{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:63UATL33R36INIACYPJSZWF3V6","short_pith_number":"pith:63UATL33","canonical_record":{"source":{"id":"1810.11509","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"hep-ph","submitted_at":"2018-10-26T19:13:33Z","cross_cats_sorted":["hep-ex","physics.comp-ph","stat.ML"],"title_canon_sha256":"62387440758cff50cf11346bebebb56d07849a24bcdd5e4fe2c5f6f7610dce93","abstract_canon_sha256":"0ccedb7f68bf649d55e8f4980b92ce26bac61371dd006193d3854eee3997c168"},"schema_version":"1.0"},"canonical_sha256":"f6e809af7b8efc86a002c3d32cd8bbafb0a336111d767873ceb8cad477f83bc3","source":{"kind":"arxiv","id":"1810.11509","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1810.11509","created_at":"2026-07-05T01:44:36Z"},{"alias_kind":"arxiv_version","alias_value":"1810.11509v3","created_at":"2026-07-05T01:44:36Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1810.11509","created_at":"2026-07-05T01:44:36Z"},{"alias_kind":"pith_short_12","alias_value":"63UATL33R36I","created_at":"2026-07-05T01:44:36Z"},{"alias_kind":"pith_short_16","alias_value":"63UATL33R36INIAC","created_at":"2026-07-05T01:44:36Z"},{"alias_kind":"pith_short_8","alias_value":"63UATL33","created_at":"2026-07-05T01:44:36Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:63UATL33R36INIACYPJSZWF3V6","target":"record","payload":{"canonical_record":{"source":{"id":"1810.11509","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"hep-ph","submitted_at":"2018-10-26T19:13:33Z","cross_cats_sorted":["hep-ex","physics.comp-ph","stat.ML"],"title_canon_sha256":"62387440758cff50cf11346bebebb56d07849a24bcdd5e4fe2c5f6f7610dce93","abstract_canon_sha256":"0ccedb7f68bf649d55e8f4980b92ce26bac61371dd006193d3854eee3997c168"},"schema_version":"1.0"},"canonical_sha256":"f6e809af7b8efc86a002c3d32cd8bbafb0a336111d767873ceb8cad477f83bc3","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T01:44:36.326538Z","signature_b64":"qB4UHhBquz7aRAXqbjNXwkBy8HXJRFaSyhS+bIaPdWRwfyKEYFxMP+08x63KT4H6ViRWOzN+BSn8uxPqGvvqDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f6e809af7b8efc86a002c3d32cd8bbafb0a336111d767873ceb8cad477f83bc3","last_reissued_at":"2026-07-05T01:44:36.326084Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T01:44:36.326084Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1810.11509","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T01:44:36Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"u8lYYubE5ASiXay4dXvTVDGgJFANyCH+GEP/ejoaVQl3IKeh5zx6RFZct8WpjQpW9fYHqSXl+h9ZU7mkUvWxBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-12T16:06:49.127787Z"},"content_sha256":"bffd4c0947909afb168dffa206bb524494c15b469f7d3e7f8f74c6bd2779b585","schema_version":"1.0","event_id":"sha256:bffd4c0947909afb168dffa206bb524494c15b469f7d3e7f8f74c6bd2779b585"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:63UATL33R36INIACYPJSZWF3V6","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Neural Network-Based Approach to Phase Space Integration","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["hep-ex","physics.comp-ph","stat.ML"],"primary_cat":"hep-ph","authors_text":"Matthew D. Klimek, Maxim Perelstein","submitted_at":"2018-10-26T19:13:33Z","abstract_excerpt":"Monte Carlo methods are widely used in particle physics to integrate and sample probability distributions (differential cross sections or decay rates) on multi-dimensional phase spaces. We present a Neural Network (NN) algorithm optimized to perform this task. The algorithm has been applied to several examples of direct relevance for particle physics, including situations with non-trivial features such as sharp resonances and soft/collinear enhancements. Excellent performance has been demonstrated in all examples, with the properly trained NN achieving unweighting efficiencies of between 30% a"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1810.11509","kind":"arxiv","version":3},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/1810.11509/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T01:44:36Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"9COI7/enlPpuQ8EbLWCDX/hJUdcwbWR3nS+uizoA0ZEXqUSWVQZdO5P8h3D4BC9gFKGNLps6f1+q2ME8MQpZDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-12T16:06:49.128709Z"},"content_sha256":"81f138f54200530c4abafa44b16a5dd24cb9ce6ccb7aab3ca90e39270403a243","schema_version":"1.0","event_id":"sha256:81f138f54200530c4abafa44b16a5dd24cb9ce6ccb7aab3ca90e39270403a243"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/63UATL33R36INIACYPJSZWF3V6/bundle.json","state_url":"https://pith.science/pith/63UATL33R36INIACYPJSZWF3V6/