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20242026
most citedTime-dependent Neural Galerkin Method for Quantum Dynamics

4 citations · 4 across the 1 of their papers we have counts for

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6 papers

quant-ph20264 cited

Time-dependent Neural Galerkin Method for Quantum Dynamics

Alessandro Sinibaldi, Douglas Hendry, Filippo Vicentini +1

We introduce a classical computational method for quantum dynamics that relies on a global-in-time variational principle. Unlike conventional time-stepping approaches, our scheme c…

quant-ph2025

Neural Projected Quantum Dynamics: a systematic study

Luca Gravina, Vincenzo Savona, Filippo Vicentini

We investigate the challenge of classical simulation of unitary quantum dynamics with variational Monte Carlo approaches, addressing the instabilities and high computational demand…

quant-ph2025

Quantum computing and artificial intelligence: status and perspectives

Giovanni Acampora, Andris Ambainis, Natalia Ares +36

This white paper discusses and explores the various points of intersection between quantum computing and artificial intelligence (AI). It describes how quantum computing could supp…

quant-ph2025

Modern applications of machine learning in quantum sciences

Anna Dawid, Julian Arnold, Borja Requena +26

In this book, we provide a comprehensive introduction to the most recent advances in the application of machine learning methods in quantum sciences. We cover the use of deep learn…

quant-ph2024

Efficiency of neural quantum states in light of the quantum geometric tensor

Sidhartha Dash, Luca Gravina, Filippo Vicentini +2

Neural quantum state (NQS) ansätze have shown promise in variational Monte Carlo algorithms by their theoretical capability of representing any quantum state. However, the reason…

quant-ph2024

Variational Benchmarks for Quantum Many-Body Problems

Dian Wu, Riccardo Rossi, Filippo Vicentini +30

The continued development of computational approaches to many-body ground-state problems in physics and chemistry calls for a consistent way to assess its overall progress. In this…