Casting a safety net: A reliable machine learning approach for analyzing coalescing black holes

An interdisciplinary team has developed an algorithm that immediately checks its own calculations of merging black holes’ properties and corrects its result if necessary — inexpensively and rapidly. The machine learning method provides very accurate information about the observed gravitational waves and will be ready for use when the global network of gravitational-wave detectors starts its next observing run in May.

Source: sciencedaily.com

Related posts

Non-stop flight: 4,200 km transatlantic flight of the Painted Lady butterfly mapped

Adolescents today are more satisfied with being single

Researchers develop new training technique that aims to make AI systems less socially biased