Personal tools
Log in
You are here: Home Research Activities Advanced Technologies and Instrumentation Experimental radio, microwaves and gravitation

Experimental radio, microwaves and gravitation

Instrumental activity at radio wavelengths involves two, partially overlapping, scientific communities in Italy, with different scientific objectives. Radio astronomy uses, above all, coherent receivers connected to digital electronic systems for the analysis of the converted signal, on ground-based telescopes with ever larger collecting areas. To increase further the baselines of interferometric systems, possible space missions are being studied.

The study of the CMB (Cosmic Microwave Background), that is, the first light in the Universe, is today carried out using coherent (radio), incoherent (bolometers) and cryogenic quantum receivers, for ground-based telescopes, balloons (Boomerang), and space missions (Planck). Lastly, gravitational experiments using radio science are carried out with interplanetary probes, using, above all, precise radio tracking measurements.

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