{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:DGBTVKXTAXMI5XJHSR6EHCNNIS","short_pith_number":"pith:DGBTVKXT","canonical_record":{"source":{"id":"2604.26477","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"quant-ph","submitted_at":"2026-04-29T09:41:01Z","cross_cats_sorted":[],"title_canon_sha256":"8037aeb403b3ebbb4c0c18d1fc0882b008c3ff178cf6404f4b6b46eb721644dc","abstract_canon_sha256":"6ad01081a5f4a92b7b7fe4a37faade7ae4c205570e6bb75414e57576adf3d94c"},"schema_version":"1.0"},"canonical_sha256":"19833aaaf305d88edd27947c4389ad44be1895504630adbc7e9793278947880f","source":{"kind":"arxiv","id":"2604.26477","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2604.26477","created_at":"2026-05-21T01:04:26Z"},{"alias_kind":"arxiv_version","alias_value":"2604.26477v2","created_at":"2026-05-21T01:04:26Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2604.26477","created_at":"2026-05-21T01:04:26Z"},{"alias_kind":"pith_short_12","alias_value":"DGBTVKXTAXMI","created_at":"2026-05-21T01:04:26Z"},{"alias_kind":"pith_short_16","alias_value":"DGBTVKXTAXMI5XJH","created_at":"2026-05-21T01:04:26Z"},{"alias_kind":"pith_short_8","alias_value":"DGBTVKXT","created_at":"2026-05-21T01:04:26Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:DGBTVKXTAXMI5XJHSR6EHCNNIS","target":"record","payload":{"canonical_record":{"source":{"id":"2604.26477","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"quant-ph","submitted_at":"2026-04-29T09:41:01Z","cross_cats_sorted":[],"title_canon_sha256":"8037aeb403b3ebbb4c0c18d1fc0882b008c3ff178cf6404f4b6b46eb721644dc","abstract_canon_sha256":"6ad01081a5f4a92b7b7fe4a37faade7ae4c205570e6bb75414e57576adf3d94c"},"schema_version":"1.0"},"canonical_sha256":"19833aaaf305d88edd27947c4389ad44be1895504630adbc7e9793278947880f","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-21T01:04:26.473569Z","signature_b64":"BZoi513nsDQz7bVEnkJyUjBMcrMInHWf/Y2FoicUDkXecGhsvYeIVHepJ6ahJm0uOfrARw5Y7QtgJiGSLoB9Dw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"19833aaaf305d88edd27947c4389ad44be1895504630adbc7e9793278947880f","last_reissued_at":"2026-05-21T01:04:26.472809Z","signature_status":"signed_v1","first_computed_at":"2026-05-21T01:04:26.472809Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2604.26477","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":"2026-05-21T01:04:26Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"qff8OvwEUasFTMsQSYqADwYNHzMfO8B5y1AFcLMQ5lEJpIncZWjDx++9S8CXxSi+h2VfxHW/BmOZoR+zzgYWDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-28T07:00:55.222410Z"},"content_sha256":"ea51bff6d824fd404ed39084d4692ca6879912ec2b1a3df997f6146800a4a9a5","schema_version":"1.0","event_id":"sha256:ea51bff6d824fd404ed39084d4692ca6879912ec2b1a3df997f6146800a4a9a5"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:DGBTVKXTAXMI5XJHSR6EHCNNIS","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Multi-Objective Optimization by Quantum-Annealing-Inspired Algorithms","license":"http://creativecommons.org/licenses/by/4.0/","headline":"Quantum-annealing-inspired algorithms on classical GPUs outperform quantum processors and leading classical solvers on multi-objective MaxCut problems.","cross_cats":[],"primary_cat":"quant-ph","authors_text":"Man-Hong Yung, Pavel Mosharev, Xian-Zhe Tao","submitted_at":"2026-04-29T09:41:01Z","abstract_excerpt":"Combinatorial optimization is widely regarded as a primary application for near-term quantum processors, although a definitive demonstration of the practical quantum advantage remains elusive. Recent studies have reported that both gate-based quantum circuits and quantum annealers can outperform state-of-the-art classical heuristics on multi-objective optimization (MO-MaxCut) problems. However, these studies did not fully account for the substantial pre- and post-processing overheads intrinsic to quantum solvers, leading to incomplete comparisons between quantum and classical approaches. In