论文标题
巴格达地图集：一个无弹性中子散射$（n，n'γ）$数据的关系数据库
The Baghdad Atlas: A relational database of inelastic neutron-scattering $(n,n'γ)$ data
论文作者
论文摘要
基于A. M. Demidov $ et $ $ al $。的原始（$ n，n'γ$）的工作开发了一个关系数据库伊拉克的巴格达（莫斯科，Atomizdat 1978）]进行105个独立测量，其中包括76个天然成分的元素样本和29个同位素增强的样品。该地图集的信息包括：$γ$ ray的能量和相对强度；核素和水平数据对应于与目标样品相关的残留核和元数据，这些数据允许与定义值相对于定义值提取通量加权（$ n，n'γ$）横截面的通量加权（$ n，n'γ$）。 The optimized angular-distribution-corrected fast-neutron flux-weighted partial $γ$-ray cross section for the production of the 846.8-keV $2^{+}_{1} \rightarrow 0^{+}_{\rm gs}$ $γ$-ray transition in $^{56}$Fe, determined to be $\langle σ_γ\ rangle = 143（29）$ MB，用于此目的。但是，可以轻松地实现所采用的横截面的不同值，以根据对该数量的修订确定来适应用户的喜好。 Atlas（$ n，N'γ$）数据已编译为一系列CSV风格的ASCII数据集，并且已经开发了一组Python脚本，以在本地构建和安装数据库。然后可以通过SQLite引擎直接访问数据库，也可以使用诸如Jupyter笔记本python-Browser接口之类的替代方法。使用完整的软件包分发了一些利用不同互动方法的示例。
A relational database has been developed based on the original ($n,n'γ$) work carried out by A. M. Demidov $et$ $al$., at the Nuclear Research Institute in Baghdad, Iraq [$"Atlas$ $of$ $Gamma$-$Ray$ $Spectra$ $from$ $the$ $Inelastic$ $Scattering$ $of$ $Reactor$ $Fast$ $Neutrons"$, Nuclear Research Institute, Baghdad, Iraq (Moscow, Atomizdat 1978)] for 105 independent measurements comprising 76 elemental samples of natural composition and 29 isotopically-enriched samples. The information from this Atlas includes: $γ$-ray energies and relative intensities; nuclide and level data corresponding to the residual nucleus and meta data associated with the target sample that allows for the extraction of the flux-weighted ($n,n'γ$) cross sections for a given transition relative to a defined value. The optimized angular-distribution-corrected fast-neutron flux-weighted partial $γ$-ray cross section for the production of the 846.8-keV $2^{+}_{1} \rightarrow 0^{+}_{\rm gs}$ $γ$-ray transition in $^{56}$Fe, determined to be $\langle σ_γ \rangle = 143(29)$ mb, is used for this purpose. However, different values for the adopted cross section can be readily implemented to accommodate user preference based on revised determinations of this quantity. The Atlas ($n,n'γ$) data has been compiled into a series of CSV-style ASCII data sets and a suite of Python scripts have been developed to build and install the database locally. The database can then be accessed directly through the SQLite engine, or using alternative methods such as the Jupyter Notebook Python-browser interface. Several examples exploiting different interaction methodologies are distributed with the complete software package.
