{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:VHKWUCVZEGEURN772HEPFLGN74","short_pith_number":"pith:VHKWUCVZ","canonical_record":{"source":{"id":"2305.03527","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"quant-ph","submitted_at":"2023-05-05T13:33:43Z","cross_cats_sorted":[],"title_canon_sha256":"190c87c4fba44170700f2b952f0da369bfe07af314bed8fd3dbce4f84e3a48b2","abstract_canon_sha256":"4966aed18f4d3e3895591efd9908dfa9fc89ecef5d88b3fd9a555f5ec3383056"},"schema_version":"1.0"},"canonical_sha256":"a9d56a0ab9218948b7ffd1c8f2accdff31dd076877872a12c64fb3d56ab5f233","source":{"kind":"arxiv","id":"2305.03527","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2305.03527","created_at":"2026-07-05T10:54:29Z"},{"alias_kind":"arxiv_version","alias_value":"2305.03527v2","created_at":"2026-07-05T10:54:29Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2305.03527","created_at":"2026-07-05T10:54:29Z"},{"alias_kind":"pith_short_12","alias_value":"VHKWUCVZEGEU","created_at":"2026-07-05T10:54:29Z"},{"alias_kind":"pith_short_16","alias_value":"VHKWUCVZEGEURN77","created_at":"2026-07-05T10:54:29Z"},{"alias_kind":"pith_short_8","alias_value":"VHKWUCVZ","created_at":"2026-07-05T10:54:29Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:VHKWUCVZEGEURN772HEPFLGN74","target":"record","payload":{"canonical_record":{"source":{"id":"2305.03527","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"quant-ph","submitted_at":"2023-05-05T13:33:43Z","cross_cats_sorted":[],"title_canon_sha256":"190c87c4fba44170700f2b952f0da369bfe07af314bed8fd3dbce4f84e3a48b2","abstract_canon_sha256":"4966aed18f4d3e3895591efd9908dfa9fc89ecef5d88b3fd9a555f5ec3383056"},"schema_version":"1.0"},"canonical_sha256":"a9d56a0ab9218948b7ffd1c8f2accdff31dd076877872a12c64fb3d56ab5f233","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:54:29.879700Z","signature_b64":"pLRjh6UJlRp7soaGfscrZzGH5rc97prQTB2uEszKAUVzgLyZU9Se7vZL18uj95Rtk2yxX9N4dTkRSYhdJLE8Dg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a9d56a0ab9218948b7ffd1c8f2accdff31dd076877872a12c64fb3d56ab5f233","last_reissued_at":"2026-07-05T10:54:29.879235Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:54:29.879235Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2305.03527","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":"2026-07-05T10:54:29Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"eSpAAbdivfhgk6ot85TTvmOKtNTGvRHM+2qXrAlcjpqu/q2GlR/+dNYcecM7OgF25inZUNe0folxeJI3vU0XAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-15T16:36:48.777578Z"},"content_sha256":"a43c7034c4bc08607a1ff32d0cf95eaed92248c64ce0b2005a83b2033ead56dd","schema_version":"1.0","event_id":"sha256:a43c7034c4bc08607a1ff32d0cf95eaed92248c64ce0b2005a83b2033ead56dd"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:VHKWUCVZEGEURN772HEPFLGN74","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"ResQNets: A Residual Approach for Mitigating Barren Plateaus in Quantum Neural Networks","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"quant-ph","authors_text":"Muhammad Kashif, Saif Al-Kuwari","submitted_at":"2023-05-05T13:33:43Z","abstract_excerpt":"The barren plateau problem in quantum neural networks (QNNs) is a significant challenge that hinders the practical success of QNNs. In this paper, we introduce residual quantum neural networks (ResQNets) as a solution to address this problem. ResQNets are inspired by classical residual neural networks and involve splitting the conventional QNN architecture into multiple quantum nodes, each containing its own parameterized quantum circuit, and introducing residual connections between these nodes. Our study demonstrates the efficacy of ResQNets by comparing their performance with that of convent"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2305.03527","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/2305.03527/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":"2026-07-05T10:54:29Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"F6QFRXC1RcDOge5Fqk59Eq53pY7AFa3OeiYkXElWjRs5SH/mlY5XscxF4U6AFPrJKynZcAFGh95drOE+tbkSDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-15T16:36:48.778513Z"},"content_sha256":"2085eaacbb76b9319aa0bfb5dffdc72c3245ed470d630d5e6d8d1d3e2ecc7360","schema_version":"1.0","event_id":"sha256:2085eaacbb76b9319aa0bfb5dffdc72c3245ed470d630d5e6d8d1d3e2ecc7360"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/VHKWUCVZEGEURN772HEPFLGN74/bundle.json","state_url":"https://pith.science/pith