th"},"claims":{"count":4,"items":[{"kind":"strongest_claim","text":"Our results show that QAIAs can sample candidate solutions approximately two orders of magnitude faster than previously studied quantum processors. In terms of end-to-end runtime, QAIAs also surpass industry-leading classical solvers, thereby establishing themselves as the superior performers among the quantum and classical solvers evaluated thus far for the MO-MaxCut instances.","source":"verdict.strongest_claim","status":"machine_extracted","claim_id":"C1","attestation":"unclaimed"},{"kind":"weakest_assumption","text":"That the chosen benchmark suite and the way pre- and post-processing overheads are measured for both quantum and classical solvers produce a fair, unbiased comparison without hidden selection effects or incomplete accounting.","source":"verdict.weakest_assumption","status":"machine_extracted","claim_id":"C2","attestation":"unclaimed"},{"kind":"one_line_summary","text":"GPU-based quantum-annealing-inspired algorithms outperform both quantum processors and industry-leading classical solvers in end-to-end runtime on MO-MaxCut benchmarks.","source":"verdict.one_line_summary","status":"machine_extracted","claim_id":"C3","attestation":"unclaimed"},{"kind":"headline","text":"Quantum-annealing-inspired algorithms on classical GPUs outperform quantum processors and leading classical solvers on multi-objective MaxCut problems.","source":"verdict.pith_extraction.headline","status":"machine_extracted","claim_id":"C4","attestation":"unclaimed"}],"snapshot_sha256":"0c99293278e43641f6369d14cc0ada046e5362553eb941df034d05d8eacde21c"},"source":{"id":"2604.26477","kind":"arxiv","version":2},"verdict":{"id":"024e0a00-13ac-4962-975b-beb7852296d6","model_set":{"reader":"grok-4.3"},"created_at":"2026-05-07T11:19:21.533468Z","strongest_claim":"Our results show that QAIAs can sample candidate solutions approximately two orders of magnitude faster than previously studied quantum processors. In terms of end-to-end runtime, QAIAs also surpass industry-leading classical solvers, thereby establishing themselves as the superior performers among the quantum and classical solvers evaluated thus far for the MO-MaxCut instances.","one_line_summary":"GPU-based quantum-annealing-inspired algorithms outperform both quantum processors and industry-leading classical solvers in end-to-end runtime on MO-MaxCut benchmarks.","pipeline_version":"pith-pipeline@v0.9.0","weakest_assumption":"That the chosen benchmark suite and the way pre- and post-processing overheads are measured for both quantum and classical solvers produce a fair, unbiased comparison without hidden selection effects or incomplete accounting.","pith_extraction_headline":"Quantum-annealing-inspired algorithms on classical GPUs outperform quantum processors and leading classical solvers on multi-objective MaxCut problems."},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2604.26477/integrity.json","findings":[],"available":true,"detectors_run":[{"name":"ai_meta_artifact","ran_at":"2026-05-21T00:34:30.612951Z","status":"completed","version":"1.0.0","findings_count":0},{"name":"doi_compliance","ran_at":"2026-05-19T20:04:47.689930Z","status":"completed","version":"1.0.0","findings_count":0}],"snapshot_sha256":"b1df11eec64891f517f92b34c5e1bc47d689821a91db1c641688a853eb99f36a"},"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":"024e0a00-13ac-4962-975b-beb7852296d6"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-21T01:04:26Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"pTFC29l3VaO5c3DKjM+nSjpVJYC75mhDwzvpalbvdZm527mPnrBUcpomFSAV2I96FZuCshVwTZERTOYE2kyODg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-28T07:00:55.222924Z"},"content_sha256":"df7f406877145c82ce6c9e48cd0d1835b02a4289a75ead6fd416381ae354fabb","schema_version":"1.0","event_id":"sha256:df7f406877145c82ce6c9e48cd0d1835b02a4289a75ead6fd416381ae354fabb"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