The GravNet project is located between particle and gravitational wave physics and aims to build a global network of detectors that specifically searches for high-frequency gravitational waves. The detector network could help solve one of the great unsolved questions of modern physics: detecting dark matter. “High-frequency gravitational waves could, for example, be produced during the merging of what are known as primordial black holes. Our global detector network would then be able to detect such signatures,” says GravNet spokesman Prof. Dr. Matthias Schott from the Physical Institute at the University of Bonn. “And precisely these black holes are ideal candidates for dark matter.”
As part of the ERC project, the researchers will develop the first detectors for the planned network and install them in Bonn, Mainz, and Frascati. “Our detectors are based on what are known as cavity resonators in strong magnetic fields, in which high-frequency gravitational waves would trigger a very small electrical signal,” explains Matthias Schott. “Such signals are so small that they can only be detected with modern quantum technologies.”
The ambitious undertaking is only made possible by the ERC Synergy Grant program, which supports groups of up to four principal investigators offering different skills and resources in order to work on a large-scale research question. “Experimental infrastructures on site and expertise from the fields of cryogenic and magnetic technologies, quantum sensors, theoretical physics, data analysis, and extremely low-noise electronics are required to make GravNet a reality,” says Schott, who is also a member of the transdisciplinary research areas (TRA) “Modelling” and “Matter” at the University of Bonn. As part of GravNet, Prof. Schott thus cooperates with Prof. Dmitry Budker from the University of Mainz, Prof. Diego Blas from the Institut de Física d'Altes Energies (IFAE), Spain, and Dr. Claudio Gatti from the Laboratori Nazionali di Frascati (INFN-LNF), Italy. GravNet will be supported with around 10 million euros over six years; around 2.4 million euros will go to the University of Bonn.
Further information on the project "CeLEARN: Learning in Single Cells Through Dynamical Internal Representations“" can be found here.
