177 citations · 1.4k across the 57 of their papers we have counts for
5 papers · 1 filter
Supervised learning of few dirty bosons with variable particle number
Pere Mujal, Àlex Martínez Miguel, Artur Polls +2
We investigate the supervised machine learning of few interacting bosons in optical speckle disorder via artificial neural networks. The learning curve shows an approximately unive…
Itinerant ferromagnetism in the repulsive Hubbard chain with anisotropic odd-wave attraction
Manpreet Singh, Sebastiano Pilati, Giuliano Orso
The ground-state properties of the Hubbard chain with on-site repulsion and anisotropic nearest-neighbor attraction are investigated by means of density matrix renormalization grou…
Scalable neural networks for the efficient learning of disordered quantum systems
N. Saraceni, S. Cantori, S. Pilati
Supervised machine learning is emerging as a powerful computational tool to predict the properties of complex quantum systems at a limited computational cost. In this article, we q…
Simulating disordered quantum systems via dense and sparse restricted Boltzmann machines
S. Pilati, P. Pieri
In recent years, generative artificial neural networks based on restricted Boltzmann machines (RBMs) have been successfully employed as accurate and flexible variational wave funct…
Boosting Monte Carlo simulations of spin glasses using autoregressive neural networks
B. McNaughton, M. V. Milošević, A. Perali +1
The autoregressive neural networks are emerging as a powerful computational tool to solve relevant problems in classical and quantum mechanics. One of their appealing functionaliti…