Physics analysis for the HL-LHC: concepts and pipelines in practice with the Analysis Grand Challenge Article Swipe
A. Held
,
Elliott Kauffman
,
Oksana Shadura
,
Andrew Wightman
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2401.02766
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2401.02766
Realistic environments for prototyping, studying and improving analysis workflows are a crucial element on the way towards user-friendly physics analysis at HL-LHC scale. The IRIS-HEP Analysis Grand Challenge (AGC) provides such an environment. It defines a scalable and modular analysis task that captures relevant workflow aspects, ranging from large-scale data processing and handling of systematic uncertainties to statistical inference and analysis preservation. By being based on publicly available Open Data, the AGC provides a point of contact for the broader community. Multiple different implementations of the analysis task that make use of various pipelines and software stacks already exist. This contribution presents an updated AGC analysis task. It features a machine learning component and expanded analysis complexity, including the handling of an extended and more realistic set of systematic uncertainties. These changes both align the AGC further with analysis needs at the HL-LHC and allow for probing an increased set of functionality. Another focus is the showcase of a reference AGC implementation, which is heavily based on the HEP Python ecosystem and uses modern analysis facilities. The integration of various data delivery strategies is described, resulting in multiple analysis pipelines that are compared to each other.
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2401.02766
- https://arxiv.org/pdf/2401.02766
- OA Status
- green
- Related Works
- 10
- OpenAlex ID
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All OpenAlex metadata
Raw OpenAlex JSON
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https://openalex.org/W4390690179Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.48550/arxiv.2401.02766Digital Object Identifier
- Title
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Physics analysis for the HL-LHC: concepts and pipelines in practice with the Analysis Grand ChallengeWork title
- Type
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preprintOpenAlex work type
- Language
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enPrimary language
- Publication year
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2024Year of publication
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2024-01-05Full publication date if available
- Authors
-
A. Held, Elliott Kauffman, Oksana Shadura, Andrew WightmanList of authors in order
- Landing page
-
https://arxiv.org/abs/2401.02766Publisher landing page
- PDF URL
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https://arxiv.org/pdf/2401.02766Direct link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
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greenOpen access status per OpenAlex
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https://arxiv.org/pdf/2401.02766Direct OA link when available
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Python (programming language), Computer science, Modular design, Large Hadron Collider, Workflow, Scalability, Software engineering, Data science, Systems engineering, Programming language, Operating system, Engineering, Particle physics, Database, PhysicsTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.community. | 80 |
| abstract_inverted_index.described, | 184 |
| abstract_inverted_index.processing | 50 |
| abstract_inverted_index.strategies | 182 |
| abstract_inverted_index.systematic | 54, 128 |
| abstract_inverted_index.complexity, | 116 |
| abstract_inverted_index.facilities. | 175 |
| abstract_inverted_index.integration | 177 |
| abstract_inverted_index.large-scale | 48 |
| abstract_inverted_index.statistical | 57 |
| abstract_inverted_index.contribution | 100 |
| abstract_inverted_index.environment. | 32 |
| abstract_inverted_index.environments | 1 |
| abstract_inverted_index.prototyping, | 3 |
| abstract_inverted_index.preservation. | 61 |
| abstract_inverted_index.uncertainties | 55 |
| abstract_inverted_index.user-friendly | 17 |
| abstract_inverted_index.functionality. | 151 |
| abstract_inverted_index.uncertainties. | 129 |
| abstract_inverted_index.implementation, | 161 |
| abstract_inverted_index.implementations | 83 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 4 |
| citation_normalized_percentile |