RG.BIO SIGNED

Project "RG.BIO" data sheet

The following table provides information about the project.

 Partnership

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 Project objective

Biological systems displaying collective behaviour are characterized by strong spatio-temporal correlations, which partly transcend the multiform diversity of their microscopic details, much as it happens in statistical physics systems close to a critical point. Recent experiments show that collective biological systems conform to another hallmark of statistical physics, namely scaling. Scaling laws have been found to be valid both at the static and at the dynamic level, although with critical exponents unlike any known model. Building on the experimental evidence of strong correlations and scaling laws, I will develop a novel renormalization group (RG) approach to strongly correlated biological systems, with the purpose of classifying into new universality classes the collective phenomena of life. The key theoretical idea of the method is to perform an expansion around an equilibrium field theory in which the interaction network between the individuals in the group is fixed, and to assess the stability of the resulting RG fixed points with respect to weak off-equilibrium effects, complementing the RG flow with the standard loop expansion around the upper critical dimension. The renormalization group will allow us to go beyond the hydrodynamic regime of small fluctuations, thus pushing theoretical prediction into the critical region of the parameters, where the correlation length scales with the system's size, a region experiments show to be inhabited by several biological systems. To define the starting field theory in the most economic way I will study the role of effective symmetries in giving rise to weakly conserved quantities and non-dissipative terms, and assess their stability under the RG flow. Finally, my lab will conduct new experimental campaigns on flocks (starlings, swifts), swarms (midges, mosquitoes) and cell colonies, to explore and test the new universality classes identified by the renormalization group approach.