Machine learning is becoming an essential part of a physicist’s toolkit. How should new students learn to use it? When Radha Mastandrea started her undergraduate physics program at MIT in 2015, she ...

Another theory held that the forces between two particles falls off exponentially in direct relationship to the distance between two particles and that the factor by which it drops is not dependent on ...

The Nobel Prize in Physics was awarded to US scientist John Hopfield and British-Canadian researcher Geoffrey Hinton for their work in the field of machine learning, the Royal Swedish Academy of ...

Machine learning can get a boost from quantum physics. On certain types of machine learning tasks, quantum computers have an exponential advantage over standard computation, scientists report in the ...

By applying new methods of machine learning to quantum chemistry research, Heidelberg University scientists have made significant strides in computational chemistry. They have achieved a major ...

The CMS Collaboration has shown, for the first time, that machine learning can be used to fully reconstruct particle ...

John Hopfield and Geoffrey Hinton won the Nobel Prize in Physics for their foundational work in artificial intelligence. Hinton, known as the godfather of AI, is a dual citizen of Canada and Britain, ...

For more than 20 years in experimental particle physics and astrophysics, machine learning has been accelerating the pace of science, helping scientists tackle problems of greater and greater ...

Researchers employ machine learning to more accurately model the boundary layer wind field of tropical cyclones. Conventional approaches to storm forecasting involve large numerical simulations run on ...