تقرير
Fast evaluation of interaction integrals for confined systems with machine learning
| العنوان: | Fast evaluation of interaction integrals for confined systems with machine learning |
|---|---|
| المؤلفون: | Mreńca-Kolasińska, Alina, Kolasiński, Krzysztof, Szafran, Bartłomiej |
| المصدر: | Phys. Rev. B 102, 075422 (2020) |
| سنة النشر: | 2020 |
| المجموعة: | Condensed Matter Physics (Other) |
| مصطلحات موضوعية: | Physics - Computational Physics, Condensed Matter - Mesoscale and Nanoscale Physics |
| الوصف: | 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 |
| نوع الوثيقة: | Working Paper |
| DOI: | 10.1103/PhysRevB.102.075422 |
| URL الوصول: | http://arxiv.org/abs/2007.12875 |
| رقم الأكسشن: | edsarx.2007.12875 |
| قاعدة البيانات: | arXiv |
| DOI: | 10.1103/PhysRevB.102.075422 |
|---|