{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2021:DHSWUMZLTIP6N5YHALYACLYWOK","short_pith_number":"pith:DHSWUMZL","schema_version":"1.0","canonical_sha256":"19e56a332b9a1fe6f70702f0012f1672b749055598f320d64b1c54948589a903","source":{"kind":"arxiv","id":"2110.10196","version":2},"attestation_state":"computed","paper":{"title":"Diversity metric for evaluation of quantum annealing","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"quant-ph","authors_text":"Alex Zucca, Hossein Sadeghi, Masoud Mohseni, Mohammad H. Amin","submitted_at":"2021-10-19T18:37:01Z","abstract_excerpt":"Solving discrete NP-hard problems is an important part of scientific discoveries and operations research as well as many commercial applications. A commonly used metric to compare meta-heuristic solvers is the time required to obtain an optimal solution, known as time to solution. However, for some applications it is desirable to have a set of high-quality and diverse solutions, instead of a single optimal one. For these applications, time to solution may not be informative of the performance of a solver, and another metric would be necessary. In particular, it is not known how well quantum so"},"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":"2110.10196","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"quant-ph","submitted_at":"2021-10-19T18:37:01Z","cross_cats_sorted":[],"title_canon_sha256":"bf61aacd0d65617052344e88b46f591bed8ceab8ad52cbbbe6741f75728d7980","abstract_canon_sha256":"66b0f05770600fed66152274c4394aa7aef455f635d5ac94dc5e6dc0d491863d"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T03:24:58.970294Z","signature_b64":"75inrkY9ChqeAcDg2bnIq6oGt9yXWMLvB4VlK2qmgkW39fkDSyNZjaX4fvFrbEL9QyEmALipMSb8jrGSaOvnAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"19e56a332b9a1fe6f70702f0012f1672b749055598f320d64b1c54948589a903","last_reissued_at":"2026-07-05T03:24:58.969806Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T03:24:58.969806Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Diversity metric for evaluation of quantum annealing","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"quant-ph","authors_text":"Alex Zucca, Hossein Sadeghi, Masoud Mohseni, Mohammad H. Amin","submitted_at":"2021-10-19T18:37:01Z","abstract_excerpt":"Solving discrete NP-hard problems is an important part of scientific discoveries and operations research as well as many commercial applications. A commonly used metric to compare meta-heuristic solvers is the time required to obtain an optimal solution, known as time to solution. However, for some applications it is desirable to have a set of high-quality and diverse solutions, instead of a single optimal one. For these applications, time to solution may not be informative of the performance of a solver, and another metric would be necessary. In particular, it is not known how well quantum so"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2110.10196","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/2110.10196/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":"2110.10196","created_at":"2026-07-05T03:24:58.969864+00:00"},{"alias_kind":"arxiv_version","alias_value":"2110.10196v2","created_at":"2026-07-05T03:24:58.969864+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2110.10196","created_at":"2026-07-05T03:24:58.969864+00:00"},{"alias_kind":"pith_short_12","alias_value":"DHSWUMZLTIP6","created_at":"2026-07-05T03:24:58.969864+00:00"},{"alias_kind":"pith_short_16","alias_value":"DHSWUMZLTIP6N5YH","created_at":"2026-07-05T03:24:58.969864+00:00"},{"alias_kind":"pith_short_8","alias_value":"DHSWUMZL","created_at":"2026-07-05T03:24:58.969864+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":2,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2411.10406","citing_title":"How to Build a Quantum Supercomputer: Scaling from Hundreds to Millions of Qubits","ref_index":183,"is_internal_anchor":false},{"citing_arxiv_id":"2604.26534","citing_title":"Neural and Tensor Networks in the Study of Quantum Annealing Processors","ref_index":130,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/DHSWUMZLTIP6N5YHALYACLYWOK","json":"https://pith.science/pith/DHSWUMZLTIP6N5YHALYACLYWOK.json","graph_json":"https://pith.science/api/pith-number/DHSWUMZLTIP6N5YHALYACLYWOK/graph.json","events_json":"https://pith.science/api/pith-number/DHSWUMZLTIP6N5YHALYACLYWOK/events.json","paper":"https://pith.science/paper/DHSWUMZL"},"agent_actions":{"view_html":"https://pith.science/pith/DHSWUMZLTIP6N5YHALYACLYWOK","download_json":"https://pith.science/pith/DHSWUMZLTIP6N5YHALYACLYWOK.json","view_paper":"https://pith.science/paper/DHSWUMZL","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2110.10196&json=true","fetch_graph":"https://pith.science/api/pith-number/DHSWUMZLTIP6N5YHALYACLYWOK/graph.json","fetch_events":"https://pith.science/api/pith-number/DHSWUMZLTIP6N5YHALYACLYWOK/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/DHSWUMZLTIP6N5YHALYACLYWOK/action/timestamp_anchor","attest_storage":"https://pith.science/pith/DHSWUMZLTIP6N5YHALYACLYWOK/action/storage_attestation","attest_author":"https://pith.science/pith/DHSWUMZLTIP6N5YHALYACLYWOK/action/author_attestation","sign_citation":"https://pith.science/pith/DHSWUMZLTIP6N5YHALYACLYWOK/action/citation_signature","submit_replication":"https://pith.science/pith/DHSWUMZLTIP6N5YHALYACLYWOK/action/replication_record"}},"created_at":"2026-07-05T03:24:58.969864+00:00","updated_at":"2026-07-05T03:24:58.969864+00:00"}