Foto del docente

Armando Bazzani

Associate Professor

Department of Physics and Astronomy

Academic discipline: MAT/07 Mathematical Physics

Curriculum vitae

Born: 24/2/62 Padova (Italy)

24/2/87: Degree in Physics at the University of Padova with the evaluation
         110/110 cum laude


   1992: researcher of Mathematical Physics at the Science Faculty of the
         Bologna University

   1992: PHD in Physics with a Thesis: "Analytical properties of perturbative
         series and stability in beam dynamics"

   2002: associate professor in Mathematical Physics at the Physics department
         of Bologna University

He participates to the group of Physics of Complex Systems (www.physycom.unibo.it) at the
Physics Department of the Bologna University and he coordinates some research projects in the Physics of the City Laboratory. He is responsible of the INFN theory project BO41 on physical applications of dynamical systems theory.

 Teaching activities

Analytical Mechanics for the Degree in Atmospheric Physicsand Methereology, Laboratory of Computational Techniques for the degree in Biology and Institution of Mathematics for
the degree in Architecture (Politecnico di Milano)

Research Activity of Armando Bazzani

In past years he contributed to the application of Birkhoff normal forms for symplectic maps to accelerator physics. Recently the research activity concerns the study of dynamical models relevant for social and biological systems. In particular there have been considered the applications of dynamical systems theory to neuronal networks and evolution models. In the first case we have studied the properties of the BCM neuron model for synaptic plasticity
by considering the effect of a stochastic noise in the external stimula. In the second case we are studying a mathematical modeling for the evolution of phenotypic characters, based on a non-linear Fokker-Planck equation, to reproduce the  evolvability character recently described by biologists. Finally the emergent properties of an automata gas (i.e. a statistical systems
of cognitive particles) are studied for the applications to modeling urban mobility.