In the coming decades, we will face major computational challenges, when the improved sensitivity of third-generation gravitational wave detectors will be such that they will be able to detect a high number (of the order of 7 × 104 per year) of multi-messenger events from binary neutron star mergers, similar to GW 170817. In this Perspective, we discuss the application of multimodal artificial intelligence techniques for multi-messenger astrophysics, fusing the information from different signal emissions.
Cuoco E, Patricelli B, Iess A, Morawski F (2022). Computational challenges for multimodal astrophysics. NATURE COMPUTATIONAL SCIENCE, 2(8), 479-485 [10.1038/s43588-022-00288-z].
Computational challenges for multimodal astrophysics
Cuoco E
;
2022
Abstract
In the coming decades, we will face major computational challenges, when the improved sensitivity of third-generation gravitational wave detectors will be such that they will be able to detect a high number (of the order of 7 × 104 per year) of multi-messenger events from binary neutron star mergers, similar to GW 170817. In this Perspective, we discuss the application of multimodal artificial intelligence techniques for multi-messenger astrophysics, fusing the information from different signal emissions.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
