论文标题
自动分化以进行错误分析
Automatic differentiation for error analysis
论文作者
论文摘要
我们提出Aderrors.jl，这是一种用于蒙特卡洛数据线性误差传播和分析的软件。尽管重点是晶格QCD中的数据分析，其中必须从蒙特卡洛样品中计算出可观察到的估计值，但该软件还处理具有不确定性的变量，即相关或不相关。由于自动分化技术，即使在迭代算法中，也可以精确地执行线性误差传播（即非线性拟合参数中的错误）。在此贡献中，我们概述了该软件的功能，包括访问拟合参数的不确定性以及处理相关数据。该软件用朱莉娅（Julia）撰写，可在https://gitlab.ift.uam-csic.es/alberto/aderrors.jl下载和使用。
We present ADerrors.jl, a software for linear error propagation and analysis of Monte Carlo data. Although the focus is in data analysis in Lattice QCD, where estimates of the observables have to be computed from Monte Carlo samples, the software also deals with variables with uncertainties, either correlated or uncorrelated. Thanks to automatic differentiation techniques linear error propagation is performed exactly, even in iterative algorithms (i.e. errors in parameters of non-linear fits). In this contribution we present an overview of the capabilities of the software, including access to uncertainties in fit parameters and dealing with correlated data. The software, written in julia, is available for download and use in https://gitlab.ift.uam-csic.es/alberto/aderrors.jl