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/63UATL33R36INIACYPJSZWF3V6/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-12T16:06:49Z","links":{"resolver":"https://pith.science/pith/63UATL33R36INIACYPJSZWF3V6","bundle":"https://pith.science/pith/63UATL33R36INIACYPJSZWF3V6/bundle.json","state":"https://pith.science/pith/63UATL33R36INIACYPJSZWF3V6/state.json","well_known_bundle":"https://pith.science/.well-known/pith/63UATL33R36INIACYPJSZWF3V6/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:63UATL33R36INIACYPJSZWF3V6","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":"0ccedb7f68bf649d55e8f4980b92ce26bac61371dd006193d3854eee3997c168","cross_cats_sorted":["hep-ex","physics.comp-ph","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"hep-ph","submitted_at":"2018-10-26T19:13:33Z","title_canon_sha256":"62387440758cff50cf11346bebebb56d07849a24bcdd5e4fe2c5f6f7610dce93"},"schema_version":"1.0","source":{"id":"1810.11509","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1810.11509","created_at":"2026-07-05T01:44:36Z"},{"alias_kind":"arxiv_version","alias_value":"1810.11509v3","created_at":"2026-07-05T01:44:36Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1810.11509","created_at":"2026-07-05T01:44:36Z"},{"alias_kind":"pith_short_12","alias_value":"63UATL33R36I","created_at":"2026-07-05T01:44:36Z"},{"alias_kind":"pith_short_16","alias_value":"63UATL33R36INIAC","created_at":"2026-07-05T01:44:36Z"},{"alias_kind":"pith_short_8","alias_value":"63UATL33","created_at":"2026-07-05T01:44:36Z"}],"graph_snapshots":[{"event_id":"sha256:81f138f54200530c4abafa44b16a5dd24cb9ce6ccb7aab3ca90e39270403a243","target":"graph","created_at":"2026-07-05T01:44:36Z","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":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/1810.11509/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Monte Carlo methods are widely used in particle physics to integrate and sample probability distributions (differential cross sections or decay rates) on multi-dimensional phase spaces. We present a Neural Network (NN) algorithm optimized to perform this task. The algorithm has been applied to several examples of direct relevance for particle physics, including situations with non-trivial features such as sharp resonances and soft/collinear enhancements. Excellent performance has been demonstrated in all examples, with the properly trained NN achieving unweighting efficiencies of between 30% a","authors_text":"Matthew D. Klimek, Maxim Perelstein","cross_cats":["hep-ex","physics.comp-ph","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"hep-ph","submitted_at":"2018-10-26T19:13:33Z","title":"Neural Network-Based Approach to Phase Space Integration"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1810.11509","kind":"arxiv","version":3},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:bffd4c0947909afb168dffa206bb524494c15b469f7d3e7f8f74c6bd2779b585","target":"record","created_at":"2026-07-05T01:44:36Z","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":"0ccedb7f68bf649d55e8f4980b92ce26bac61371dd006193d3854eee3997c168","cross_cats_sorted":["hep-ex","physics.comp-ph","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"hep-ph","submitted_at":"2018-10-26T19:13:33Z","title_canon_sha256":"62387440758cff50cf11346bebebb56d07849a24bcdd5e4fe2c5f6f7610dce93"},"schema_version":"1.0","source":{"id":"1810.11509","kind":"arxiv","version":3}},"canonical_sha256":"f6e809af7b8efc86a002c3d32cd8bbafb0a336111d767873ceb8cad477f83bc3","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"f6e809af7b8efc86a002c3d32cd8bbafb0a336111d767873ceb8cad477f83bc3","first_computed_at":"2026-07-05T01:44:36.326084Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T01:44:36.326084Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"qB4UHhBquz7aRAXqbjNXwkBy8HXJRFaSyhS+bIaPdWRwfyKEYFxMP+08x63KT4H6ViRWOzN+BSn8uxPqGvvqDw==","signature_status":"signed_v1","signed_at":"2026-07-05T01:44:36.326538Z","signed_message":"canonical_sha256_bytes"},"source_id":"1810.11509","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:bffd4c0947909afb168dffa206bb524494c15b469f7d3e7f8f74c6bd2779b585","sha256:81f138f54200530c4abafa44b16a5dd24cb9ce6ccb7aab3ca90e39270403a243"],"state_sha256":"c532198d3199a5803f3d2469edea4e1e8645cb0a2437d3b05915040301bc1ece"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"29wye78cFQgdBrvBLrgwnUVJwG5Wx1z0sNBYNSUQmnrR8F2k60uuQZPfJK7XrIHSZmQgeOHA7o5Uj8ACMsbVCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-12T16:06:49.135023Z","bundle_sha256":"33c35c0c9789710dea1621793ce2f7fa7ebd4094a8715ae9d75b1189d5ccec17"}}