/DGBTVKXTAXMI5XJHSR6EHCNNIS/bundle.json","state_url":"https://pith.science/pith/DGBTVKXTAXMI5XJHSR6EHCNNIS/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/DGBTVKXTAXMI5XJHSR6EHCNNIS/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":"2026-05-28T07:00:55Z","links":{"resolver":"https://pith.science/pith/DGBTVKXTAXMI5XJHSR6EHCNNIS","bundle":"https://pith.science/pith/DGBTVKXTAXMI5XJHSR6EHCNNIS/bundle.json","state":"https://pith.science/pith/DGBTVKXTAXMI5XJHSR6EHCNNIS/state.json","well_known_bundle":"https://pith.science/.well-known/pith/DGBTVKXTAXMI5XJHSR6EHCNNIS/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:DGBTVKXTAXMI5XJHSR6EHCNNIS","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":"6ad01081a5f4a92b7b7fe4a37faade7ae4c205570e6bb75414e57576adf3d94c","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"quant-ph","submitted_at":"2026-04-29T09:41:01Z","title_canon_sha256":"8037aeb403b3ebbb4c0c18d1fc0882b008c3ff178cf6404f4b6b46eb721644dc"},"schema_version":"1.0","source":{"id":"2604.26477","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2604.26477","created_at":"2026-05-21T01:04:26Z"},{"alias_kind":"arxiv_version","alias_value":"2604.26477v2","created_at":"2026-05-21T01:04:26Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2604.26477","created_at":"2026-05-21T01:04:26Z"},{"alias_kind":"pith_short_12","alias_value":"DGBTVKXTAXMI","created_at":"2026-05-21T01:04:26Z"},{"alias_kind":"pith_short_16","alias_value":"DGBTVKXTAXMI5XJH","created_at":"2026-05-21T01:04:26Z"},{"alias_kind":"pith_short_8","alias_value":"DGBTVKXT","created_at":"2026-05-21T01:04:26Z"}],"graph_snapshots":[{"event_id":"sha256:df7f406877145c82ce6c9e48cd0d1835b02a4289a75ead6fd416381ae354fabb","target":"graph","created_at":"2026-05-21T01:04:26Z","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":"Our results show that QAIAs can sample candidate solutions approximately two orders of magnitude faster than previously studied quantum processors. In terms of end-to-end runtime, QAIAs also surpass industry-leading classical solvers, thereby establishing themselves as the superior performers among the quantum and classical solvers evaluated thus far for the MO-MaxCut instances."},{"attestation":"unclaimed","claim_id":"C2","kind":"weakest_assumption","source":"verdict.weakest_assumption","status":"machine_extracted","text":"That the chosen benchmark suite and the way pre- and post-processing overheads are measured for both quantum and classical solvers produce a fair, unbiased comparison without hidden selection effects or incomplete accounting."},{"attestation":"unclaimed","claim_id":"C3","kind":"one_line_summary","source":"verdict.one_line_summary","status":"machine_extracted","text":"GPU-based quantum-annealing-inspired algorithms outperform both quantum processors and industry-leading classical solvers in end-to-end runtime on MO-MaxCut benchmarks."},{"attestation":"unclaimed","claim_id":"C4","kind":"headline","source":"verdict.pith_extraction.headline","status":"machine_extracted","text":"Quantum-annealing-inspired algorithms on classical GPUs outperform quantum processors and leading classical solvers on multi-objective MaxCut problems."}],"snapshot_sha256":"0c99293278e43641f6369d14cc0ada046e5362553eb941df034d05d8eacde21c"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[{"findings_count":0,"name":"ai_meta_artifact","ran_at":"2026-05-21T00:34:30.612951Z","status":"completed","version":"1.0.0"},{"findings_count":0,"name":"doi_compliance","ran_at":"2026-05-19T20:04:47.689930Z","status":"completed","version":"1.0.0"}],"endpoint":"/pith/2604.26477/integrity.json","findings":[],"snapshot_sha256":"b1df11eec64891f517f92b34c5e1bc47d689821a91db1c641688a853eb99f36a","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Combinatorial optimization is widely regarded as a primary application for near-term quantum processors, although a definitive demonstration of the practical quantum advantage