3 papers
quant-ph2026
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…
quant-ph2025
Classically Prepared, Quantumly Evolved: Hybrid Algorithm for Molecular Spectra
Alessandro Santini, Stefano Barison, Filippo Vicentini
We introduce a hybrid classical-quantum algorithm to compute dynamical correlation functions and excitation spectra in many-body quantum systems, with a focus on molecular systems.…
quant-ph2025
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…