{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2018:KJ7WKMCWLMUOA33EDTKYBIUUXO","short_pith_number":"pith:KJ7WKMCW","schema_version":"1.0","canonical_sha256":"527f6530565b28e06f641cd580a294bbb569caa74f1e9f78efc2fb2879667c79","source":{"kind":"arxiv","id":"1810.01549","version":2},"attestation_state":"computed","paper":{"title":"Efficient ab initio auxiliary-field quantum Monte Carlo calculations in Gaussian bases via low-rank tensor decomposition","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["physics.chem-ph"],"primary_cat":"physics.comp-ph","authors_text":"Garnet Kin-Lic Chan, James Shee, Mario Motta, Shiwei Zhang","submitted_at":"2018-10-03T00:49:13Z","abstract_excerpt":"We describe an algorithm to reduce the cost of auxiliary-field quantum Monte Carlo (AFQMC) calculations for the electronic structure problem. The technique uses a nested low-rank factorization of the electron repulsion integral (ERI). While the cost of conventional AFQMC calculations in Gaussian bases scales as $\\mathcal{O}(N^4)$ where $N$ is the size of the basis, we show that ground-state energies can be computed through tensor decomposition with reduced memory requirements and sub-quartic scaling. The algorithm is applied to hydrogen chains and square grids, water clusters, and hexagonal BN"},"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":"1810.01549","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"physics.comp-ph","submitted_at":"2018-10-03T00:49:13Z","cross_cats_sorted":["physics.chem-ph"],"title_canon_sha256":"9d2c46f91f9e05f5ff57f9a9168f24c7733559d9f2b978c55558d127a7984a1d","abstract_canon_sha256":"09e13962ca1234dea996c8ef4664d282de4151c8bf4b8f895533a97c7b25013b"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:41:53.844853Z","signature_b64":"vkfZ973850wWI7ulXqzz+31mfndGO8bDPKkE8s3ObvltrLvqaZ5360gRB+BvXbVCGyf/HuzHWDvi+b1VUCfnAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"527f6530565b28e06f641cd580a294bbb569caa74f1e9f78efc2fb2879667c79","last_reissued_at":"2026-05-17T23:41:53.844289Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:41:53.844289Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Efficient ab initio auxiliary-field quantum Monte Carlo calculations in Gaussian bases via low-rank tensor decomposition","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["physics.chem-ph"],"primary_cat":"physics.comp-ph","authors_text":"Garnet Kin-Lic Chan, James Shee, Mario Motta, Shiwei Zhang","submitted_at":"2018-10-03T00:49:13Z","abstract_excerpt":"We describe an algorithm to reduce the cost of auxiliary-field quantum Monte Carlo (AFQMC) calculations for the electronic structure problem. The technique uses a nested low-rank factorization of the electron repulsion integral (ERI). While the cost of conventional AFQMC calculations in Gaussian bases scales as $\\mathcal{O}(N^4)$ where $N$ is the size of the basis, we show that ground-state energies can be computed through tensor decomposition with reduced memory requirements and sub-quartic scaling. The algorithm is applied to hydrogen chains and square grids, water clusters, and hexagonal BN"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1810.01549","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":""},"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":"1810.01549","created_at":"2026-05-17T23:41:53.844380+00:00"},{"alias_kind":"arxiv_version","alias_value":"1810.01549v2","created_at":"2026-05-17T23:41:53.844380+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1810.01549","created_at":"2026-05-17T23:41:53.844380+00:00"},{"alias_kind":"pith_short_12","alias_value":"KJ7WKMCWLMUO","created_at":"2026-05-18T12:32:33.847187+00:00"},{"alias_kind":"pith_short_16","alias_value":"KJ7WKMCWLMUOA33E","created_at":"2026-05-18T12:32:33.847187+00:00"},{"alias_kind":"pith_short_8","alias_value":"KJ7WKMCW","created_at":"2026-05-18T12:32:33.847187+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/KJ7WKMCWLMUOA33EDTKYBIUUXO","json":"https://pith.science/pith/KJ7WKMCWLMUOA33EDTKYBIUUXO.json","graph_json":"https://pith.science/api/pith-number/KJ7WKMCWLMUOA33EDTKYBIUUXO/graph.json","events_json":"https://pith.science/api/pith-number/KJ7WKMCWLMUOA33EDTKYBIUUXO/events.json","paper":"https://pith.science/paper/KJ7WKMCW"},"agent_actions":{"view_html":"https://pith.science/pith/KJ7WKMCWLMUOA33EDTKYBIUUXO","download_json":"https://pith.science/pith/KJ7WKMCWLMUOA33EDTKYBIUUXO.json","view_paper":"https://pith.science/paper/KJ7WKMCW","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1810.01549&json=true","fetch_graph":"https://pith.science/api/pith-number/KJ7WKMCWLMUOA33EDTKYBIUUXO/graph.json","fetch_events":"https://pith.science/api/pith-number/KJ7WKMCWLMUOA33EDTKYBIUUXO/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/KJ7WKMCWLMUOA33EDTKYBIUUXO/action/timestamp_anchor","attest_storage":"https://pith.science/pith/KJ7WKMCWLMUOA33EDTKYBIUUXO/action/storage_attestation","attest_author":"https://pith.science/pith/KJ7WKMCWLMUOA33EDTKYBIUUXO/action/author_attestation","sign_citation":"https://pith.science/pith/KJ7WKMCWLMUOA33EDTKYBIUUXO/action/citation_signature","submit_replication":"https://pith.science/pith/KJ7WKMCWLMUOA33EDTKYBIUUXO/action/replication_record"}},"created_at":"2026-05-17T23:41:53.844380+00:00","updated_at":"2026-05-17T23:41:53.844380+00:00"}