remains elusive. Recent studies have reported that both gate-based quantum circuits and quantum annealers can outperform state-of-the-art classical heuristics on multi-objective optimization (MO-MaxCut) problems. However, these studies did not fully account for the substantial pre- and post-processing overheads intrinsic to quantum solvers, leading to incomplete comparisons between quantum and classical approaches. In th","authors_text":"Man-Hong Yung, Pavel Mosharev, Xian-Zhe Tao","cross_cats":[],"headline":"Quantum-annealing-inspired algorithms on classical GPUs outperform quantum processors and leading classical solvers on multi-objective MaxCut problems.","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"quant-ph","submitted_at":"2026-04-29T09:41:01Z","title":"Multi-Objective Optimization by Quantum-Annealing-Inspired Algorithms"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2604.26477","kind":"arxiv","version":2},"verdict":{"created_at":"2026-05-07T11:19:21.533468Z","id":"024e0a00-13ac-4962-975b-beb7852296d6","model_set":{"reader":"grok-4.3"},"one_line_summary":"GPU-based quantum-annealing-inspired algorithms outperform both quantum processors and industry-leading classical solvers in end-to-end runtime on MO-MaxCut benchmarks.","pipeline_version":"pith-pipeline@v0.9.0","pith_extraction_headline":"Quantum-annealing-inspired algorithms on classical GPUs outperform quantum processors and leading classical solvers on multi-objective MaxCut problems.","strongest_claim":"Our results show that QAIAs can sample candidate solutions approximately two orders of magnitude faster than previously studied quantum processors. In terms of end-to-end runtime, QAIAs also surpass industry-leading classical solvers, thereby establishing themselves as the superior performers among the quantum and classical solvers evaluated thus far for the MO-MaxCut instances.","weakest_assumption":"That the chosen benchmark suite and the way pre- and post-processing overheads are measured for both quantum and classical solvers produce a fair, unbiased comparison without hidden selection effects or incomplete accounting."}},"verdict_id":"024e0a00-13ac-4962-975b-beb7852296d6"}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:ea51bff6d824fd404ed39084d4692ca6879912ec2b1a3df997f6146800a4a9a5","target":"record","created_at":"2026-05-21T01:04:26Z","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":"6ad01081a5f4a92b7b7fe4a37faade7ae4c205570e6bb75414e57576adf3d94c","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"quant-ph","submitted_at":"2026-04-29T09:41:01Z","title_canon_sha256":"8037aeb403b3ebbb4c0c18d1fc0882b008c3ff178cf6404f4b6b46eb721644dc"},"schema_version":"1.0","source":{"id":"2604.26477","kind":"arxiv","version":2}},"canonical_sha256":"19833aaaf305d88edd27947c4389ad44be1895504630adbc7e9793278947880f","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"19833aaaf305d88edd27947c4389ad44be1895504630adbc7e9793278947880f","first_computed_at":"2026-05-21T01:04:26.472809Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-21T01:04:26.472809Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"BZoi513nsDQz7bVEnkJyUjBMcrMInHWf/Y2FoicUDkXecGhsvYeIVHepJ6ahJm0uOfrARw5Y7QtgJiGSLoB9Dw==","signature_status":"signed_v1","signed_at":"2026-05-21T01:04:26.473569Z","signed_message":"canonical_sha256_bytes"},"source_id":"2604.26477","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ea51bff6d824fd404ed39084d4692ca6879912ec2b1a3df997f6146800a4a9a5","sha256:df7f406877145c82ce6c9e48cd0d1835b02a4289a75ead6fd416381ae354fabb"],"state_sha256":"5d1678471ce9cd9449279f1c135d7d5fe6fbef09fb78b092eccbcc261ad2829c"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"8cZeGq+CgPuiRe9poO5Wmd0oNjoqOCzD3X8GdZiMCls4+N3ehzjkg7SwWGQPbkVW79jG4etrtwGDV9gsPfiCCQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-28T07:00:55.225282Z","bundle_sha256":"3a3b007301ff356d3e73a0d784186169787ba1649b1bcf28a7ccc9cc6a6f9f89"}}