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The large scale structure of the universe

The large scale distribution of matter provides one of the principal observables for testing the cosmological model. The inhomogeneity of the distribution of galaxies and dark matter, the dependence of this on the scale, and its time evolution, depend critically on the parameter values of the model. The combination of measurements of the expansion rate of the Universe with those of the rate of growth of density fluctuations, allow, in principle, the basis of the theory to be tested, and also provide a verification of the theory of General Relativity. In fact, there exists the fascinating possibility that dark energy is a manifestation of a modified gravity, that is, a deviation from the Einstein equations. This is currently one of the alternatives to dark energy most actively explored. Along with observation of the cosmic microwave background, the quantitative characterisation of the large scale structure of the Universe via redshift surveys of galaxies and clusters and weak lensing measurements are surely the methods that promise the best results in this field, thanks to the large surveys either underway or planned.

Radio evidence of a minor merger in the Shapley supercluster

Jan 17, 2022

Radio evidence of a minor merger in the Shapley supercluster A group of radio astronomers led by INAF has conducted a multi-frequency and multi-band study of the Shapley Supercluster, where the formation of large structures is ongoing at the present cosmological age. Radio astronomers have discovered a radio emission that acts as a "bridge" between a cluster of galaxies and a group of galaxies

Multiwavelength snapshot of a repeating fast radio burst

Dec 09, 2021

Multiwavelength snapshot of a repeating fast radio burst With a multiwavelength campaign, a group of astronomers led by the Italian National Institute for Astrophysics (INAF) studied a repeating fast radio burst (FRB). The object FRB20201124A, discovered in November 2020, reactivated in March 2021, emitting a series of radio bursts

Classifying Seyfert Galaxies with Deep Learning

Sep 28, 2021

Classifying Seyfert Galaxies with Deep Learning Scientist uses deep learning to identify low luminous Seyfert 1.9 galaxies that are usually missed by human inspection among ten thousands of spectra. These results are published in the Astrophysical Journal Supplement Series by Yen Chen Chen, in the department of physics at Sapienza University of Rome and ICRANet