{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:DWAAL2CVQ32WZWWH6IAROFSNJ7","short_pith_number":"pith:DWAAL2CV","canonical_record":{"source":{"id":"2506.01177","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-06-01T21:24:43Z","cross_cats_sorted":["cs.AI","q-bio.BM"],"title_canon_sha256":"116c6405ca9ccd4304f39ca48419b150b454af39073843f873992350dc09e43e","abstract_canon_sha256":"59adaf7e1fd2344b273ebeadb911cdb0921ecb9848e54c812ff675eb9dd0ce4f"},"schema_version":"1.0"},"canonical_sha256":"1d8005e85586f56cdac7f20117164d4fc72e7438a65f82c0814822a3ccbfad50","source":{"kind":"arxiv","id":"2506.01177","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2506.01177","created_at":"2026-07-05T11:43:12Z"},{"alias_kind":"arxiv_version","alias_value":"2506.01177v2","created_at":"2026-07-05T11:43:12Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.01177","created_at":"2026-07-05T11:43:12Z"},{"alias_kind":"pith_short_12","alias_value":"DWAAL2CVQ32W","created_at":"2026-07-05T11:43:12Z"},{"alias_kind":"pith_short_16","alias_value":"DWAAL2CVQ32WZWWH","created_at":"2026-07-05T11:43:12Z"},{"alias_kind":"pith_short_8","alias_value":"DWAAL2CV","created_at":"2026-07-05T11:43:12Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:DWAAL2CVQ32WZWWH6IAROFSNJ7","target":"record","payload":{"canonical_record":{"source":{"id":"2506.01177","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-06-01T21:24:43Z","cross_cats_sorted":["cs.AI","q-bio.BM"],"title_canon_sha256":"116c6405ca9ccd4304f39ca48419b150b454af39073843f873992350dc09e43e","abstract_canon_sha256":"59adaf7e1fd2344b273ebeadb911cdb0921ecb9848e54c812ff675eb9dd0ce4f"},"schema_version":"1.0"},"canonical_sha256":"1d8005e85586f56cdac7f20117164d4fc72e7438a65f82c0814822a3ccbfad50","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:43:12.384713Z","signature_b64":"icbG8TvqLBevsoPdPuxeIC2yFjeedrXTHgtNsvped9h++FCgNyvYmbidsp7BCi3VV6PlEx5dvziLyvcdy+pnBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"1d8005e85586f56cdac7f20117164d4fc72e7438a65f82c0814822a3ccbfad50","last_reissued_at":"2026-07-05T11:43:12.384160Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:43:12.384160Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2506.01177","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:43:12Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"4yddQV7EzAP+dJMeeD2InIXEuaa2EEXPeEPXbNQtB65C4ArcNS071fjyfaRkW26uB73aZeT/fbNtpXziVfA8Cw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T04:26:23.274721Z"},"content_sha256":"76db311da6d9d9d1072d96fbf5022e5e3a38862e3387733b69d65be0c6204734","schema_version":"1.0","event_id":"sha256:76db311da6d9d9d1072d96fbf5022e5e3a38862e3387733b69d65be0c6204734"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:DWAAL2CVQ32WZWWH6IAROFSNJ7","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Bridging Quantum and Classical Computing in Drug Design: Architecture Principles for Improved Molecule Generation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","q-bio.BM"],"primary_cat":"cs.LG","authors_text":"Andrew Smith, Erhan Guven","submitted_at":"2025-06-01T21:24:43Z","abstract_excerpt":"Hybrid quantum-classical machine learning offers a path to leverage noisy intermediate-scale quantum (NISQ) devices for drug discovery, but optimal model architectures remain unclear. We systematically optimize the quantum-classical bridge architecture of generative adversarial networks (GANs) for molecule discovery using multi-objective Bayesian optimization. Our optimized model (BO-QGAN) significantly improves performance, achieving a 2.27-fold higher Drug Candidate Score (DCS) than prior quantum-hybrid benchmarks and 2.21-fold higher than the classical baseline, while reducing parameter cou"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.01177","kind":"arxiv","version":2},"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/2506.01177/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":"2026-07-05T11:43:12Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"1WD1EC5xiGzOKUdFqnSA6sDvhIhbu/Eis3tjFExuv42da0GqI8mPs01ajc9w3OvTNaTA7GMGdA3EjtXf1/gIAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T04:26:23.275624Z"},"content_sha256":"7ebed6d1158a6f7cdf7aeb30c39ae7072ebb3774908490150e8b641fea1309c9","schema_version":"1.0","event_id":"sha256:7ebed6d1158a6f7cdf7aeb30c39ae7072ebb3774908490150e8b641fea1309c9"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/DWAAL2CVQ32WZWWH6IAROFSNJ7/bundle.json","state_url":"https://pith.science/pith/DWAAL2CVQ32WZWWH6IAROFSNJ7/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/DWAAL2CVQ32WZWWH6IAROFSNJ7/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":"2026-08-08T04:26:23Z","links":{"resolver":"https://pith.science/pith/DWAAL2CVQ32WZWWH6IAROFSNJ7","bundle":"https://pith.science/pith/DWAAL2CVQ32WZWWH6IAROFSNJ7/bundle.json","state":"https://pith.science/pith/DWAAL2CVQ32WZWWH6IAROFSNJ7/state.json","well_known_bundle":"https://pith.science/.well-known/pith/DWAAL2CVQ32WZWWH6IAROFSNJ7/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:DWAAL2CVQ32WZWWH6IAROFSNJ7","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":"59adaf7e1fd2344b273ebeadb911cdb0921ecb9848e54c812ff675eb9dd0ce4f","cross_cats_sorted":["cs.AI","q-bio.BM"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-06-01T21:24:43Z","title_canon_sha256":"116c6405ca9ccd4304f39ca48419b150b454af39073843f873992350dc09e43e"},"schema_version":"1.0","source":{"id":"2506.01177","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2506.01177","created_at":"2026-07-05T11:43:12Z"},{"alias_kind":"arxiv_version","alias_value":"2506.01177v2","created_at":"2026-07-05T11:43:12Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.01177","created_at":"2026-07-05T11:43:12Z"},{"alias_kind":"pith_short_12","alias_value":"DWAAL2CVQ32W","created_at":"2026-07-05T11:43:12Z"},{"alias_kind":"pith_short_16","alias_value":"DWAAL2CVQ32WZWWH","created_at":"2026-07-05T11:43:12Z"},{"alias_kind":"pith_short_8","alias_value":"DWAAL2CV","created_at":"2026-07-05T11:43:12Z"}],"graph_snapshots":[{"event_id":"sha256:7ebed6d1158a6f7cdf7aeb30c39ae7072ebb3774908490150e8b641fea1309c9","target":"graph","created_at":"2026-07-05T11:43:12Z","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/2506.01177/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Hybrid quantum-classical machine learning offers a path to leverage noisy intermediate-scale quantum (NISQ) devices for drug discovery, but optimal model architectures remain unclear. We systematically optimize the quantum-classical bridge architecture of generative adversarial networks (GANs) for molecule discovery using multi-objective Bayesian optimization. Our optimized model (BO-QGAN) significantly improves performance, achieving a 2.27-fold higher Drug Candidate Score (DCS) than prior quantum-hybrid benchmarks and 2.21-fold higher than the classical baseline, while reducing parameter cou","authors_text":"Andrew Smith, Erhan Guven","cross_cats":["cs.AI","q-bio.BM"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-06-01T21:24:43Z","title":"Bridging Quantum and Classical Computing in Drug Design: Architecture Principles for Improved Molecule Generation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.01177","kind":"arxiv","version":2},"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":"sha256:76db311da6d9d9d1072d96fbf5022e5e3a38862e3387733b69d65be0c6204734","target":"record","created_at":"2026-07-05T11:43:12Z","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":"59adaf7e1fd2344b273ebeadb911cdb0921ecb9848e54c812ff675eb9dd0ce4f","cross_cats_sorted":["cs.AI","q-bio.BM"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-06-01T21:24:43Z","title_canon_sha256":"116c6405ca9ccd4304f39ca48419b150b454af39073843f873992350dc09e43e"},"schema_version":"1.0","source":{"id":"2506.01177","kind":"arxiv","version":2}},"canonical_sha256":"1d8005e85586f56cdac7f20117164d4fc72e7438a65f82c0814822a3ccbfad50","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"1d8005e85586f56cdac7f20117164d4fc72e7438a65f82c0814822a3ccbfad50","first_computed_at":"2026-07-05T11:43:12.384160Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:43:12.384160Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"icbG8TvqLBevsoPdPuxeIC2yFjeedrXTHgtNsvped9h++FCgNyvYmbidsp7BCi3VV6PlEx5dvziLyvcdy+pnBw==","signature_status":"signed_v1","signed_at":"2026-07-05T11:43:12.384713Z","signed_message":"canonical_sha256_bytes"},"source_id":"2506.01177","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:76db311da6d9d9d1072d96fbf5022e5e3a38862e3387733b69d65be0c6204734","sha256:7ebed6d1158a6f7cdf7aeb30c39ae7072ebb3774908490150e8b641fea1309c9"],"state_sha256":"cab45c9c059983ff6ce36192be6ea06ed04d5139c0beba802257fdb6284ac577"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"9B2GG3P/TEwagW1CMaj+SiIAlq2u1DloAl1EJp5MOlx9hLv9a7xeOUQeJh3ct7MWmnNpVsKdbla9EnBHm7K1AA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-08T04:26:23.282762Z","bundle_sha256":"7a8cca80e1314a4e0ad1780839ed438f5d0a19581493f366d49e6666935b82c3"}}