Speaker
Andrea Bulgarelli
(University of Turin and INFN Turin)
Description
Entanglement calculations in quantum field theories are extremely challenging and typically rely on the replica trick, where the problem is rephrased in a study of defects. We demonstrate that the use of deep generative models drastically outperforms standard Monte Carlo algorithms. Remarkably, such a machine-learning method enables high-precision estimates of Rényi entropies in three dimensions for very large lattices. Moreover, we propose a new paradigm for studying lattice defects with flow-based sampling.
| Parallel Session (for talks only) | Quantum computing and quantum information |
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Authors
Alessando Nada
Andrea Bulgarelli
(University of Turin and INFN Turin)
Elia Cellini
Karl Jansen
Kim A. Nicoli
Marco Panero
Shinichi Nakajima
Stefan K\"{u}hn
