دورية أكاديمية

An Error Analysis Toolkit for Binned Counting Experiments

التفاصيل البيبلوغرافية
العنوان: An Error Analysis Toolkit for Binned Counting Experiments
المؤلفون: Messerly Ben, Fine Rob, Olivier Andrew
المصدر: EPJ Web of Conferences, Vol 251, p 03046 (2021)
بيانات النشر: EDP Sciences, 2021.
سنة النشر: 2021
المجموعة: LCC:Physics
مصطلحات موضوعية: Physics, QC1-999
الوصف: We introduce the MINERvA Analysis Toolkit (MAT), a utility for centralizing the handling of systematic uncertainties in HEP analyses. The fundamental utilities of the toolkit are the MnvHnD, a powerful histogram container class, and the systematic Universe classes, which provide a modular implementation of the many universe error analysis approach. These products can be used stand-alone or as part of a complete error analysis prescription. They support the propagation of systematic uncertainty through all stages of analysis, and provide flexibility for an arbitrary level of user customization. This extensible solution to error analysis enables the standardization of systematic uncertainty definitions across an experiment and a transparent user interface to lower the barrier to entry for new analyzers.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 2100-014X
العلاقة: https://www.epj-conferences.org/articles/epjconf/pdf/2021/05/epjconf_chep2021_03046.pdfTest; https://doaj.org/toc/2100-014XTest
DOI: 10.1051/epjconf/202125103046
الوصول الحر: https://doaj.org/article/6ddd2103977c4860be94fcef414fc6a5Test
رقم الانضمام: edsdoj.6ddd2103977c4860be94fcef414fc6a5
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:2100014X
DOI:10.1051/epjconf/202125103046