Anomalous Directed Percolation on a Dynamic Network using Rydberg Facilitation

Fuente: arXiv
Saved in:
Bibliographic Details
Main Authors: Brady, Daniel, Ohler, Simon, Otterbach, Johannes, Fleischhauer, Michael
Format: Preprint
Published: 2024
Subjects:
Online Access:
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866917650258460672
author Brady, Daniel
Ohler, Simon
Otterbach, Johannes
Fleischhauer, Michael
author_facet Brady, Daniel
Ohler, Simon
Otterbach, Johannes
Fleischhauer, Michael
contents The facilitation of Rydberg excitations in a gas of atoms provides an ideal model system to study epidemic evolution on (dynamic) networks and self organization of complex systems to the critical point of a non-equilibrium phase transition. Using Monte-Carlo simulations and a machine learning algorithm we show that the universality class of this phase transition can be tuned. The classes include directed percolation (DP), the most common class in short-range spreading models, and mean-field (MF) behavior, but also different types of anomalous directed percolation (ADP), characterized by rare long-range excitation processes. In a frozen gas, ground state atoms that can facilitate each other form a static network, for which we predict DP universality. Atomic motion then turns the network into a dynamic one with long-range (Levy-flight type) excitations. This leads to continuously varying critical exponents corresponding to the ADP universality class, eventually reaching MF behavior. These findings also explain the recently observed critical exponent of Rydberg facilitation in an ultra-cold gas experiment [Helmrich et al., Nature 577, 481 (2020)], which was in between DP and MF values.
format Preprint
id arxiv_https___arxiv_org_abs_2404_16523
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Anomalous Directed Percolation on a Dynamic Network using Rydberg Facilitation
Brady, Daniel
Ohler, Simon
Otterbach, Johannes
Fleischhauer, Michael
Quantum Gases
The facilitation of Rydberg excitations in a gas of atoms provides an ideal model system to study epidemic evolution on (dynamic) networks and self organization of complex systems to the critical point of a non-equilibrium phase transition. Using Monte-Carlo simulations and a machine learning algorithm we show that the universality class of this phase transition can be tuned. The classes include directed percolation (DP), the most common class in short-range spreading models, and mean-field (MF) behavior, but also different types of anomalous directed percolation (ADP), characterized by rare long-range excitation processes. In a frozen gas, ground state atoms that can facilitate each other form a static network, for which we predict DP universality. Atomic motion then turns the network into a dynamic one with long-range (Levy-flight type) excitations. This leads to continuously varying critical exponents corresponding to the ADP universality class, eventually reaching MF behavior. These findings also explain the recently observed critical exponent of Rydberg facilitation in an ultra-cold gas experiment [Helmrich et al., Nature 577, 481 (2020)], which was in between DP and MF values.
title Anomalous Directed Percolation on a Dynamic Network using Rydberg Facilitation
topic Quantum Gases
url https://arxiv.org/abs/2404.16523