{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:6IROK6YYJ3TE4FNBOJHWZH5KI7","short_pith_number":"pith:6IROK6YY","schema_version":"1.0","canonical_sha256":"f222e57b184ee64e15a1724f6c9faa47e9e7105f89338fe06daaa5055c8f4681","source":{"kind":"arxiv","id":"2412.15147","version":1},"attestation_state":"computed","paper":{"title":"Performance of Variational Algorithms for Local Hamiltonian Problems on Random Regular Graphs","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"quant-ph","authors_text":"Adrian She, James Sud, Kunal Marwaha","submitted_at":"2024-12-19T18:27:39Z","abstract_excerpt":"We design two variational algorithms to optimize specific 2-local Hamiltonians defined on graphs. Our algorithms are inspired by the Quantum Approximate Optimization Algorithm. We develop formulae to analyze the energy achieved by these algorithms with high probability over random regular graphs in the infinite-size limit, using techniques from [arXiv:2110.14206]. The complexity of evaluating these formulae scales exponentially with the number of layers of the algorithms, so our numerical evaluation is limited to a small constant number of layers. We compare these algorithms to simple classica"},"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":"2412.15147","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"quant-ph","submitted_at":"2024-12-19T18:27:39Z","cross_cats_sorted":[],"title_canon_sha256":"627df969e77eafbc7782199d8367f0d92acaa2a968e67e7ffa786f1cb3e8ce3e","abstract_canon_sha256":"02692ebfbbd22c773ee1d638747e8e75d6ddac9c9f0cd2fa3c5c24968e22b595"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:51:58.525861Z","signature_b64":"45kiZN+6mkS2S0UFRaqzWZHQKYmHqPhWcSrkCckq2chuDsiuoDE1yx/Yu+FrZxJzXcaN4jCerc22hr5Sc9zLBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f222e57b184ee64e15a1724f6c9faa47e9e7105f89338fe06daaa5055c8f4681","last_reissued_at":"2026-07-05T09:51:58.525413Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:51:58.525413Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Performance of Variational Algorithms for Local Hamiltonian Problems on Random Regular Graphs","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"quant-ph","authors_text":"Adrian She, James Sud, Kunal Marwaha","submitted_at":"2024-12-19T18:27:39Z","abstract_excerpt":"We design two variational algorithms to optimize specific 2-local Hamiltonians defined on graphs. Our algorithms are inspired by the Quantum Approximate Optimization Algorithm. We develop formulae to analyze the energy achieved by these algorithms with high probability over random regular graphs in the infinite-size limit, using techniques from [arXiv:2110.14206]. The complexity of evaluating these formulae scales exponentially with the number of layers of the algorithms, so our numerical evaluation is limited to a small constant number of layers. We compare these algorithms to simple classica"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.15147","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/2412.15147/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":"2412.15147","created_at":"2026-07-05T09:51:58.525464+00:00"},{"alias_kind":"arxiv_version","alias_value":"2412.15147v1","created_at":"2026-07-05T09:51:58.525464+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.15147","created_at":"2026-07-05T09:51:58.525464+00:00"},{"alias_kind":"pith_short_12","alias_value":"6IROK6YYJ3TE","created_at":"2026-07-05T09:51:58.525464+00:00"},{"alias_kind":"pith_short_16","alias_value":"6IROK6YYJ3TE4FNB","created_at":"2026-07-05T09:51:58.525464+00:00"},{"alias_kind":"pith_short_8","alias_value":"6IROK6YY","created_at":"2026-07-05T09:51:58.525464+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/6IROK6YYJ3TE4FNBOJHWZH5KI7","json":"https://pith.science/pith/6IROK6YYJ3TE4FNBOJHWZH5KI7.json","graph_json":"https://pith.science/api/pith-number/6IROK6YYJ3TE4FNBOJHWZH5KI7/graph.json","events_json":"https://pith.science/api/pith-number/6IROK6YYJ3TE4FNBOJHWZH5KI7/events.json","paper":"https://pith.science/paper/6IROK6YY"},"agent_actions":{"view_html":"https://pith.science/pith/6IROK6YYJ3TE4FNBOJHWZH5KI7","download_json":"https://pith.science/pith/6IROK6YYJ3TE4FNBOJHWZH5KI7.json","view_paper":"https://pith.science/paper/6IROK6YY","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2412.15147&json=true","fetch_graph":"https://pith.science/api/pith-number/6IROK6YYJ3TE4FNBOJHWZH5KI7/graph.json","fetch_events":"https://pith.science/api/pith-number/6IROK6YYJ3TE4FNBOJHWZH5KI7/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/6IROK6YYJ3TE4FNBOJHWZH5KI7/action/timestamp_anchor","attest_storage":"https://pith.science/pith/6IROK6YYJ3TE4FNBOJHWZH5KI7/action/storage_attestation","attest_author":"https://pith.science/pith/6IROK6YYJ3TE4FNBOJHWZH5KI7/action/author_attestation","sign_citation":"https://pith.science/pith/6IROK6YYJ3TE4FNBOJHWZH5KI7/action/citation_signature","submit_replication":"https://pith.science/pith/6IROK6YYJ3TE4FNBOJHWZH5KI7/action/replication_record"}},"created_at":"2026-07-05T09:51:58.525464+00:00","updated_at":"2026-07-05T09:51:58.525464+00:00"}