XIV Arrábida meeting
“Caminhos da Complexidade”
Convento da Arrábida, Portugal
(How
to arrive)
July 1-3, 2013
Statistical dynamics of complex systems
Statistical
mechanics concepts are becoming a powerful tool for the identification of
behavioural patterns in complex systems. By providing
a link between the detailed microscopic and the aggregated macroscopic properties
of a complex system, they capture the emerging information and identify the
quasi-stationary evolution of behavioural patterns. An important mathematical discipline in this
endeavour is the theory of stochastic processes which not only describes systems
with incomplete information as also,
through stochastic representations, provides a tool to compute the
behaviour of both random and deterministic systems. The workshop will attempt
to cover the state of the art in these domains and explain how the concepts may
be experimentally validated on several natural systems.
Invited Speakers
ORGANIZERS: T. ARAUJO (ISEG, Technical University of
Lisbon, Portugal) M. C. CARVALHO (University of Lisbon, Portugal) I. M. GAMBA (University of Texas at Austin, USA) R. V. MENDES (Complexity Sciences Institute, Portugal)
S. Banisch
(Bielefeld University, Germany)
F. Bonnetto
(Georgia Tech, USA)
L. Caffarelli
(University of Texas at Austin, USA)
E. Carlen (Rutgers
University, USA)
S. Caprino
(University of Rome Tor Vergata, Italy)
M. C. Carvalho
(University of Lisbon, Portugal)
E. Dolera
(University of Pavia, Italy)
R. Esposito (University of
Rome Tor Vergata, Italy)
I. M.
Gamba (University of Texas at Austin,
USA)
C. Liverani
(University of Rome Tor Vergata, Italy)
R. Marra
(University of Rome Tor Vergata, Italy)
R. V. Mendes
(Complexity Sciences Institute,
Portugal)
P. Morrison (University of
Texas at Austin, USA)
E. Ben-Naim
(Los Alamos, USA)
E. Orlandi
(University of Roma Tre, Italy)
M. J. Oliveira (Universidade Aberta de Lisboa)
M. Pulvirenti
(University of Rome la Sapienza, Italy)
A. J. Soares
(Universidade do Minho, Portugal)
B. Wennberg
(Chalmers Institute, Sweden)
This program is partially
supported by University
of Texas at Austin-Universities in Portugal Co-Lab initiative.