Deep learning for retrieval of the internuclear distance in a molecule from interference patterns in photoelectron momentum distributions
| العنوان: | Deep learning for retrieval of the internuclear distance in a molecule from interference patterns in photoelectron momentum distributions |
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| المؤلفون: | Manfred Lein, Nikolay Shvetsov-Shilovski |
| المصدر: | Physical Review A. 105 |
| بيانات النشر: | American Physical Society (APS), 2022. |
| سنة النشر: | 2022 |
| مصطلحات موضوعية: | Atomic Physics (physics.atom-ph), Physics::Atomic and Molecular Clusters, FOS: Physical sciences, Physics::Atomic Physics, Physics - Atomic Physics |
| الوصف: | We use a convolutional neural network to retrieve the internuclear distance in the two-dimensional H$_2^{+}$ molecule ionized by a strong few-cycle laser pulse based on the photoelectron momentum distribution. We show that a neural network trained on a relatively small dataset consisting of a few thousand of images can predict the internuclear distance with an absolute error less than 0.1 a.u. We study the effect of focal averaging, and we find that the convolutional neural network trained using the focal averaged electron momentum distributions also shows a good performance in reconstructing the internuclear distance. Comment: 15 pages, 3 figures |
| تدمد: | 2469-9934 2469-9926 |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::83541406675a65817f5afb0d3a706b50 https://doi.org/10.1103/physreva.105.l021102 |
| حقوق: | OPEN |
| رقم الأكسشن: | edsair.doi.dedup.....83541406675a65817f5afb0d3a706b50 |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 24699934 24699926 |
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