3 papers
quant-ph2024
Learning symmetry-protected topological order from trapped-ion experiments
Nicolas Sadoune, Ivan Pogorelov, Claire L. Edmunds +6
Classical machine learning has proven remarkably useful in post-processing quantum data, yet typical learning algorithms often require prior training to be effective. In this work,…
cond-mat.str-el2024
Human-machine collaboration: ordering mechanism of rank-2 spin liquid on breathing pyrochlore lattice
Nicolas Sadoune, Ke Liu, Han Yan +3
Machine learning algorithms thrive on large data sets of good quality. Here we show that they can also excel in a typical research setting with little data of limited quality, thro…
cond-mat.str-el2020
Revealing the Phase Diagram of Kitaev Materials by Machine Learning: Cooperation and Competition between Spin Liquids
Ke Liu, Nicolas Sadoune, Nihal Rao +2
Kitaev materials are promising materials for hosting quantum spin liquids and investigating the interplay of topological and symmetry-breaking phases. We use an unsupervised and in…