{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/the-anti-k_t-jet-clustering-algorithm","title":"The anti-k_t jet clustering algorithm","arxiv_id":"0802.1189","date":"2008-02-08","proceeding":null,"authors":["Matteo Cacciari","Gavin P. Salam","Gregory Soyez"],"abstract":"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.","url_abs":"http://arxiv.org/abs/0802.1189v2","url_pdf":"http://arxiv.org/pdf/0802.1189v2.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"links_only","authors_date_abstract":"arXiv metadata, CC0 1.0 (https://info.arxiv.org/help/license), from the Kaggle arXiv metadata snapshot of 2026-09-12"},"code_links":[{"paper_slug":"the-anti-k_t-jet-clustering-algorithm","repo_url":"https://github.com/graeme-a-stewart/antikt-python","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok","spdx":"Apache-2.0"}}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=0802.1189","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"0802.1189"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-24T18:15:14+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. Samples come from repositories linked to the paper, official or community; repo_kind says which.","repos":[{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/graeme-a-stewart/antikt-python","reach":{"status":"ok","spdx":"Apache-2.0"}}],"summary":{"unverified":3},"by_repo_kind":{"listed":{"samples":3,"ran":0,"repositories":1}},"repo_kind_vocabulary":{"official":"The archive marks this repository official for the paper","named_in_paper":"The archive records that the paper mentions this repository; it is not marked official","listed":"In the archive's code links for this paper, not marked official and not recorded as mentioned in the paper","found_in_text":"Syntology found this repository in the paper's own text; whether it is the authors' implementation is not asserted","community":"Not in the archive's code links for this paper; a community repository Syntology harvested"},"n_pointer_only_for_licence":0,"samples":[{"code_sha256_prefix":"68230455a2f3b6e4","entry":"find_closest_jets","repo":"graeme-a-stewart/antikt-python","repo_kind":"listed","path":"src/pyantikt/acceleratedbasicjetfinder.py","file_url":"https://github.com/graeme-a-stewart/antikt-python/blob/HEAD/src/pyantikt/acceleratedbasicjetfinder.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"68230455a2f3b6e4"}},{"code_sha256_prefix":"c9439490d5c6e792","entry":"find_closest_jets","repo":"graeme-a-stewart/antikt-python","repo_kind":"listed","path":"src/pyantikt/acceleratedtiledjetfinder.py","file_url":"https://github.com/graeme-a-stewart/antikt-python/blob/HEAD/src/pyantikt/acceleratedtiledjetfinder.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"c9439490d5c6e792"}},{"code_sha256_prefix":"213f514924621c58","entry":"initial_history","repo":"graeme-a-stewart/antikt-python","repo_kind":"listed","path":"src/pyantikt/history.py","file_url":"https://github.com/graeme-a-stewart/antikt-python/blob/HEAD/src/pyantikt/history.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"213f514924621c58"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}