Rényi entanglement entropy of spin chain with Generative Neural Networks

Fuente: arXiv
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Hauptverfasser: Białas, Piotr, Korcyl, Piotr, Stebel, Tomasz, Zapolski, Dawid
Format: Preprint
Veröffentlicht: 2024
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author Białas, Piotr
Korcyl, Piotr
Stebel, Tomasz
Zapolski, Dawid
author_facet Białas, Piotr
Korcyl, Piotr
Stebel, Tomasz
Zapolski, Dawid
contents We describe a method to estimate Rényi entanglement entropy of a spin system, which is based on the replica trick and generative neural networks with explicit probability estimation. It can be extended to any spin system or lattice field theory. We demonstrate our method on a one-dimensional quantum Ising spin chain. As the generative model, we use a hierarchy of autoregressive networks, allowing us to simulate up to 32 spins. We calculate the second Rényi entropy and its derivative and cross-check our results with the numerical evaluation of entropy and results available in the literature.
format Preprint
id arxiv_https___arxiv_org_abs_2406_06193
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Rényi entanglement entropy of spin chain with Generative Neural Networks
Białas, Piotr
Korcyl, Piotr
Stebel, Tomasz
Zapolski, Dawid
Statistical Mechanics
Disordered Systems and Neural Networks
High Energy Physics - Lattice
Quantum Physics
We describe a method to estimate Rényi entanglement entropy of a spin system, which is based on the replica trick and generative neural networks with explicit probability estimation. It can be extended to any spin system or lattice field theory. We demonstrate our method on a one-dimensional quantum Ising spin chain. As the generative model, we use a hierarchy of autoregressive networks, allowing us to simulate up to 32 spins. We calculate the second Rényi entropy and its derivative and cross-check our results with the numerical evaluation of entropy and results available in the literature.
title Rényi entanglement entropy of spin chain with Generative Neural Networks
topic Statistical Mechanics
Disordered Systems and Neural Networks
High Energy Physics - Lattice
Quantum Physics
url https://arxiv.org/abs/2406.06193