Which data formats are supported?

The skill specifically supports ATLAS PHYSLITE and PHYS derivations, providing optimized query patterns for each format.

Can I use it with Rucio?

Yes, the skill provides specific guidance and code snippets for fetching datasets using Rucio DIDs via dataset.Rucio.

What is ServiceX used for in this skill?

ServiceX is used to extract and transform data from large ATLAS xAOD datasets into manageable formats for analysis using func_adl queries.

Does it handle unit conversions?

Yes, it automatically suggests patterns to convert data into standard LHC units such as GeV and meters within the query.

What dependencies are required to run the code?

You must ensure that 'func_adl_servicex_xaodr25' is listed as a dependency and installed in your active virtual environment.

ServiceX for ATLAS xAOD

Name: ServiceX for ATLAS xAOD
Author: gordonwatts

bygordonwatts

数据科学与机器学习

Generates and optimizes ServiceX queries in func_adl for analyzing ATLAS xAOD high-energy physics data.

关于

ServiceX for ATLAS xAOD is a specialized skill designed to streamline the creation, debugging, and execution of data extraction queries for high-energy physics research. It automates the generation of func_adl query patterns tailored for PHYSLITE and PHYS data formats, ensuring adherence to ATLAS-specific best practices such as event-level filtering, unit conversion to standard LHC units (GeV), and efficient Rucio dataset fetching. This skill simplifies the complex workflow of skimming large-scale datasets, allowing researchers to focus on data analysis rather than query syntax and data model intricacies.

主要功能

0 GitHub stars
Automated func_adl query generation for PHYSLITE and PHYS datasets
Optimized event-level and object-level filtering patterns
Automatic unit conversion to standard LHC units (GeV, meters)
Seamless integration with Rucio for dataset delivery and retrieval
Context-aware guidance for xAOD data models including jets, electrons, and muons

使用场景

Building complex skim queries for ATLAS PHYSLITE datasets
Debugging and refining func_adl queries for physics analysis
Automating dataset fetching from Rucio for local processing

关于

主要功能

0 GitHub stars
Automated func_adl query generation for PHYSLITE and PHYS datasets
Optimized event-level and object-level filtering patterns
Automatic unit conversion to standard LHC units (GeV, meters)
Seamless integration with Rucio for dataset delivery and retrieval
Context-aware guidance for xAOD data models including jets, electrons, and muons

使用场景

Building complex skim queries for ATLAS PHYSLITE datasets
Debugging and refining func_adl queries for physics analysis
Automating dataset fetching from Rucio for local processing