177 citations · 1.4k across the 57 of their papers we have counts for
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Quantum Monte Carlo study of the role of p-wave interactions in ultracold repulsive Fermi gases
Gianluca Bertaina, Marco G. Tarallo, Sebastiano Pilati
Single-component ultracold atomic Fermi gases are usually described using noninteracting many-fermion models. However, recent experiments reached a regime where -wave interactio…
Machine Learning Scoring Functions for Drug Discoveries from Experimental and Computer-Generated Protein-Ligand Structures: Towards Per-Target Scoring Functions
F. Pellicani, D. Dal Ben, A. Perali +1
In recent years, machine learning has been proposed as a promising strategy to build accurate scoring functions for computational docking finalized to numerically empowered drug di…
Phase separation in binary Bose mixtures at finite temperature
G. Spada, L. Parisi, G. Pascual +5
We investigate the magnetic behavior of finite-temperature repulsive two-component Bose mixtures by means of exact path-integral Monte-Carlo simulations. Novel algorithms are imple…
Accelerating equilibrium spin-glass simulations using quantum annealers via generative deep learning
Giuseppe Scriva, Emanuele Costa, Benjamin McNaughton +1
Adiabatic quantum computers, such as the quantum annealers commercialized by D-Wave Systems Inc., are routinely used to tackle combinatorial optimization problems. In this article,…
Supervised learning of random quantum circuits via scalable neural networks
S. Cantori, D. Vitali, S. Pilati
Predicting the output of quantum circuits is a hard computational task that plays a pivotal role in the development of universal quantum computers. Here we investigate the supervis…
Deep learning density functionals for gradient descent optimization
Emanuele Costa, Giuseppe Scriva, Rosario Fazio +1
Machine-learned regression models represent a promising tool to implement accurate and computationally affordable energy-density functionals to solve quantum many-body problems via…