2 papers
physics.comp-ph2024
Solving deep-learning density functional theory via variational autoencoders
Emanuele Costa, Giuseppe Scriva, Sebastiano Pilati
In recent years, machine learning models, chiefly deep neural networks, have revealed suited to learn accurate energy-density functionals from data. However, problematic instabilit…
quant-ph2023
Challenges of variational quantum optimization with measurement shot noise
Giuseppe Scriva, Nikita Astrakhantsev, Sebastiano Pilati +1
Quantum enhanced optimization of classical cost functions is a central theme of quantum computing due to its high potential value in science and technology. The variational quantum…