Fast evaluation of interaction integrals for confined systems with machine learning

Autor:	Mreńca-Kolasińska, Alina, Kolasiński, Krzysztof, Szafran, Bartłomiej
Rok vydání:	2020
Předmět:	Physics - Computational Physics Condensed Matter - Mesoscale and Nanoscale Physics
Zdroj:	Phys. Rev. B 102, 075422 (2020)
Druh dokumentu:	Working Paper
DOI:	10.1103/PhysRevB.102.075422
Popis:	The calculation of interaction integrals is a bottleneck for the treatment of many-body quantum systems due to its high numerical cost. We conduct configuration interaction calculations of the few-electron states confined in III-V semiconductor 2D structures using a shallow neural network to calculate the two-electron integrals, that can be used for general isotropic interaction potentials. This approach allows for a speed up of the evaluation of the energy levels and a controllable accuracy. Comment: 9 pages, 10 figures
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2007.12875 Zobrazit plný text záznamu View this record from Arxiv