Foto del docente

Lauro Moscardini

Professor

Department of Physics and Astronomy

Academic discipline: FIS/05 Astronomy and Astrophysics

Director of First Cycle Degree of Astronomy

Research

Keywords: cosmology gravitational lensing galaxy clusters early universe numerical simulations

The research activity is mainly focussed in the field of theoretical and observational cosmology, in particular with the application of numerical techniques in astrophysics. The study of the formation of cosmic structures, mostly performed thanks the comparison of the results of numerical simulations with the most recent observational data, represents a robust tool to constrain the main cosmological parameters, like the contributions to the density parameter coming from the matter and dark energy. In this framework, thanks to their observability in different wavebands (optical, X-rays, Sunyaev-Zel'dovich effect, gravitational lensing, etc.), galaxy clusters play a very important role, being at the top of the hierarchical process of formation.  

Main research interests: determination of the cosmological parameters using the properties of galaxy clusters (spatial distribution, topology, velocity field, dipoles); high-resolution hydrodynamical simulations of galaxy clusters (thermal structure, X-ray properties, Sunyaev-Zel'dovich effect, dynamical models); cosmological modelling (extended study of non-gaussian models and tilted/antitilted models; constraints on quintessence models); theoretical modelling of the clustering evolution of cosmic structures and constraints on the cosmological parameters from the comparison with observational data (high-redshift galaxies, Lyman-break galaxies, galaxy clusters observed in optical, X-ray and millimetric bands, quasars); implementation of N-body and hydrodynamical codes (Particle-Mesh, Piecewise Parabolic Method); models for the perturbation evolution (non-linear approximations, eulerian theory, high-order moments, biasing); gravitational lensing from galaxy clusters (statistics of gravitational arcs, optimal filtering).

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