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pyerrors: a python framework for error analysis of Monte Carlo data

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arxiv 2209.14371 v2 pith:SIVVPL3V submitted 2022-09-28 hep-lat physics.comp-phphysics.data-an

Fabian Joswig , Simon Kuberski , Justus T. Kuhlmann , Jan Neuendorf This is my paper · ORCID
classification hep-latphysics.comp-phphysics.data-an
keywords erroranalysisdatapyerrorspythoncarlocombinedframework
verification ladder T0 review T1 audit T2 compute T3 formal
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abstract

We present the pyerrors python package for statistical error analysis of Monte Carlo data. Linear error propagation using automatic differentiation in an object oriented framework is combined with the $\Gamma$-method for a reliable estimation of autocorrelation times. Data from different sources can easily be combined, keeping the information on the origin of error components intact throughout the analysis. pyerrors can be smoothly integrated into the existing scientific python ecosystem which allows for efficient and compact analyses.

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Cited by 5 Pith papers

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