تقرير
Fast evaluation of interaction integrals for confined systems with machine learning
العنوان: | Fast evaluation of interaction integrals for confined systems with machine learning |
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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 |
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