{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:SP6ETXJOKCSAEQJIU5SJFQF2YW","short_pith_number":"pith:SP6ETXJO","schema_version":"1.0","canonical_sha256":"93fc49dd2e50a4024128a76492c0bac5b994f56c500dac11ea47932317a4ecd4","source":{"kind":"arxiv","id":"2506.18594","version":1},"attestation_state":"computed","paper":{"title":"Systematic improvement of the quantum approximate optimisation ansatz for combinatorial optimisation using quantum subspace expansion","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["nucl-th"],"primary_cat":"quant-ph","authors_text":"Yann Beaujeault-Taudi\\`ere","submitted_at":"2025-06-23T12:54:06Z","abstract_excerpt":"The quantum approximate optimisation ansatz (QAOA) is one of the flagship algorithms used to tackle combinatorial optimisation on graphs problems using a quantum computer, and is considered a strong candidate for early fault-tolerant advantage. In this work, I study the enhancement of the QAOA with a generator coordinate method (GCM), and achieve systematic performances improvements in the approximation ratio and fidelity for the maximal independent set on Erd\\\"os-R\\'enyi graphs. The cost-to-solution of the present method and the QAOA are compared by analysing the number of logical CNOT and $T"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2506.18594","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"quant-ph","submitted_at":"2025-06-23T12:54:06Z","cross_cats_sorted":["nucl-th"],"title_canon_sha256":"0da588ada75891df2c6e9af130b085da366b137cc80d58b708b1fef94b38a8f4","abstract_canon_sha256":"1c70a3fd500045887f13674d8877e05fc976d633a81f51da08193cb6f00d7b20"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:25:52.586674Z","signature_b64":"SQ2HKf/X2hfzS7PAIhooqOG11HYulOckM6gAc26D4i7TilRBovxa6rCNiwU6QXbvHkVEyQxFRkNPs6Stf0LKDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"93fc49dd2e50a4024128a76492c0bac5b994f56c500dac11ea47932317a4ecd4","last_reissued_at":"2026-07-05T11:25:52.586030Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:25:52.586030Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Systematic improvement of the quantum approximate optimisation ansatz for combinatorial optimisation using quantum subspace expansion","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["nucl-th"],"primary_cat":"quant-ph","authors_text":"Yann Beaujeault-Taudi\\`ere","submitted_at":"2025-06-23T12:54:06Z","abstract_excerpt":"The quantum approximate optimisation ansatz (QAOA) is one of the flagship algorithms used to tackle combinatorial optimisation on graphs problems using a quantum computer, and is considered a strong candidate for early fault-tolerant advantage. In this work, I study the enhancement of the QAOA with a generator coordinate method (GCM), and achieve systematic performances improvements in the approximation ratio and fidelity for the maximal independent set on Erd\\\"os-R\\'enyi graphs. The cost-to-solution of the present method and the QAOA are compared by analysing the number of logical CNOT and $T"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.18594","kind":"arxiv","version":1},"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/2506.18594/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2506.18594","created_at":"2026-07-05T11:25:52.586099+00:00"},{"alias_kind":"arxiv_version","alias_value":"2506.18594v1","created_at":"2026-07-05T11:25:52.586099+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.18594","created_at":"2026-07-05T11:25:52.586099+00:00"},{"alias_kind":"pith_short_12","alias_value":"SP6ETXJOKCSA","created_at":"2026-07-05T11:25:52.586099+00:00"},{"alias_kind":"pith_short_16","alias_value":"SP6ETXJOKCSAEQJI","created_at":"2026-07-05T11:25:52.586099+00:00"},{"alias_kind":"pith_short_8","alias_value":"SP6ETXJO","created_at":"2026-07-05T11:25:52.586099+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/SP6ETXJOKCSAEQJIU5SJFQF2YW","json":"https://pith.science/pith/SP6ETXJOKCSAEQJIU5SJFQF2YW.json","graph_json":"https://pith.science/api/pith-number/SP6ETXJOKCSAEQJIU5SJFQF2YW/graph.json","events_json":"https://pith.science/api/pith-number/SP6ETXJOKCSAEQJIU5SJFQF2YW/events.json","paper":"https://pith.science/paper/SP6ETXJO"},"agent_actions":{"view_html":"https://pith.science/pith/SP6ETXJOKCSAEQJIU5SJFQF2YW","download_json":"https://pith.science/pith/SP6ETXJOKCSAEQJIU5SJFQF2YW.json","view_paper":"https://pith.science/paper/SP6ETXJO","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2506.18594&json=true","fetch_graph":"https://pith.science/api/pith-number/SP6ETXJOKCSAEQJIU5SJFQF2YW/graph.json","fetch_events":"https://pith.science/api/pith-number/SP6ETXJOKCSAEQJIU5SJFQF2YW/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/SP6ETXJOKCSAEQJIU5SJFQF2YW/action/timestamp_anchor","attest_storage":"https://pith.science/pith/SP6ETXJOKCSAEQJIU5SJFQF2YW/action/storage_attestation","attest_author":"https://pith.science/pith/SP6ETXJOKCSAEQJIU5SJFQF2YW/action/author_attestation","sign_citation":"https://pith.science/pith/SP6ETXJOKCSAEQJIU5SJFQF2YW/action/citation_signature","submit_replication":"https://pith.science/pith/SP6ETXJOKCSAEQJIU5SJFQF2YW/action/replication_record"}},"created_at":"2026-07-05T11:25:52.586099+00:00","updated_at":"2026-07-05T11:25:52.586099+00:00"}