{"paper":{"title":"ML-based Fast Simulation of FARICH Responses","license":"http://creativecommons.org/licenses/by/4.0/","headline":"A conditional GAN can generate realistic photon hits for the FARICH detector much faster than Monte Carlo methods.","cross_cats":["cs.LG"],"primary_cat":"hep-ex","authors_text":"Alexander Barnyakov, Artem Ivanov, Fedor Ratnikov, Foma Shipilov, Sergey Kononov, Vladimir Bobrovnikov","submitted_at":"2026-05-17T20:06:45Z","abstract_excerpt":"A fast simulation of the detector response is a vital task in high-energy physics (HEP). Traditional Monte-Carlo methods form the backbone of modern particle physics simulation software but are computationally expensive. We present a machine-learning-based approach to fast simulation of the Focusing Aerogel Ring Imaging Cherenkov (FARICH) detector response. Given a particle track and momentum, the goal is to generate realistic samples of photon hits on the detector matrix. We propose a conditional Generative Adversarial Network (cGAN) with a lightweight convolutional architecture that reproduc"},"claims":{"count":4,"items":[{"kind":"strongest_claim","text":"The cGAN produces realistic samples and provides a significant speed-up over Monte-Carlo simulation.","source":"verdict.strongest_claim","status":"machine_extracted","claim_id":"C1","attestation":"unclaimed"},{"kind":"weakest_assumption","text":"That the chosen metrics on probability maps and reconstructed velocity distributions are adequate proxies for the realism needed in downstream physics analyses, without direct comparison to real experimental data.","source":"verdict.weakest_assumption","status":"machine_extracted","claim_id":"C2","attestation":"unclaimed"},{"kind":"one_line_summary","text":"A cGAN generates realistic photon hit samples for the FARICH detector conditioned on particle parameters and outperforms a linear statistical baseline in realism while providing speed-up over Monte Carlo.","source":"verdict.one_line_summary","status":"machine_extracted","claim_id":"C3","attestation":"unclaimed"},{"kind":"headline","text":"A conditional GAN can generate realistic photon hits for the FARICH detector much faster than Monte Carlo methods.","source":"verdict.pith_extraction.headline","status":"machine_extracted","claim_id":"C4","attestation":"unclaimed"}],"snapshot_sha256":"55ffb60adc7315e26c4cb8844a5b26881f84a04e0e79c928b04b084905fafb64"},"source":{"id":"2605.17635","kind":"arxiv","version":1},"verdict":{"id":"bf5fe0a0-ee56-4808-b0f0-4055dc1cec33","model_set":{"reader":"grok-4.3"},"created_at":"2026-05-19T22:06:24.479974Z","strongest_claim":"The cGAN produces realistic samples and provides a significant speed-up over Monte-Carlo simulation.","one_line_summary":"A cGAN generates realistic photon hit samples for the FARICH detector conditioned on particle parameters and outperforms a linear statistical baseline in realism while providing speed-up over Monte Carlo.","pipeline_version":"pith-pipeline@v0.9.0","weakest_assumption":"That the chosen metrics on probability maps and reconstructed velocity distributions are adequate proxies for the realism needed in downstream physics analyses, without direct comparison to real experimental data.","pith_extraction_headline":"A conditional GAN can generate realistic photon hits for the FARICH detector much faster than Monte Carlo methods."},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2605.17635/integrity.json","findings":[],"available":true,"detectors_run":[{"name":"cited_work_retraction","ran_at":"2026-05-19T22:52:43.452799Z","status":"completed","version":"1.0.0","findings_count":0},{"name":"doi_title_agreement","ran_at":"2026-05-19T22:31:19.508472Z","status":"completed","version":"1.0.0","findings_count":0},{"name":"doi_compliance","ran_at":"2026-05-19T22:12:15.471350Z","status":"completed","version":"1.0.0","findings_count":0},{"name":"ai_meta_artifact","ran_at":"2026-05-19T21:33:23.556220Z","status":"skipped","version":"1.0.0","findings_count":0},{"name":"claim_evidence","ran_at":"2026-05-19T21:21:57.479108Z","status":"completed","version":"1.0.0","findings_count":0}],"snapshot_sha256":"ec2d305223800c5c5dee4756851cfc4d539a0a6d5b4b4c933a18dfb1c3c60508"},"references":{"count":27,"sample":[{"doi":"","year":2015,"title":"I. Savin, A. Efremov, D. Peshekhonov, A. Kovalenko, O. Teryaev, O. Shevchenko, A. Nagajcev, A. Guskov, V. Kukhtin and N. Toplilin,Spin physics experiments at nica- spd with polarized proton and deuter","work_id":"242067b4-6461-4ca2-acda-583db8a9aab6","ref_index":1,"cited_arxiv_id":"","is_internal_anchor":false},{"doi":"","year":2021,"title":"V. Abazov, V. Abramov, L. Afanasyev, R. Akhunzyanov, A. Akindinov, N. Akopov, I. Alekseev, A. Aleshko, V. Y. Alexakhin, G. Alexeevet al.,arXiv preprint arXiv:2102.00442(2021)","work_id":"e72499f2-67f8-481c-aa7e-1042c358b49d","ref_index":2,"cited_arxiv_id":"","is_internal_anchor":false},{"doi":"","year":2023,"title":"T. S. Collaboration,Technical design report of the spin physics detector(2023), JINR SPD Collaboration","work_id":"a7517be2-a5c8-4182-b64b-7f439873c2a9","ref_index":3,"cited_arxiv_id":"","is_internal_anchor":false},{"doi":"","year":2023,"title":"Korzenev,Spin physics detector at the nica accelerator complex(2023), Technology & Instrumentation in Particle Physics (TIPP2023)","work_id":"106fda6a-a9a3-4aa2-ad47-a15b2a346312","ref_index":4,"cited_arxiv_id":"","is_internal_anchor":false},{"doi":"","year":2020,"title":"H. Kindo, I. Adachi, L. Burmistrov, F. Le Diberder, K. Hataya, S. Kakimimoto, H. Kakuno, H. Kawai, T. Kawasaki, T. Konno, S. Korpar, P. Kriˇ zan, T. Kumita, Y. Lai, M. Machida, M. Mrvar, S. Nishida, K","work_id":"6080ec2f-0570-4a27-9ab2-fb08df0a0db6","ref_index":5,"cited_arxiv_id":"","is_internal_anchor":false}],"resolved_work":27,"snapshot_sha256":"b222fc4eaa1782914cba19333f7415055dd0fd15299b2177258f5308b6338bc8","internal_anchors":0},"formal_canon":{"evidence_count":1,"snapshot_sha256":"74b7953cb00ff387c087c2080171308bb7c6069eeaf691411b71a07054f62142"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"}