Eigenvalue-flipping algorithm for matrix Monte Carlo

Autor: Samuel Kováčik, Juraj Tekel
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Zdroj: Journal of High Energy Physics, Vol 2022, Iss 4, Pp 1-12 (2022)
Druh dokumentu: article
ISSN: 1029-8479
DOI: 10.1007/JHEP04(2022)149
Popis: Abstract Many physical systems can be described in terms of matrix models that we often cannot solve analytically. Fortunately, they can be studied numerically in a straightforward way. Many commonly used algorithms follow the Monte Carlo method, which is efficient for small matrix sizes but cannot guarantee ergodicity when working with large ones. In this paper, we propose an improvement of the algorithm that, for a large class of matrix models, allows to tunnel between various vacua in a proficient way, where sign change of eigenvalues is proposed externally. We test the method on two models: the pure potential matrix model and the scalar field theory on the fuzzy sphere.
Databáze: Directory of Open Access Journals