{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2018:2IMQLVCOBCTIHFBSYMNOK5CAVE","short_pith_number":"pith:2IMQLVCO","schema_version":"1.0","canonical_sha256":"d21905d44e08a6839432c31ae57440a919c1bbe7abda17e20a673f382f2658da","source":{"kind":"arxiv","id":"1807.08378","version":2},"attestation_state":"computed","paper":{"title":"Efficient representation of long-range interactions in tensor network algorithms","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cond-mat.str-el","authors_text":"Garnet Kin-Lic Chan, Matthew J. O'Rourke, Zhendong Li","submitted_at":"2018-07-22T22:22:10Z","abstract_excerpt":"We describe a practical and efficient approach to represent physically realistic long-range interactions in two-dimensional tensor network algorithms via projected entangled-pair operators (PEPOs). We express the long-range interaction as a linear combination of correlation functions of an auxiliary system with only nearest-neighbor interactions. To obtain a smooth and radially isotropic interaction across all length scales, we map the physical lattice to an auxiliary lattice of expanded size. Our construction yields a long-range PEPO as a sum of ancillary PEPOs, each of small, constant bond d"},"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":"1807.08378","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cond-mat.str-el","submitted_at":"2018-07-22T22:22:10Z","cross_cats_sorted":[],"title_canon_sha256":"84780ecdcf6a69cae74ebbec7d44852c1ffb10f413e4d9595ed84f0993645d73","abstract_canon_sha256":"9c2009f53daf04141e1bf763974acb6e4ab13d94797267b9aabc3f37420beded"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:00:29.881099Z","signature_b64":"N+5IvEoxkQj4XH8HPFnRHJEY8AAW4BcwN6C4/GAtnmK8SNGWhKShqbmRXNcDCQLuEbnxPBphz6eWo9TPe2QiCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d21905d44e08a6839432c31ae57440a919c1bbe7abda17e20a673f382f2658da","last_reissued_at":"2026-05-18T00:00:29.880669Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:00:29.880669Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Efficient representation of long-range interactions in tensor network algorithms","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cond-mat.str-el","authors_text":"Garnet Kin-Lic Chan, Matthew J. O'Rourke, Zhendong Li","submitted_at":"2018-07-22T22:22:10Z","abstract_excerpt":"We describe a practical and efficient approach to represent physically realistic long-range interactions in two-dimensional tensor network algorithms via projected entangled-pair operators (PEPOs). We express the long-range interaction as a linear combination of correlation functions of an auxiliary system with only nearest-neighbor interactions. To obtain a smooth and radially isotropic interaction across all length scales, we map the physical lattice to an auxiliary lattice of expanded size. Our construction yields a long-range PEPO as a sum of ancillary PEPOs, each of small, constant bond d"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1807.08378","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":"1807.08378","created_at":"2026-05-18T00:00:29.880733+00:00"},{"alias_kind":"arxiv_version","alias_value":"1807.08378v2","created_at":"2026-05-18T00:00:29.880733+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1807.08378","created_at":"2026-05-18T00:00:29.880733+00:00"},{"alias_kind":"pith_short_12","alias_value":"2IMQLVCOBCTI","created_at":"2026-05-18T12:32:02.567920+00:00"},{"alias_kind":"pith_short_16","alias_value":"2IMQLVCOBCTIHFBS","created_at":"2026-05-18T12:32:02.567920+00:00"},{"alias_kind":"pith_short_8","alias_value":"2IMQLVCO","created_at":"2026-05-18T12:32:02.567920+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/2IMQLVCOBCTIHFBSYMNOK5CAVE","json":"https://pith.science/pith/2IMQLVCOBCTIHFBSYMNOK5CAVE.json","graph_json":"https://pith.science/api/pith-number/2IMQLVCOBCTIHFBSYMNOK5CAVE/graph.json","events_json":"https://pith.science/api/pith-number/2IMQLVCOBCTIHFBSYMNOK5CAVE/events.json","paper":"https://pith.science/paper/2IMQLVCO"},"agent_actions":{"view_html":"https://pith.science/pith/2IMQLVCOBCTIHFBSYMNOK5CAVE","download_json":"https://pith.science/pith/2IMQLVCOBCTIHFBSYMNOK5CAVE.json","view_paper":"https://pith.science/paper/2IMQLVCO","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1807.08378&json=true","fetch_graph":"https://pith.science/api/pith-number/2IMQLVCOBCTIHFBSYMNOK5CAVE/graph.json","fetch_events":"https://pith.science/api/pith-number/2IMQLVCOBCTIHFBSYMNOK5CAVE/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/2IMQLVCOBCTIHFBSYMNOK5CAVE/action/timestamp_anchor","attest_storage":"https://pith.science/pith/2IMQLVCOBCTIHFBSYMNOK5CAVE/action/storage_attestation","attest_author":"https://pith.science/pith/2IMQLVCOBCTIHFBSYMNOK5CAVE/action/author_attestation","sign_citation":"https://pith.science/pith/2IMQLVCOBCTIHFBSYMNOK5CAVE/action/citation_signature","submit_replication":"https://pith.science/pith/2IMQLVCOBCTIHFBSYMNOK5CAVE/action/replication_record"}},"created_at":"2026-05-18T00:00:29.880733+00:00","updated_at":"2026-05-18T00:00:29.880733+00:00"}