{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:332GYYL5CTJLZP37ZKAJ2EOFSF","short_pith_number":"pith:332GYYL5","schema_version":"1.0","canonical_sha256":"def46c617d14d2bcbf7fca809d11c5916cef2ba581d2d0678650fe6f9095b8d5","source":{"kind":"arxiv","id":"2411.02160","version":2},"attestation_state":"computed","paper":{"title":"Resource-optimized fault-tolerant simulation of the Fermi-Hubbard model and high-temperature superconductor models","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cond-mat.str-el"],"primary_cat":"quant-ph","authors_text":"Angus Kan, Benjamin Symons","submitted_at":"2024-11-04T15:18:29Z","abstract_excerpt":"Exploring low-cost applications is paramount to creating value in early fault-tolerant quantum computers. Here we optimize both gate and qubit counts of recent algorithms for simulating the Fermi-Hubbard model. We further devise and compile algorithms to simulate established models of cuprate and pnictide high-temperature superconductors, which include beyond-nearest-neighbor hopping terms and multi-orbital interactions that are absent in the Fermi-Hubbard model. We show that simulations of these more realistic models of high-temperature superconductors require only an order of magnitude or 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":"2411.02160","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"quant-ph","submitted_at":"2024-11-04T15:18:29Z","cross_cats_sorted":["cond-mat.str-el"],"title_canon_sha256":"d592c602d76169eaf37f24af709c8da6bcd7764eee3a29229e5f2dbd701323ae","abstract_canon_sha256":"a90a7a938e66ae7b2d69d0ce9b642e4616f21254f23cd710cce5a14d5800c6a3"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:52:00.709322Z","signature_b64":"WllIJPyrbnyDrxHw4ih5HWe1q4PUyl6l72LUzvfn2OrKxMdARt8Ru95B5m+FbbixqdPEIZZxMNxQi9YUdmonAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"def46c617d14d2bcbf7fca809d11c5916cef2ba581d2d0678650fe6f9095b8d5","last_reissued_at":"2026-07-05T11:52:00.708833Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:52:00.708833Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Resource-optimized fault-tolerant simulation of the Fermi-Hubbard model and high-temperature superconductor models","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cond-mat.str-el"],"primary_cat":"quant-ph","authors_text":"Angus Kan, Benjamin Symons","submitted_at":"2024-11-04T15:18:29Z","abstract_excerpt":"Exploring low-cost applications is paramount to creating value in early fault-tolerant quantum computers. Here we optimize both gate and qubit counts of recent algorithms for simulating the Fermi-Hubbard model. We further devise and compile algorithms to simulate established models of cuprate and pnictide high-temperature superconductors, which include beyond-nearest-neighbor hopping terms and multi-orbital interactions that are absent in the Fermi-Hubbard model. We show that simulations of these more realistic models of high-temperature superconductors require only an order of magnitude or so"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2411.02160","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/2411.02160/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":"2411.02160","created_at":"2026-07-05T11:52:00.708895+00:00"},{"alias_kind":"arxiv_version","alias_value":"2411.02160v2","created_at":"2026-07-05T11:52:00.708895+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2411.02160","created_at":"2026-07-05T11:52:00.708895+00:00"},{"alias_kind":"pith_short_12","alias_value":"332GYYL5CTJL","created_at":"2026-07-05T11:52:00.708895+00:00"},{"alias_kind":"pith_short_16","alias_value":"332GYYL5CTJLZP37","created_at":"2026-07-05T11:52:00.708895+00:00"},{"alias_kind":"pith_short_8","alias_value":"332GYYL5","created_at":"2026-07-05T11:52:00.708895+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":2,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2406.09340","citing_title":"Prospects for NMR Spectral Prediction on Fault-Tolerant Quantum Computers","ref_index":103,"is_internal_anchor":false},{"citing_arxiv_id":"2411.10406","citing_title":"How to Build a Quantum Supercomputer: Scaling from Hundreds to Millions of Qubits","ref_index":30,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/332GYYL5CTJLZP37ZKAJ2EOFSF","json":"https://pith.science/pith/332GYYL5CTJLZP37ZKAJ2EOFSF.json","graph_json":"https://pith.science/api/pith-number/332GYYL5CTJLZP37ZKAJ2EOFSF/graph.json","events_json":"https://pith.science/api/pith-number/332GYYL5CTJLZP37ZKAJ2EOFSF/events.json","paper":"https://pith.science/paper/332GYYL5"},"agent_actions":{"view_html":"https://pith.science/pith/332GYYL5CTJLZP37ZKAJ2EOFSF","download_json":"https://pith.science/pith/332GYYL5CTJLZP37ZKAJ2EOFSF.json","view_paper":"https://pith.science/paper/332GYYL5","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2411.02160&json=true","fetch_graph":"https://pith.science/api/pith-number/332GYYL5CTJLZP37ZKAJ2EOFSF/graph.json","fetch_events":"https://pith.science/api/pith-number/332GYYL5CTJLZP37ZKAJ2EOFSF/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/332GYYL5CTJLZP37ZKAJ2EOFSF/action/timestamp_anchor","attest_storage":"https://pith.science/pith/332GYYL5CTJLZP37ZKAJ2EOFSF/action/storage_attestation","attest_author":"https://pith.science/pith/332GYYL5CTJLZP37ZKAJ2EOFSF/action/author_attestation","sign_citation":"https://pith.science/pith/332GYYL5CTJLZP37ZKAJ2EOFSF/action/citation_signature","submit_replication":"https://pith.science/pith/332GYYL5CTJLZP37ZKAJ2EOFSF/action/replication_record"}},"created_at":"2026-07-05T11:52:00.708895+00:00","updated_at":"2026-07-05T11:52:00.708895+00:00"}