A new theorem from the field of quantum machine learning has poked a major hole in the accepted understanding about information scrambling.
Argonne scientists across several disciplines have combined forces to create a new process for testing and predicting the effects of high temperatures on refractory oxides.
A gardener hoping for a crop of the juiciest summer tomatoes might tend to each and every plant in a plot. But a farmer working to feed the world?
Scientists from the University of Bristol's Quantum Engineering Technology Labs (QETLabs) have developed an algorithm that provides valuable insights into the physics underlying quantum systems—paving the way for significant ...
A deep spatiotemporal neural network trained on more than 36,000 earthquakes offers a new way of quickly predicting ground shaking intensity once an earthquake is underway, researchers report at the Seismological Society ...
Using machine learning methods, researchers at TU Graz can predict the structure formation of functionalized molecules at the interfaces of hybrid materials. Now they have also succeeded in looking behind the driving forces ...
Tomographic reconstruction of an object's interior volume from limited angular views is a challenging problem with practical applications in biological imaging, failure analysis of integrated circuits, etc. A team at MIT ...
Research from Penn's Department of Physics and Astronomy has produced the largest catalog of galaxy morphology classification to date. Led by former postdocs Jesús Vega-Ferrero and Helena Domínguez Sánchez, who worked ...
With the help of machine-learning techniques, a team of astronomers has discovered a dozen quasars that have been warped by a naturally occurring cosmic "lens" and split into four similar images. Quasars are extremely luminous ...
Rock art of human figures created over thousands of years in Australia's Arnhem Land has been put through a transformative machine learning study to analyse style changes over the years.
