EconPapers    
Economics at your fingertips  
 

Fast automated analysis of strong gravitational lenses with convolutional neural networks

Yashar D. Hezaveh (), Laurence Perreault Levasseur () and Philip J. Marshall
Additional contact information
Yashar D. Hezaveh: Kavli Institute for Particle Astrophysics and Cosmology, Stanford University
Laurence Perreault Levasseur: Kavli Institute for Particle Astrophysics and Cosmology, Stanford University
Philip J. Marshall: Kavli Institute for Particle Astrophysics and Cosmology, Stanford University

Nature, 2017, vol. 548, issue 7669, 555-557

Abstract: Estimates of parameters of strong gravitational lenses are obtained in an automated way using convolutional neural networks, with similar accuracy and greatly improved speed compared to previous methods.

Date: 2017
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.nature.com/articles/nature23463 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:nat:nature:v:548:y:2017:i:7669:d:10.1038_nature23463

Ordering information: This journal article can be ordered from
https://www.nature.com/

DOI: 10.1038/nature23463

Access Statistics for this article

Nature is currently edited by Magdalena Skipper

More articles in Nature from Nature
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

 
Page updated 2025-03-19
Handle: RePEc:nat:nature:v:548:y:2017:i:7669:d:10.1038_nature23463