A Monte Carlo algorithm for spin foam intertwiners

Fuente: arXiv
Enregistré dans:
Détails bibliographiques
Auteur principal: Steinhaus, Sebastian
Format: Preprint
Publié: 2024
Sujets:
Accès en ligne:
Tags: Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
_version_ 1866910539511234560
author Steinhaus, Sebastian
author_facet Steinhaus, Sebastian
contents Monte Carlo algorithms are barely considered in spin foam quantum gravity. Due to the quantum nature of spin foam amplitudes one cannot readily apply them, and the present sign problem is a threat to convergence and thus efficiency. Yet, ultimately the severity of the sign problem in spin foams is not known. In this article we propose a new probability distribution for coherent (boundary) intertwiners, which we use to define a Markov Chain Monte Carlo algorithm. We apply this algorithm to the SU(2) coherent vertex amplitude for various Regge-type boundary data and find convergent, accurate results at far lower costs than the explicit calculation. The resources are instead used to increase the size of boundary spins, bridging the gap to the asymptotic formulae. While the sign problem is not solved, it is under control in the vast majority of cases. We close by discussing how this algorithm can be extended to larger triangulations with boundary and 4d Lorentzian spin foam models. More speculatively, we discuss how this algorithm can be used to sample (Regge-geometric) bulk intertwiners.
format Preprint
id arxiv_https___arxiv_org_abs_2403_04836
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle A Monte Carlo algorithm for spin foam intertwiners
Steinhaus, Sebastian
General Relativity and Quantum Cosmology
Monte Carlo algorithms are barely considered in spin foam quantum gravity. Due to the quantum nature of spin foam amplitudes one cannot readily apply them, and the present sign problem is a threat to convergence and thus efficiency. Yet, ultimately the severity of the sign problem in spin foams is not known. In this article we propose a new probability distribution for coherent (boundary) intertwiners, which we use to define a Markov Chain Monte Carlo algorithm. We apply this algorithm to the SU(2) coherent vertex amplitude for various Regge-type boundary data and find convergent, accurate results at far lower costs than the explicit calculation. The resources are instead used to increase the size of boundary spins, bridging the gap to the asymptotic formulae. While the sign problem is not solved, it is under control in the vast majority of cases. We close by discussing how this algorithm can be extended to larger triangulations with boundary and 4d Lorentzian spin foam models. More speculatively, we discuss how this algorithm can be used to sample (Regge-geometric) bulk intertwiners.
title A Monte Carlo algorithm for spin foam intertwiners
topic General Relativity and Quantum Cosmology
url https://arxiv.org/abs/2403.04836