Nicolas Sadoune

Efficient and scalable Path Integral Monte Carlo Simulations with worm-type updates for Bose-Hubbard and XXZ models

L. Pollet, Nicolas Sadoune, 2022, 2204.12262.

Unsupervised Interpretable Learning of Phases From Many-Qubit Systems

G. Giudici, L. Pollet, Nicolas Sadoune, 2022, 2208.08850.

Revealing the Phase Diagram of Kitaev Materials by Machine Learning: Cooperation and Competition between Spin Liquids pdf

Ke Liu, Jonas Greitemann, Lode Pollet, 2020, Physical Review Research.

Efficient and scalable path integral Monte Carlo simulations with worm-type updates for Bose-Hubbard and XXZ models

L. Pollet, Nicolas Sadoune, 2022, SciPost Physics Codebases.

Efficient and scalable path integral Monte Carlo simulations with worm-type updates for Bose-Hubbard and X X Z models

Nicolas Sadoune, 2022 .

Unsupervised interpretable learning of phases from many-qubit systems

G. Giudici, L. Pollet, Nicolas Sadoune, 2022, Physical Review Research.