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The anti-ktjet clustering algorithm
Open accessAbstract
The k_t and Cambridge/Aachen inclusive jet finding algorithms for hadron-hadron collisions can be seen as belonging to a broader class of sequential recombination jet algorithms, parametrised by the power of the energy scale in the distance measure. We examine some properties of a new member of this class, for which the power is negative. This ``anti-k_t'' algorithm essentially behaves like an idealised cone algorithm, in that jets with only soft fragmentation are conical, active and passive areas are equal, the area anomalous dimensions are zero, the non-global logarithms are those of a rigid boundary and the Milan factor is universal. None of these properties hold for existing sequential recombination algorithms, nor for cone algorithms with split--merge steps, such as SISCone. They are however the identifying characteristics of the collinear unsafe plain ``iterative cone'' algorithm, for which the anti-k_t algorithm provides a natural, fast, infrared and collinear safe replacement.
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Cited by
Larkoski, A. J., Moult, I., & Nachman, B. (2020) · Physics Reports · doi:10.1016/j.physrep.2019.11.001 · Cited by 361
ATLAS Collaboration, Aad, G., Abbott, B., Abdallah, J., Abdel Khalek, S., Abdinov, O., Aben, R., Abi, B., Abolins, M., AbouZeid, O. S., et al. (2015) · The European Physical Journal C · doi:10.1140/epjc/s10052-015-3517-3 · Cited by 328
The ATLAS collaboration, Aaboud, M., Aad, G., Abbott, B., Abdinov, O., Abeloos, B., Abidi, S. H., AbouZeid, O. S., Abraham, N. L., Abramowicz, H., et al. (2018) · Journal of High Energy Physics · doi:10.1007/jhep01(2018)126 · Cited by 292
QCD-aware recursive neural networks for jet physics
Louppe, G., Cho, K., Becot, C., & Cranmer, K. (2019) · Journal of High Energy Physics · doi:10.1007/jhep01(2019)057 · Cited by 123
Metadata
- Authors
- Cacciari, M., Salam, G. P., & Soyez, G.
- Venue
- Journal of High Energy Physics
- Published
- 2008-04-16
- Volume
- 2008
- Issue
- 04
- Pages
- 063-063
- ISSN
- 1029-8479 (ISSN-L)
- OpenAlex
- W2100507804
- Cited by
- 7,140
- References
- 0
- FWCI
- 68.05
- Type
- journal article
- Language
- en
- Open access
- bronze
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