Machine-learning could help us use cosmic muons to peer inside large objects such as nuclear reactors. Developed by researchers in China, the technique is capable of identifying target materials such as uranium even if they are coated with other materials. The muon is a subatomic particle that is essentially a heavier version of the electron. Huge numbers of cosmic muons are created in Earth’s atmosphere when cosmic rays collide with gas molecules. Thousands of cosmic muons per second rain down on every square metre of Earth’s surface and these particles can penetrate tens to hundreds of metres through solid materials. As a result, cosmic muons are used to peer inside large objects such as nuclear reactors, volcanoes and ancient pyramids. This involves placing detectors next to an object and detecting muons that have passed through or scattered within the object. Detector data are then processed using a tomography algorithm to create a 3D image of the object’s interior.…