{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:3AF3DBYVWXRL4QBLHTHOS37FQM","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"54197c8e8e780b4d417ca739809675760306843819befb9639834a0cd0481821","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"hep-ex","submitted_at":"2026-05-17T20:06:45Z","title_canon_sha256":"b1a0cfd704697b7ae334df8e544c0de0989b15a062c188259784398d104ec0bc"},"schema_version":"1.0","source":{"id":"2605.17635","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.17635","created_at":"2026-05-20T00:04:49Z"},{"alias_kind":"arxiv_version","alias_value":"2605.17635v1","created_at":"2026-05-20T00:04:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.17635","created_at":"2026-05-20T00:04:49Z"},{"alias_kind":"pith_short_12","alias_value":"3AF3DBYVWXRL","created_at":"2026-05-20T00:04:49Z"},{"alias_kind":"pith_short_16","alias_value":"3AF3DBYVWXRL4QBL","created_at":"2026-05-20T00:04:49Z"},{"alias_kind":"pith_short_8","alias_value":"3AF3DBYV","created_at":"2026-05-20T00:04:49Z"}],"graph_snapshots":[{"event_id":"sha256:2ee710e2d3aa516c48116f0cfe93de0250b583b2b28315d469e988bcca8229f8","target":"graph","created_at":"2026-05-20T00:04:49Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":4,"items":[{"attestation":"unclaimed","claim_id":"C1","kind":"strongest_claim","source":"verdict.strongest_claim","status":"machine_extracted","text":"The cGAN produces realistic samples and provides a significant speed-up over Monte-Carlo simulation."},{"attestation":"unclaimed","claim_id":"C2","kind":"weakest_assumption","source":"verdict.weakest_assumption","status":"machine_extracted","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."},{"attestation":"unclaimed","claim_id":"C3","kind":"one_line_summary","source":"verdict.one_line_summary","status":"machine_extracted","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."},{"attestation":"unclaimed","claim_id":"C4","kind":"headline","source":"verdict.pith_extraction.headline","status":"machine_extracted","text":"A conditional GAN can generate realistic photon hits for the FARICH detector much faster than Monte Carlo methods."}],"snapshot_sha256":"55ffb60adc7315e26c4cb8844a5b26881f84a04e0e79c928b04b084905fafb64"},"formal_canon":{"evidence_count":1,"snapshot_sha256":"74b7953cb00ff387c087c2080171308bb7c6069eeaf691411b71a07054f62142"},"integrity":{"available":true,"clean":true,"detectors_run":[{"findings_count":0,"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"}],"endpoint":"/pith/2605.17635/integrity.json","findings":[],"snapshot_sha256":"ec2d305223800c5c5dee4756851cfc4d539a0a6d5b4b4c933a18dfb1c3c60508","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"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","authors_text":"Alexander Barnyakov, Artem Ivanov, Fedor Ratnikov, Foma Shipilov, Sergey Kononov, Vladimir Bobrovnikov","cross_cats":["cs.LG"],"headline":"A conditional GAN can generate realistic photon hits for the FARICH detector much faster than Monte Carlo methods.","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"hep-ex","submitted_at":"2026-05-17T20:06:45Z","title":"ML-based Fast Simulation of FARICH Responses"},"references":{"count":27,"internal_anchors":0,"resolved_work":27,"sample":[{"cited_arxiv_id":"","doi":"","is_internal_anchor":false,"ref_index":1,"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","year":2015},{"cited_arxiv_id":"","doi":"","is_internal_anchor":false,"ref_index":2,"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","year":2021},{"cited_arxiv_id":"","doi":"","is_internal_anchor":false,"ref_index":3,"title":"T. S. Collaboration,Technical design report of the spin physics detector(2023), JINR SPD Collaboration","work_id":"a7517be2-a5c8-4182-b64b-7f439873c2a9","year":2023},{"cited_arxiv_id":"","doi":"","is_internal_anchor":false,"ref_index":4,"title":"Korzenev,Spin physics detector at the nica accelerator complex(2023), Technology & Instrumentation in Particle Physics (TIPP2023)","work_id":"106fda6a-a9a3-4aa2-ad47-a15b2a346312","year":2023},{"cited_arxiv_id":"","doi":"","is_internal_anchor":false,"ref_index":5,"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","year":2020}],"snapshot_sha256":"b222fc4eaa1782914cba19333f7415055dd0fd15299b2177258f5308b6338bc8"},"source":{"id":"2605.17635","kind":"arxiv","version":1},"verdict":{"created_at":"2026-05-19T22:06:24.479974Z","id":"bf5fe0a0-ee56-4808-b0f0-4055dc1cec33","model_set":{"reader":"grok-4.3"},"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","pith_extraction_headline":"A conditional GAN can generate realistic photon hits for the FARICH detector much faster than Monte Carlo methods.","strongest_claim":"The cGAN produces realistic samples and provides a significant speed-up over Monte-Carlo simulation.","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."}},"verdict_id":"bf5fe0a0-ee56-4808-b0f0-4055dc1cec33"}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:aeb8129cce74d464614fabdb4040f6f2ebd4bf557b7ad70562722d1615c2adde","target":"record","created_at":"2026-05-20T00:04:49Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"54197c8e8e780b4d417ca739809675760306843819befb9639834a0cd0481821","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"hep-ex","submitted_at":"2026-05-17T20:06:45Z","title_canon_sha256":"b1a0cfd704697b7ae334df8e544c0de0989b15a062c188259784398d104ec0bc"},"schema_version":"1.0","source":{"id":"2605.17635","kind":"arxiv","version":1}},"canonical_sha256":"d80bb18715b5e2be402b3ccee96fe5831b597c7826366dd4dccf7e3a8df6452d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d80bb18715b5e2be402b3ccee96fe5831b597c7826366dd4dccf7e3a8df6452d","first_computed_at":"2026-05-20T00:04:49.748970Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-20T00:04:49.748970Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ONXsNXe2Aet/WgeRcYwhNrB9/9GOsVGR3g3SJmCkBRXEBVIxfUhGuXX8fVXsomO5ir8B6rZ4iQHvC7mV1pUmAA==","signature_status":"signed_v1","signed_at":"2026-05-20T00:04:49.749784Z","signed_message":"canonical_sha256_bytes"},"source_id":"2605.17635","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:aeb8129cce74d464614fabdb4040f6f2ebd4bf557b7ad70562722d1615c2adde","sha256:2ee710e2d3aa516c48116f0cfe93de0250b583b2b28315d469e988bcca8229f8"],"state_sha256":"12355366e6f96dc77ab20fa0769c4c5313f91c7e5ea360f11670735daced5290"}