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.
Emergent quantum mechanics (EmQM) is a research program that explores the possibility of an ontology for quantum mechanics. The resurgence of interest in realist approaches to quantum mechanics, including deterministic and indeterministic ones, challenges the standard textbook view. For example, standard “no-go” theorems against the possibility of realist, i.e., ontologically-grounded, quantum mechanics are increasingly recognized as falling short of their stated aim. Recent work also indicates that traditional assumptions and theorems such as nonlocality, contextuality, free choice, and non-signalling, need not necessarily contradict the existence of certain quantum ontologies.
On the occasion of David Bohm’s 100th birthday, a symposium on emergent quantum mechanics will be held at the University of London, Senate House, on October 26 – 28, 2017 (www.emqm17.org). This special issue features expert views that critically evaluate the prospects and significance – for 21st century physics – of ontological quantum mechanics, an approach which David Bohm helped pioneer. In original de Broglie-Bohm theory, the mathematical formalism refers to hypothetical ontic elements (e.g., John Bell’s “beables”) such as the quantum potential. In the 21st century, realist quantum approaches often distinguish between ψ-epistemic and ψ-ontic ontological quantum theories. Unlike ψ-ontic theories, the ψ-epistemic theories do not view the wave function ψ as a state of reality. Nevertheless, both types of approaches posit – again – the possibility of an ontological foundation for quantum mechanics.
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
What makes a system 'complex'? A system can be thought of as complex if its dynamics cannot be easily predicted, or explained, as a linear summation of the individual dynamics of its components. In other words, the many constituent microscopic parts bring about macroscopic phenomena that cannot be understood by considering a single part alone. There is a growing awareness that complexity is strongly related to criticality: the behaviour of dynamical spatiotemporal systems at an order/disorder phase transition where scale invariance prevails. Complex systems can also be viewed as distributed information-processing systems, particularly in the domains of computational neuroscience, health, bioinformatics, systems biology and artificial life. Consciousness emerging from neuronal activity and interactions, cell behaviour resultant from gene regulatory networks and swarming behaviour are all examples of global system behaviour emerging as a result of the local interactions of the individuals (neurons, genes, animals). Can these interactions be seen as a generic computational process? This question shapes the third component of our symposium, linking computation to complexity and criticality.
The C³ 2017 Symposium will cover a diverse range of theoretical and practical approaches to computational modelling of complex systems, including information theory, agent-based simulation, statistical physics, network theory, nonlinear dynamics, swarm intelligence, evolutionary methods, artificial life, computational epidemiology, computational neuroscience, and econophysics, among others.
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.