282 citations · 328 across the 8 of their papers we have counts for
25 papers
Dilute neutron star matter from neural-network quantum states
Bryce Fore, Jane M. Kim, Giuseppe Carleo +2
Low-density neutron matter is characterized by fascinating emergent quantum phenomena, such as the formation of Cooper pairs and the onset of superfluidity. We model this density r…
Exponential challenges in unbiasing quantum Monte Carlo algorithms with quantum computers
Guglielmo Mazzola, Giuseppe Carleo
Recently, Huggins et. al. [Nature, 603, 416-420 (2022)] devised a general projective Quantum Monte Carlo method suitable for implementation on quantum computers. This hybrid approa…
Entanglement Forging with generative neural network models
Patrick Huembeli, Giuseppe Carleo, Antonio Mezzacapo
The optimal use of quantum and classical computational techniques together is important to address problems that cannot be easily solved by quantum computations alone. This is the…
Continuous-variable neural-network quantum states and the quantum rotor model
James Stokes, Saibal De, Shravan Veerapaneni +1
We initiate the study of neural-network quantum state algorithms for analyzing continuous-variable lattice quantum systems in first quantization. A simple family of continuous-vari…
Simultaneous Perturbation Stochastic Approximation of the Quantum Fisher Information
Julien Gacon, Christa Zoufal, Giuseppe Carleo +1
The Quantum Fisher Information matrix (QFIM) is a central metric in promising algorithms, such as Quantum Natural Gradient Descent and Variational Quantum Imaginary Time Evolution.…
Hamiltonian reconstruction as metric for variational studies
Kevin Zhang, Samuel Lederer, Kenny Choo +3
Variational approaches are among the most powerful modern techniques to approximately solve quantum many-body problems. These encompass both variational states based on tensor or n…