Gaussian Process Regression for Absorption Spectra Analysis of Molecular Dimers

التفاصيل البيبلوغرافية
العنوان: Gaussian Process Regression for Absorption Spectra Analysis of Molecular Dimers
المؤلفون: Taher-Ghahramani, Farhad, Zheng, Fulu, Eisfeld, Alexander
سنة النشر: 2021
المجموعة: Physics (Other)
Quantum Physics
مصطلحات موضوعية: Quantum Physics, Physics - Atomic and Molecular Clusters
الوصف: A common task is the determination of system parameters from spectroscopy, where one compares the experimental spectrum with calculated spectra, that depend on the desired parameters. Here we discuss an approach based on a machine learning technique, where the parameters for the numerical calculations are chosen from Gaussian Process Regression (GPR). This approach does not only quickly converge to an optimal parameter set, but in addition provides information about the complete parameter space, which allows for example to identify extended parameter regions where numerical spectra are consistent with the experimental one. We consider as example dimers of organic molecules and aim at extracting in particular the interaction between the monomers, and their mutual orientation. We find that indeed the GPR gives reliable results which are in agreement with direct calculations of these parameters using quantum chemical methods.
نوع الوثيقة: Working Paper
DOI: 10.1016/j.saa.2022.121091
URL الوصول: http://arxiv.org/abs/2112.07590
رقم الأكسشن: edsarx.2112.07590
قاعدة البيانات: arXiv
الوصف
DOI:10.1016/j.saa.2022.121091