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Unité de recherche
PCRD EU
Numéro de projet
03.0025
Titre du projet
STIPCO: Statistical physics of information processing and combinatorial optimization
Titre du projet anglais
STIPCO: Statistical physics of information processing and combinatorial optimization
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Mots-clé
(Anglais)
Education; Training; Scientific Research; Social Aspects
Autre Numéro de projet
(Anglais)
EU project number: HPRN-CT-2002-00319
Programme de recherche
(Anglais)
EU-programme: 5. Frame Research Programme - 4.1.1 Research training networks
Description succincte
(Anglais)
See abstract
Résumé des résultats (Abstract)
(Anglais)
Our project addresses several different problems, in various fields where modem statistical offers a unifying point of view: we will study complex systems in a number of research areas outside the traditional frontiers of physics where the application of these methods looks particularly promising. They all relate to the collective behavior of heterogeneous agents, where the 'agents' can be as diverse as logical constraints in optimisation problems or error correcting codes, proteins in molecular networks, or economic agents.
Our proposal has four main directions:
- Combinatorial optimisation problems. Optimisation is naturally related to questions that are typical of statistical physics, like for example questions about energy landscapes, dynamics in these landscapes, thermalization and out-of-equilibrium processes at work in the algorithms;
- Error correcting codes. This is a field of significant practical importance. The observation that error correcting codes are mathematically equivalent to certain theoreticals models of spin glasses makes it possible to use modem methods of the theory of disordered systems to obtain new results for error correcting codes, with particular emphasis on capacity, decoding performances and finite size effects;
- Biological systems. Biological systems are a source of interesting and relevant problems that can be successfully treated by methods of statistical physics. The recent accumulation of data on genetic sequences signals the existence of complex correlations in these systems, and calls for the development of new methods of analysis and classification of complex biological networks;
- Interacting agents in financial markets and socio-economic systems. Our strategy in these fields is to first identify relevant 'stylised facts' in empirical data and simple 'benchmark' models, which can be analysed in great detail using the concepts and tools from statistical physics.
Références bases de données
(Anglais)
Swiss Database: Euro-DB of the
State Secretariat for Education and Research
Hallwylstrasse 4
CH-3003 Berne, Switzerland
Tel. +41 31 322 74 82
Swiss Project-Number: 03.0025
SEFRI
- Einsteinstrasse 2 - 3003 Berne -
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