SLAC National Accelerator Laboratory | 2017 Aug 30
SLAC and Stanford researchers demonstrate that brain-mimicking ‘neural networks’ can revolutionize the way astrophysicists analyze their most complex data, including extreme distortions in spacetime that are crucial for our understanding of the universe.[attachment=0]neural_network_lensing_final.jpg[/attachment]
Researchers from the Department of Energy’s SLAC National Accelerator Laboratory and Stanford University have for the first time shown that neural networks – a form of artificial intelligence – can accurately analyze the complex distortions in spacetime known as gravitational lenses 10 million times faster than traditional methods.
“Analyses that typically take weeks to months to complete, that require the input of experts and that are computationally demanding, can be done by neural nets within a fraction of a second, in a fully automated way and, in principle, on a cell phone’s computer chip,” said postdoctoral fellow Laurence Perreault Levasseur, a co-author of a study published today in Nature. ...
Fast automated analysis of strong gravitational lenses with convolutional neural networks - Yashar D. Hezaveh et al
- Nature 548(7669):555 (31 Aug 2017) DOI: 10.1038/nature23463
arXiv.org > astro-ph > arXiv:1708.08842 > 29 Aug 2017