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High Precision FRET at Single-molecule Level for Biomolecule Structure Determination
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FunTuple: A New N-tuple Component for Offline Data Processing at the LHCb Experiment
Abhijit Mathad1,2, Martina Ferrillo1, Sacha Barré2,3
1University of Zürich, Zürich, Switzerland.
Computing and Software for Big Science
|August 30, 2024
Summary
The LHCb experiment
Area of Science:
- High Energy Physics
- Particle Physics
- Collider Physics
Background:
- The LHCb experiment requires a robust offline software framework to handle increasing data volumes from the Large Hadron Collider.
- Upcoming Run 3 and Run 4 present significant data processing challenges for the LHCb experiment.
Purpose of the Study:
- Introduce FunTuple, a new component for LHCb's offline data processing.
- Ensure consistency between trigger and offline observables.
- Provide flexibility in storing diverse event observables.
Main Methods:
- Leveraging existing trigger system tools for observable computation and storage.
- Implementing a novel component for offline data processing.
- Conducting a full suite of rigorous unit tests for validation.
Main Results:
- FunTuple enables computation and storage of diverse observables for reconstructed and simulated events.
- Consistency between trigger-computed and offline-analysed observables is achieved.
- The component offers user flexibility in customizing stored observables.
Conclusions:
- FunTuple is a reliable and flexible component for LHCb's offline data processing.
- It is crucial for addressing data challenges in Run 3 and Run 4 and beyond.
- FunTuple enhances the LHCb software framework for future analyses.
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