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Copy file name to clipboardexpand all lines: talk.md
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The analysis pipeline of the demonstrator incorporates a comprehensive suite of tools and libraries.
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These include uproot for data reading, awkward-array for data manipulation, Dask for parallel computing, and hist for histogram processing.
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For the purpose of statistical analysis, the pipeline integrates cabinetry and pyhf, providing a robust toolkit for analysis.
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.bold[A significant component of this project is the custom application of corrections, scale factors, and systematic errors using ATLAS software.
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The infrastructure and methodology for these applications will be discussed in detail during the presentation, underscoring the adaptability of the Python ecosystem for high-energy physics analysis.]
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A significant component of this project is the custom application of corrections, scale factors, and systematic errors using ATLAS software.
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The infrastructure and methodology for these applications will be discussed in detail during the presentation, underscoring the adaptability of the Python ecosystem for high-energy physics analysis.
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# Challenges for Future Analysis
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# An Analysis Grand Challenge
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HL-LHC era data scale requires rethinking how we engage with the data when we preform analysis
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HL-LHC era data scale requires rethinking interacting with data during analysis
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* .bold[Analysis Grand Challenge] (AGC) community exercise organized by [IRIS-HEP](https://iris-hep.org/) includes the stages of a projected typical HL-LHC analysis
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