{"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/jetlov-enhancing-jet-tree-tagging-through","title":"JetLOV: Enhancing Jet Tree Tagging through Neural Network Learning of Optimal LundNet Variables","arxiv_id":"2311.14654","date":"2023-11-24","proceeding":null,"authors":["Mauricio A. Diaz","Giorgio Cerro","Jacan Chaplais","Srinandan Dasmahapatra","Stefano Moretti"],"abstract":"Machine learning has played a pivotal role in advancing physics, with deep learning notably contributing to solving complex classification problems such as jet tagging in the field of jet physics. In this experiment, we aim to harness the full potential of neural networks while acknowledging that, at times, we may lose sight of the underlying physics governing these models. Nevertheless, we demonstrate that we can achieve remarkable results obscuring physics knowledge and relying completely on the model's outcome. We introduce JetLOV, a composite comprising two models: a straightforward multilayer perceptron (MLP) and the well-established LundNet. Our study reveals that we can attain comparable jet tagging performance without relying on the pre-computed LundNet variables. Instead, we allow the network to autonomously learn an entirely new set of variables, devoid of a priori knowledge of the underlying physics. These findings hold promise, particularly in addressing the issue of model dependence, which can be mitigated through generalization and training on diverse data sets.","url_abs":"https://arxiv.org/abs/2311.14654v1","url_pdf":"https://arxiv.org/pdf/2311.14654v1.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":"abstracts"},"code_links":[{"paper_slug":"jetlov-enhancing-jet-tree-tagging-through","repo_url":"https://github.com/giorgiocerro/jetlov","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"pytorch","reach":{"status":"ok","spdx":"BSD-3-Clause"}}],"tasks":[{"task_slug":"jet-tagging","task_name":"Jet Tagging"}],"methods":[{"method_slug":"set","method_name":"SET"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=2311.14654","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2311.14654"}},"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":"deterministic:regex_extraction","url":"https://github.com/GiorgioCerro/jetlov","reach":{"status":"ok","spdx":"BSD-3-Clause"}},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/giorgiocerro/jetlov","reach":{"status":"ok","spdx":"BSD-3-Clause"}}],"summary":{"ran":4,"unverified":1},"by_repo_kind":{"official":{"samples":5,"ran":4,"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":"d3f9722bb17b38e3","entry":"bkg_rejection_at_threshold","repo":"GiorgioCerro/jetlov","repo_kind":"official","path":"experiments/shower.py","file_url":"https://github.com/GiorgioCerro/jetlov/blob/HEAD/experiments/shower.py","link_basis":"first_harvest_node","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"BSD-3-Clause","inline_ok":true,"mcp_get_code":{"code_sha256":"d3f9722bb17b38e3"}},{"code_sha256_prefix":"898b1a99f58bd705","entry":"count_params","repo":"GiorgioCerro/jetlov","repo_kind":"official","path":"src/jetlov/util.py","file_url":"https://github.com/GiorgioCerro/jetlov/blob/HEAD/src/jetlov/util.py","link_basis":"first_harvest_node","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"BSD-3-Clause","inline_ok":true,"mcp_get_code":{"code_sha256":"898b1a99f58bd705"}},{"code_sha256_prefix":"26b3c531b94df21d","entry":"delta_eta_reflect","repo":"GiorgioCerro/jetlov","repo_kind":"official","path":"src/jetlov/jet_dataset.py","file_url":"https://github.com/GiorgioCerro/jetlov/blob/HEAD/src/jetlov/jet_dataset.py","link_basis":"first_harvest_node","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"BSD-3-Clause","inline_ok":true,"mcp_get_code":{"code_sha256":"26b3c531b94df21d"}},{"code_sha256_prefix":"a8b6f9791381fad6","entry":"pad_array","repo":"GiorgioCerro/jetlov","repo_kind":"official","path":"src/jetlov/jet_dataset.py","file_url":"https://github.com/GiorgioCerro/jetlov/blob/HEAD/src/jetlov/jet_dataset.py","link_basis":"first_harvest_node","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"BSD-3-Clause","inline_ok":true,"mcp_get_code":{"code_sha256":"a8b6f9791381fad6"}},{"code_sha256_prefix":"aac1dd28c8780f75","entry":"create_batches","repo":"GiorgioCerro/jetlov","repo_kind":"official","path":"experiments/shower.py","file_url":"https://github.com/GiorgioCerro/jetlov/blob/HEAD/experiments/shower.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"BSD-3-Clause","inline_ok":true,"mcp_get_code":{"code_sha256":"aac1dd28c8780f75"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}