5 papers
Variational subspace methods and application to improving variational Monte Carlo dynamics
Adrien Kahn, Luca Gravina, Filippo Vicentini
We present a formalism that allows for the direct manipulation and optimization of subspaces, circumventing the need to optimize individual states when using subspace methods. Usin…
Dissipative Quantum Chaos unveiled by Stochastic Quantum Trajectories
Filippo Ferrari, Luca Gravina, Debbie Eeltink +3
We define quantum chaos and integrability in open quantum many-body systems as a dynamical property of single stochastic realizations, referred to as quantum trajectories. This def…
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…
Looking elsewhere: improving variational Monte Carlo gradients by importance sampling
Antoine Misery, Luca Gravina, Alessandro Santini +1
Neural-network quantum states (NQS) offer a powerful and expressive ansatz for representing quantum many-body wave functions. However, their training via Variational Monte Carlo (V…
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…