LHC EFT WG note: SMEFT predictions, event reweighting, and simulation Article Swipe
Alberto Belvedere
,
S. Bhattacharya
,
G. Boldrini
,
S. Chatterjee
,
A. Calandri
,
S. Sánchez Cruz
,
J. Dickinson
,
Franz Glessgen
,
R. Goldouzian
,
A. Grohsjean
,
L. Jeppe
,
Charlotte Knight
,
Olivier Mattelaer
,
Kelci Mohrman
,
H. Nelson
,
V. Perovic
,
M. Presilla
,
S. H. Robertson
,
Nick L. Smith
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.21468/scipostphyscommrep.4
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.21468/scipostphyscommrep.4
This note provides a comprehensive overview of tools for predicting observables in the Standard Model effective field theory (SMEFT) at both tree level and one loop using event generators. We evaluate three primary methodologies–event reweighting, separate simulation of squared matrix elements, and full SMEFT process simulation–focusing on their statistical performance, computational efficiency, and potential biases. Each approach is assessed in terms of its accuracy, highlighting trade-offs between precision and resource demands. Practical insights into their applicability for high-energy physics analyses are offered, with particular attention to processes where SMEFT effects are significant. Additionally, we discuss the role of helicity in reweighting strategies and its impact on the quality of predictions. By comparing the methods across various LHC processes, this note provides guidance for selecting the most effective strategy for various SMEFT studies, ensuring robust predictions while optimizing computational resources.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.21468/scipostphyscommrep.4
- OA Status
- hybrid
- Cited By
- 2
- References
- 57
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4404854058
All OpenAlex metadata
Raw OpenAlex JSON
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https://openalex.org/W4404854058Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.21468/scipostphyscommrep.4Digital Object Identifier
- Title
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LHC EFT WG note: SMEFT predictions, event reweighting, and simulationWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2024Year of publication
- Publication date
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2024-11-29Full publication date if available
- Authors
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Alberto Belvedere, S. Bhattacharya, G. Boldrini, S. Chatterjee, A. Calandri, S. Sánchez Cruz, J. Dickinson, Franz Glessgen, R. Goldouzian, A. Grohsjean, L. Jeppe, Charlotte Knight, Olivier Mattelaer, Kelci Mohrman, H. Nelson, V. Perovic, M. Presilla, S. H. Robertson, Nick L. SmithList of authors in order
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https://doi.org/10.21468/scipostphyscommrep.4Publisher landing page
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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://doi.org/10.21468/scipostphyscommrep.4Direct OA link when available
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Computer science, Event (particle physics), Effective field theory, Large Hadron Collider, Process (computing), Particle physics, Physics, Operating system, Quantum mechanicsTop concepts (fields/topics) attached by OpenAlex
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2Total citation count in OpenAlex
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2025: 2Per-year citation counts (last 5 years)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.event | 27 |
| abstract_inverted_index.field | 16 |
| abstract_inverted_index.level | 22 |
| abstract_inverted_index.terms | 60 |
| abstract_inverted_index.their | 47, 74 |
| abstract_inverted_index.three | 31 |
| abstract_inverted_index.tools | 7 |
| abstract_inverted_index.using | 26 |
| abstract_inverted_index.where | 87 |
| abstract_inverted_index.while | 135 |
| abstract_inverted_index.across | 114 |
| abstract_inverted_index.impact | 104 |
| abstract_inverted_index.matrix | 39 |
| abstract_inverted_index.robust | 133 |
| abstract_inverted_index.theory | 17 |
| abstract_inverted_index.(SMEFT) | 18 |
| abstract_inverted_index.between | 66 |
| abstract_inverted_index.biases. | 54 |
| abstract_inverted_index.discuss | 94 |
| abstract_inverted_index.effects | 89 |
| abstract_inverted_index.methods | 113 |
| abstract_inverted_index.physics | 78 |
| abstract_inverted_index.primary | 32 |
| abstract_inverted_index.process | 44 |
| abstract_inverted_index.quality | 107 |
| abstract_inverted_index.squared | 38 |
| abstract_inverted_index.various | 115, 129 |
| abstract_inverted_index.Standard | 13 |
| abstract_inverted_index.analyses | 79 |
| abstract_inverted_index.approach | 56 |
| abstract_inverted_index.assessed | 58 |
| abstract_inverted_index.demands. | 70 |
| abstract_inverted_index.ensuring | 132 |
| abstract_inverted_index.evaluate | 30 |
| abstract_inverted_index.guidance | 121 |
| abstract_inverted_index.helicity | 98 |
| abstract_inverted_index.insights | 72 |
| abstract_inverted_index.offered, | 81 |
| abstract_inverted_index.overview | 5 |
| abstract_inverted_index.provides | 2, 120 |
| abstract_inverted_index.resource | 69 |
| abstract_inverted_index.separate | 35 |
| abstract_inverted_index.strategy | 127 |
| abstract_inverted_index.studies, | 131 |
| abstract_inverted_index.Practical | 71 |
| abstract_inverted_index.accuracy, | 63 |
| abstract_inverted_index.attention | 84 |
| abstract_inverted_index.comparing | 111 |
| abstract_inverted_index.effective | 15, 126 |
| abstract_inverted_index.elements, | 40 |
| abstract_inverted_index.potential | 53 |
| abstract_inverted_index.precision | 67 |
| abstract_inverted_index.processes | 86 |
| abstract_inverted_index.selecting | 123 |
| abstract_inverted_index.optimizing | 136 |
| abstract_inverted_index.particular | 83 |
| abstract_inverted_index.predicting | 9 |
| abstract_inverted_index.processes, | 117 |
| abstract_inverted_index.resources. | 138 |
| abstract_inverted_index.simulation | 36 |
| abstract_inverted_index.strategies | 101 |
| abstract_inverted_index.trade-offs | 65 |
| abstract_inverted_index.efficiency, | 51 |
| abstract_inverted_index.generators. | 28 |
| abstract_inverted_index.high-energy | 77 |
| abstract_inverted_index.observables | 10 |
| abstract_inverted_index.predictions | 134 |
| abstract_inverted_index.reweighting | 100 |
| abstract_inverted_index.statistical | 48 |
| abstract_inverted_index.highlighting | 64 |
| abstract_inverted_index.performance, | 49 |
| abstract_inverted_index.predictions. | 109 |
| abstract_inverted_index.reweighting, | 34 |
| abstract_inverted_index.significant. | 91 |
| abstract_inverted_index.Additionally, | 92 |
| abstract_inverted_index.applicability | 75 |
| abstract_inverted_index.comprehensive | 4 |
| abstract_inverted_index.computational | 50, 137 |
| abstract_inverted_index.methodologies–event | 33 |
| abstract_inverted_index.simulation–focusing | 45 |
| cited_by_percentile_year.max | 97 |
| cited_by_percentile_year.min | 95 |
| countries_distinct_count | 7 |
| institutions_distinct_count | 19 |
| citation_normalized_percentile.value | 0.91357509 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |