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P. Di Matteo

Researcher at Institut d'Astrophysique de Paris

Publications -  116
Citations -  16057

P. Di Matteo is an academic researcher from Institut d'Astrophysique de Paris. The author has contributed to research in topics: Galaxy & Milky Way. The author has an hindex of 42, co-authored 116 publications receiving 13799 citations. Previous affiliations of P. Di Matteo include Janssen Pharmaceutica & University of Paris.

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Journal ArticleDOI

Gaia Data Release 2. Summary of the contents and survey properties

Anthony G. A. Brown, +452 more
TL;DR: The second Gaia data release, Gaia DR2 as mentioned in this paper, is a major advance with respect to Gaia DR1 in terms of completeness, performance, and richness of the data products.
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Gaia Data Release 2: Catalogue validation

TL;DR: The second Gaia data release (DR2) contains very precise astrometric and photometric properties for more than one billion sources, astrophysical parameters for dozens of millions, radial velocities for millions, variability information for half a million of stellar sources and orbits for thousands of solar system objects as discussed by the authors.
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Gaia Data Release 2. Kinematics of globular clusters and dwarf galaxies around the Milky Way

Amina Helmi, +484 more
TL;DR: In this paper, the second data release of the Gaia mission and its power for constraining many different aspects of the dynamics of the satellites of the Milky Way is demonstrated. But the accuracy of the errors, statistical and systematic, are relatively well understood.
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The age structure of stellar populations in the solar vicinity. Clues of a two-phase formation history of the Milky Way disk

TL;DR: In this article, the authors analyzed high quality abundances data of solar neighborhood stars and showed that there are two distinct regimes of [alpha/Fe] versus age which they identify as the epochs of the thick and thin disk formation.
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Star formation efficiency in galaxy interactions and mergers: a statistical study

TL;DR: In this paper, the authors investigate the enhancement of star formation efficiency in galaxy interactions and mergers by numerical simulations of several hundred galaxy collisions, and derive general laws for the enhanced star formation as a function of the main parameters of the encounter.