Automatic Differentiation for error analysis
Automatic Differentiation for error analysis
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自动微分误差分析
DOI：
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发表时间：
2020
期刊：
影响因子：
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通讯作者：
Alberto Ramos
中科院分区：
文献类型：
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作者：
Alberto Ramos
我们提出ADerrors。一个用于蒙特卡罗数据线性误差传播和分析的软件。虽然重点是在Lattice QCD中的数据分析，其中观测值的估计必须从蒙特卡罗样本中计算，该软件还处理具有不确定性的变量，相关或不相关。由于自动微分技术，即使在迭代算法中（即非线性拟合参数中的误差），线性误差传播也能精确地执行。在本文中，我们概述了该软件的功能，包括获取拟合参数中的不确定性和处理相关数据。该软件是用julia编写的，可以在这个https URL中下载和使用
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 this https URL