Machine learning for neutron scattering at ORNL<sup>*</sup>

Mathieu Doucet(Istituto Nazionale di Fisica Nucleare, Sezione di Bari), G. E. Granroth(Oak Ridge National Laboratory), Richard Archibald(Oak Ridge National Laboratory), Changwoo Do(Oak Ridge National Laboratory), D. M. Tennant(University of Tennessee at Knoxville), Anjana Samarakoon(Oak Ridge National Laboratory), Thomas Proffen(Los Alamos National Laboratory), William T. Heller(Oak Ridge National Laboratory)
Machine Learning Science and Technology
December 1, 2020
10.1088/2632-2153/abcf88
Cited by 21

Related Papers

Proximate Kitaev quantum spin liquid behaviour in a honeycomb magnet
|Unknown|2016|863
Neutron scattering in the proximate quantum spin liquid α-RuCl <sub>3</sub>
|Science|2017|724
Quantum Criticality in an Ising Chain: Experimental Evidence for Emergent E <sub>8</sub> Symmetry
|Science|2010|722
Discrete Resistance Switching in Submicrometer Silicon Inversion Layers: Individual Interface Traps and Low-Frequency (<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mfrac><mml:mrow><mml:mn>1</mml:mn></mml:mrow><mml:mrow><mml:mi>f</mml:mi></mml:mrow></mml:mfrac></mml:math>?) Noise
|Physical Review Letters|1984|711
Dirac Strings and Magnetic Monopoles in the Spin Ice Dy <sub>2</sub> Ti <sub>2</sub> O <sub>7</sub>
|Science|2009|607