101 citations · 153 across the 5 of their papers we have counts for
5 papers
Data-Driven Time Propagation of Quantum Systems with Neural Networks
James Nelson, Luuk Coopmans, Graham Kells +1
We investigate the potential of supervised machine learning to propagate a quantum system in time. While Markovian dynamics can be learned easily, given a sufficient amount of data…
Machine-learning semi-local density functional theory for many-body lattice models at zero and finite temperature
James Nelson, Rajarshi Tiwari, Stefano Sanvito
We introduce a machine-learning density-functional-theory formalism for the spinless Hubbard model in one dimension at both zero and finite temperature. In the zero-temperature cas…
Reactivity of transition-metal alloys to oxygen and sulphur
Rajarshi Tiwari, James Nelson, Chen Xu +1
Oxidation and tarnishing are the two most common initial steps in the corrosive process of metals at ambient conditions. These are always initiated with O and S binding to a metall…
Predicting the Curie temperature of ferromagnets using machine learning
James Nelson, Stefano Sanvito
The magnetic properties of a material are determined by a subtle balance between the various interactions at play, a fact that makes the design of new magnets a daunting task. High…
Machine learning density functional theory for the Hubbard model
James Nelson, Rajarshi Tiwari, Stefano Sanvito
The solution of complex many-body lattice models can often be found by defining an energy functional of the relevant density of the problem. For instance, in the case of the Hubbar…