The IRIS-HEP Analysis Grand Challenge Article Swipe
Analysis workflows commonly used at the LHC experiments do not scale to the requirements of the HL-LHC. To address this challenge, a rich research and development program is ongoing, proposing new tools, techniques, and approaches. The IRIS-HEP software institute and its partners are bringing together many of these developments and putting them to the test in a project called the Analysis Grand Challenge (AGC). The AGC aims to demonstrate how novel workflows can scale to analysis needs at the HL-LHC. It is based around a physics analysis using publicly available Open Data and includes the relevant technical requirements and features that analysers at the LHC need. The analysis demonstration developed in this context is heavily based on tools from the HEP Python ecosystem and makes use of modern analysis facilities. This talk will review the state of the ecosystem, describe the status of the AGC, and showcase how the envisioned workflows look in practice.
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Metadata
- Type
- article
- Language
- en
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All OpenAlex metadata
Raw OpenAlex JSON
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https://doi.org/10.22323/1.414.0235Digital Object Identifier
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The IRIS-HEP Analysis Grand ChallengeWork title
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articleOpenAlex work type
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enPrimary language
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2022Year of publication
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2022-11-26Full publication date if available
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A. Held, Oksana ShaduraList of authors in order
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https://doi.org/10.22323/1.414.0235Publisher landing page
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https://pos.sissa.it/414/235/pdfDirect link to full text PDF
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YesWhether a free full text is available
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hybridOpen access status per OpenAlex
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https://pos.sissa.it/414/235/pdfDirect OA link when available
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9Total citation count in OpenAlex
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2025: 5, 2024: 4Per-year citation counts (last 5 years)
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10Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.analysis | 75, 86, 107, 128 |
| abstract_inverted_index.bringing | 43 |
| abstract_inverted_index.commonly | 2 |
| abstract_inverted_index.describe | 139 |
| abstract_inverted_index.features | 99 |
| abstract_inverted_index.includes | 93 |
| abstract_inverted_index.ongoing, | 28 |
| abstract_inverted_index.partners | 41 |
| abstract_inverted_index.publicly | 88 |
| abstract_inverted_index.relevant | 95 |
| abstract_inverted_index.research | 23 |
| abstract_inverted_index.showcase | 146 |
| abstract_inverted_index.software | 37 |
| abstract_inverted_index.together | 44 |
| abstract_inverted_index.Challenge | 62 |
| abstract_inverted_index.analysers | 101 |
| abstract_inverted_index.available | 89 |
| abstract_inverted_index.developed | 109 |
| abstract_inverted_index.ecosystem | 122 |
| abstract_inverted_index.institute | 38 |
| abstract_inverted_index.practice. | 153 |
| abstract_inverted_index.proposing | 29 |
| abstract_inverted_index.technical | 96 |
| abstract_inverted_index.workflows | 1, 71, 150 |
| abstract_inverted_index.challenge, | 20 |
| abstract_inverted_index.ecosystem, | 138 |
| abstract_inverted_index.envisioned | 149 |
| abstract_inverted_index.approaches. | 34 |
| abstract_inverted_index.demonstrate | 68 |
| abstract_inverted_index.development | 25 |
| abstract_inverted_index.experiments | 7 |
| abstract_inverted_index.facilities. | 129 |
| abstract_inverted_index.techniques, | 32 |
| abstract_inverted_index.developments | 48 |
| abstract_inverted_index.requirements | 13, 97 |
| abstract_inverted_index.demonstration | 108 |
| cited_by_percentile_year.max | 98 |
| cited_by_percentile_year.min | 97 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 2 |
| citation_normalized_percentile.value | 0.88484087 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | True |