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Dipartimento di Fisica e Scienze della Terra

STAT PHYS at UNIPR

 
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Statistical Physics and Complex Systems group at UNIPR

 



 

The research work at the Statitistcal Physics group in Parma covers many topics:

 

Complex dynamics on networks:

Networks and graphs  are the most general mathematical description of a set of elements connected pairwise by a relation. Therefore, it is not surprising that graph theory has been successfully applied to a wide range of very different disciplines, from  physics to biology, to social science, computing, psychology, economy and chemistry.

See also: Synchronization on complex networks and Time varying networks

Fundamental Aspects of Nonequilibrium Quantum Mechanics:

Complex systems and their modeling are interesting simply because matter is typically complex. On small scales, quantum mechanics describes interactions and dynamics. One typical example of a complex quantum system are photosynthetic molecules (complexes) in which transport properties seem to be governed by quantum mechanical interference. Strong correlations between the constituents make even "small" systems very complicated. In the helium atom, for instance, classical three-body chaos turns into complicated ionization spectra. The modern experimental tools of atom optics allow for a bottom-up construction of strongly correlated many-body quantum systems. We are studying their behavior on the level of single atoms and their interaction. Ongoing collaborations with experimental groups the world over enrich our research on fundamental aspects of quantum transport and its control in view of applications in atomtronics and quantum information.

Entropic Distances and Information Content:

The measure of distances and of information content arise naturally in the evolution of sequences of characters. This happens in cluster mobility in spin systems, in characterization of strings in languages, in biological sequences. The potential fields of investigation are extremely variate: emergences of structures in disordered models, analysis of evolutionary trees for biological systems or languages, recognition of authorship in texts, etc. Metric considerations play a central role in all such contexts, because of the necessity of comparisons between configurations. However, distances considered so far generally limit to summarize the asset of local differences. As to the quantitative estimate of information stored in strings, typical tools are based on compressibility algorithms. The related probabilistic concepts mostly refer to the empirical frequencies obtained from databases and historical records.