4 citations · 5 across the 2 of their papers we have counts for
17 papers · 1 filter
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…
Non-stabilizerness of Neural Quantum States
Alessandro Sinibaldi, Antonio Francesco Mello, Mario Collura +1
We introduce a methodology to estimate non-stabilizerness or "magic", a key resource for quantum complexity, with Neural Quantum States (NQS). Our framework relies on two schemes b…
Foundation Neural-Networks Quantum States as a Unified Ansatz for Multiple Hamiltonians
Riccardo Rende, Luciano Loris Viteritti, Federico Becca +3
Foundation models are highly versatile neural-network architectures capable of processing different data types, such as text and images, and generalizing across various tasks like…
Accurate neural quantum states for interacting lattice bosons
Zakari Denis, Giuseppe Carleo
In recent years, neural quantum states have emerged as a powerful variational approach, achieving state-of-the-art accuracy when representing the ground-state wave function of a gr…
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…
Challenging the Quantum Advantage Frontier with Large-Scale Classical Simulations of Annealing Dynamics
Linda Mauron, Giuseppe Carleo
Recent demonstrations of D-Wave's annealing-based quantum simulators have established new benchmarks for quantum computational advantage [arXiv:2403.00910]. However, the precise lo…