N-Representable one-electron reduced density matrices reconstruction at non-zero temperatures

Y. Launay, J. Gillet
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Abstract

This article retraces different methods that have been explored to account for the atomic thermal motion in the reconstruction of one-electron reduced density matrices from experimental X-ray structure factors (XSF) and directional Compton profiles (DCP). Attention has been paid to propose the simplest possible model, which obeys the necessary N-representability conditions, while accurately reproducing all available experimental data. The deconvolution of thermal effects makes it possible to obtain an experimental static density matrix, which can directly be compared with theoretical 1-RDM (reduced density matrix). It is found that above a 1% statistical noise level, the role played by Compton scattering data becomes negligible and no accurate 1-RDM is reachable. Since no thermal 1-RDM is available as a reference, the quality of an experimentally derived temperature-dependent matrix is difficult to assess. However, the accuracy of the obtained static 1-RDM, through the performance of the refined observables, is strong evidence that the Semi-Definite Programming method is robust and well adapted to the reconstruction of an experimental dynamical 1-RDM.
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非零温度下n-可表示单电子还原密度矩阵的重构
本文回顾了利用实验x射线结构因子(XSF)和定向康普顿剖面(DCP)重建单电子还原密度矩阵时,用于解释原子热运动的不同方法。提出了最简单的模型,该模型既满足必要的n个可表征性条件,又能准确地再现所有可用的实验数据。热效应的反褶积使实验静态密度矩阵可以直接与理论1-RDM(约简密度矩阵)进行比较。研究发现,在1%以上的统计噪声水平下,康普顿散射数据的作用可以忽略不计,无法获得精确的1-RDM。由于没有可用的热1-RDM作为参考,实验导出的温度相关矩阵的质量很难评估。然而,通过改进观测值的性能,得到的静态1-RDM的精度,有力地证明了半确定规划方法是鲁棒的,并且很好地适应于实验动态1-RDM的重建。
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