{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2021:MBYFMGYRKPVYJPUSLB7RFJBREP","short_pith_number":"pith:MBYFMGYR","schema_version":"1.0","canonical_sha256":"6070561b1153eb84be92587f12a43123db51c32c8de67b13f1e5b0db224fde90","source":{"kind":"arxiv","id":"2103.09976","version":3},"attestation_state":"computed","paper":{"title":"Low communication high performance ab initio density matrix renormalization group algorithms","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"physics.chem-ph","authors_text":"Garnet Kin-Lic Chan, Huanchen Zhai","submitted_at":"2021-03-18T01:49:19Z","abstract_excerpt":"There has been recent interest in the deployment of ab initio density matrix renormalization group computations on high performance computing platforms. Here, we introduce a reformulation of the conventional distributed memory ab initio DMRG algorithm that connects it to the conceptually simpler and advantageous sum of sub-Hamiltonians approach. Starting from this framework, we further explore a hierarchy of parallelism strategies, that includes (i) parallelism over the sum of sub-Hamiltonians, (ii) parallelism over sites, (iii) parallelism over normal and complementary operators, (iv) paralle"},"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":"2103.09976","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"physics.chem-ph","submitted_at":"2021-03-18T01:49:19Z","cross_cats_sorted":[],"title_canon_sha256":"cf5bcc02f0064d286c9e4bf19decb9e5d573aed4b3ac7e81614788bd876adc69","abstract_canon_sha256":"908708a7014c6c8d1686a6ee15384e564fe122f376823d387e6bdc3f66a9d2b2"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T02:51:39.657092Z","signature_b64":"Kl7L6+wcTyFmZh0owFFdc69pZpZh5+BSaPQJ3+C6QO7b3yawQ8zogb35xOu7o93WhUb1U9WJEbEt83QHPW2LAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"6070561b1153eb84be92587f12a43123db51c32c8de67b13f1e5b0db224fde90","last_reissued_at":"2026-07-05T02:51:39.656667Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T02:51:39.656667Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Low communication high performance ab initio density matrix renormalization group algorithms","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"physics.chem-ph","authors_text":"Garnet Kin-Lic Chan, Huanchen Zhai","submitted_at":"2021-03-18T01:49:19Z","abstract_excerpt":"There has been recent interest in the deployment of ab initio density matrix renormalization group computations on high performance computing platforms. Here, we introduce a reformulation of the conventional distributed memory ab initio DMRG algorithm that connects it to the conceptually simpler and advantageous sum of sub-Hamiltonians approach. Starting from this framework, we further explore a hierarchy of parallelism strategies, that includes (i) parallelism over the sum of sub-Hamiltonians, (ii) parallelism over sites, (iii) parallelism over normal and complementary operators, (iv) paralle"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2103.09976","kind":"arxiv","version":3},"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/2103.09976/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":"2103.09976","created_at":"2026-07-05T02:51:39.656728+00:00"},{"alias_kind":"arxiv_version","alias_value":"2103.09976v3","created_at":"2026-07-05T02:51:39.656728+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2103.09976","created_at":"2026-07-05T02:51:39.656728+00:00"},{"alias_kind":"pith_short_12","alias_value":"MBYFMGYRKPVY","created_at":"2026-07-05T02:51:39.656728+00:00"},{"alias_kind":"pith_short_16","alias_value":"MBYFMGYRKPVYJPUS","created_at":"2026-07-05T02:51:39.656728+00:00"},{"alias_kind":"pith_short_8","alias_value":"MBYFMGYR","created_at":"2026-07-05T02:51:39.656728+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2605.04517","citing_title":"Angular Gausslets","ref_index":23,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/MBYFMGYRKPVYJPUSLB7RFJBREP","json":"https://pith.science/pith/MBYFMGYRKPVYJPUSLB7RFJBREP.json","graph_json":"https://pith.science/api/pith-number/MBYFMGYRKPVYJPUSLB7RFJBREP/graph.json","events_json":"https://pith.science/api/pith-number/MBYFMGYRKPVYJPUSLB7RFJBREP/events.json","paper":"https://pith.science/paper/MBYFMGYR"},"agent_actions":{"view_html":"https://pith.science/pith/MBYFMGYRKPVYJPUSLB7RFJBREP","download_json":"https://pith.science/pith/MBYFMGYRKPVYJPUSLB7RFJBREP.json","view_paper":"https://pith.science/paper/MBYFMGYR","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2103.09976&json=true","fetch_graph":"https://pith.science/api/pith-number/MBYFMGYRKPVYJPUSLB7RFJBREP/graph.json","fetch_events":"https://pith.science/api/pith-number/MBYFMGYRKPVYJPUSLB7RFJBREP/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/MBYFMGYRKPVYJPUSLB7RFJBREP/action/timestamp_anchor","attest_storage":"https://pith.science/pith/MBYFMGYRKPVYJPUSLB7RFJBREP/action/storage_attestation","attest_author":"https://pith.science/pith/MBYFMGYRKPVYJPUSLB7RFJBREP/action/author_attestation","sign_citation":"https://pith.science/pith/MBYFMGYRKPVYJPUSLB7RFJBREP/action/citation_signature","submit_replication":"https://pith.science/pith/MBYFMGYRKPVYJPUSLB7RFJBREP/action/replication_record"}},"created_at":"2026-07-05T02:51:39.656728+00:00","updated_at":"2026-07-05T02:51:39.656728+00:00"}