/VHKWUCVZEGEURN772HEPFLGN74/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/VHKWUCVZEGEURN772HEPFLGN74/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":"2026-08-15T16:36:48Z","links":{"resolver":"https://pith.science/pith/VHKWUCVZEGEURN772HEPFLGN74","bundle":"https://pith.science/pith/VHKWUCVZEGEURN772HEPFLGN74/bundle.json","state":"https://pith.science/pith/VHKWUCVZEGEURN772HEPFLGN74/state.json","well_known_bundle":"https://pith.science/.well-known/pith/VHKWUCVZEGEURN772HEPFLGN74/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:VHKWUCVZEGEURN772HEPFLGN74","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":"4966aed18f4d3e3895591efd9908dfa9fc89ecef5d88b3fd9a555f5ec3383056","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"quant-ph","submitted_at":"2023-05-05T13:33:43Z","title_canon_sha256":"190c87c4fba44170700f2b952f0da369bfe07af314bed8fd3dbce4f84e3a48b2"},"schema_version":"1.0","source":{"id":"2305.03527","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2305.03527","created_at":"2026-07-05T10:54:29Z"},{"alias_kind":"arxiv_version","alias_value":"2305.03527v2","created_at":"2026-07-05T10:54:29Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2305.03527","created_at":"2026-07-05T10:54:29Z"},{"alias_kind":"pith_short_12","alias_value":"VHKWUCVZEGEU","created_at":"2026-07-05T10:54:29Z"},{"alias_kind":"pith_short_16","alias_value":"VHKWUCVZEGEURN77","created_at":"2026-07-05T10:54:29Z"},{"alias_kind":"pith_short_8","alias_value":"VHKWUCVZ","created_at":"2026-07-05T10:54:29Z"}],"graph_snapshots":[{"event_id":"sha256:2085eaacbb76b9319aa0bfb5dffdc72c3245ed470d630d5e6d8d1d3e2ecc7360","target":"graph","created_at":"2026-07-05T10:54:29Z","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/2305.03527/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The barren plateau problem in quantum neural networks (QNNs) is a significant challenge that hinders the practical success of QNNs. In this paper, we introduce residual quantum neural networks (ResQNets) as a solution to address this problem. ResQNets are inspired by classical residual neural networks and involve splitting the conventional QNN architecture into multiple quantum nodes, each containing its own parameterized quantum circuit, and introducing residual connections between these nodes. Our study demonstrates the efficacy of ResQNets by comparing their performance with that of convent","authors_text":"Muhammad Kashif, Saif Al-Kuwari","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"quant-ph","submitted_at":"2023-05-05T13:33:43Z","title":"ResQNets: A Residual Approach for Mitigating Barren Plateaus in Quantum Neural Networks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2305.03527","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:a43c7034c4bc08607a1ff32d0cf95eaed92248c64ce0b2005a83b2033ead56dd","target":"record","created_at":"2026-07-05T10:54:29Z","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":"4966aed18f4d3e3895591efd9908dfa9fc89ecef5d88b3fd9a555f5ec3383056","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"quant-ph","submitted_at":"2023-05-05T13:33:43Z","title_canon_sha256":"190c87c4fba44170700f2b952f0da369bfe07af314bed8fd3dbce4f84e3a48b2"},"schema_version":"1.0","source":{"id":"2305.03527","kind":"arxiv","version":2}},"canonical_sha256":"a9d56a0ab9218948b7ffd1c8f2accdff31dd076877872a12c64fb3d56ab5f233","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a9d56a0ab9218948b7ffd1c8f2accdff31dd076877872a12c64fb3d56ab5f233","first_computed_at":"2026-07-05T10:54:29.879235Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:54:29.879235Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"pLRjh6UJlRp7soaGfscrZzGH5rc97prQTB2uEszKAUVzgLyZU9Se7vZL18uj95Rtk2yxX9N4dTkRSYhdJLE8Dg==","signature_status":"signed_v1","signed_at":"2026-07-05T10:54:29.879700Z","signed_message":"canonical_sha256_bytes"},"source_id":"2305.03527","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a43c7034c4bc08607a1ff32d0cf95eaed92248c64ce0b2005a83b2033ead56dd","sha256:2085eaacbb76b9319aa0bfb5dffdc72c3245ed470d630d5e6d8d1d3e2ecc7360"],"state_sha256":"648b5ff59d86a95fffb10dade90e384f6a330dd0985c319f5997829ab5a9412a"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"aLAZK8U4cUhh2g01HXH93bOA/OG5QVB97tur0e6JvvgJKQp4On7Nd9Y2euzR+Uh4ehujM+rwqRefvA7BgK0/Bw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-15T16:36:48.784847Z","bundle_sha256":"8665f9d825c34ae1627946fff437c286d2257483e72b50a61dffddaa7eb85271"}}