but since Shannon, it has become related to information theory. This conference is an opportunity to bring researchers of these two communities together and create a synergy. The main topics and sessions of the conference cover:
Physics: classical Thermodynamics and Quantum
Statistical physics and Bayesian computation
Geometrical science of information, topology and metrics
Maximum entropy principle and inference
Kullback and Bayes or information theory and Bayesian inference
Entropy in action (applications)
The inter-disciplinary nature of contributions from both theoretical and applied perspectives are very welcome, including papers addressing conceptual and methodological developments, as well as new applications of entropy and information theory.