{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2019:RXW5GL6MKC3UMZUNJKD7MYPN4G","short_pith_number":"pith:RXW5GL6M","schema_version":"1.0","canonical_sha256":"8dedd32fcc50b746668d4a87f661ede1a1193236221541ca3b15bba98178c687","source":{"kind":"arxiv","id":"1902.00315","version":2},"attestation_state":"computed","paper":{"title":"Exploiting the causal tensor network structure of quantum processes to efficiently simulate non-Markovian path integrals","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cond-mat.mes-hall"],"primary_cat":"quant-ph","authors_text":"Felix A. Pollock, Mathias R. J{\\o}rgensen","submitted_at":"2019-02-01T13:12:24Z","abstract_excerpt":"In the path integral formulation of the evolution of an open quantum system coupled to a Gaussian, non-interacting environment, the dynamical contribution of the latter is encoded in an object called the influence functional. Here, we relate the influence functional to the process tensor -- a more general representation of a quantum stochastic process -- describing the evolution. We then use this connection to motivate a tensor network algorithm for the simulation of multi-time correlations in open systems, building on recent work where the influence functional is represented in terms of time "},"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":"1902.00315","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"quant-ph","submitted_at":"2019-02-01T13:12:24Z","cross_cats_sorted":["cond-mat.mes-hall"],"title_canon_sha256":"aadb9a422505645e56667f0b783f0cf8a6e23dd7de366d2803a722ee1389af8a","abstract_canon_sha256":"e8e8a41bb09b08f5925a3f7909f0f16c79a566c9d61b0edbe3d81332da98eed5"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T00:25:54.496207Z","signature_b64":"3m2ct5xFe75JIx+DCvv/Cy11ZdZsvGPxqWPZJ4fCaneod/MidWXvZ3LabYyprWpuVmadoazLeFx0RTq/euB4CQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"8dedd32fcc50b746668d4a87f661ede1a1193236221541ca3b15bba98178c687","last_reissued_at":"2026-07-05T00:25:54.495810Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T00:25:54.495810Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Exploiting the causal tensor network structure of quantum processes to efficiently simulate non-Markovian path integrals","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cond-mat.mes-hall"],"primary_cat":"quant-ph","authors_text":"Felix A. Pollock, Mathias R. J{\\o}rgensen","submitted_at":"2019-02-01T13:12:24Z","abstract_excerpt":"In the path integral formulation of the evolution of an open quantum system coupled to a Gaussian, non-interacting environment, the dynamical contribution of the latter is encoded in an object called the influence functional. Here, we relate the influence functional to the process tensor -- a more general representation of a quantum stochastic process -- describing the evolution. We then use this connection to motivate a tensor network algorithm for the simulation of multi-time correlations in open systems, building on recent work where the influence functional is represented in terms of time "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1902.00315","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/1902.00315/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":"1902.00315","created_at":"2026-07-05T00:25:54.495881+00:00"},{"alias_kind":"arxiv_version","alias_value":"1902.00315v2","created_at":"2026-07-05T00:25:54.495881+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1902.00315","created_at":"2026-07-05T00:25:54.495881+00:00"},{"alias_kind":"pith_short_12","alias_value":"RXW5GL6MKC3U","created_at":"2026-07-05T00:25:54.495881+00:00"},{"alias_kind":"pith_short_16","alias_value":"RXW5GL6MKC3UMZUN","created_at":"2026-07-05T00:25:54.495881+00:00"},{"alias_kind":"pith_short_8","alias_value":"RXW5GL6M","created_at":"2026-07-05T00:25:54.495881+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":1,"sample":[{"citing_arxiv_id":"2412.13739","citing_title":"Tensor-network decoders for process tensor descriptions of non-Markovian noise","ref_index":48,"is_internal_anchor":true}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/RXW5GL6MKC3UMZUNJKD7MYPN4G","json":"https://pith.science/pith/RXW5GL6MKC3UMZUNJKD7MYPN4G.json","graph_json":"https://pith.science/api/pith-number/RXW5GL6MKC3UMZUNJKD7MYPN4G/graph.json","events_json":"https://pith.science/api/pith-number/RXW5GL6MKC3UMZUNJKD7MYPN4G/events.json","paper":"https://pith.science/paper/RXW5GL6M"},"agent_actions":{"view_html":"https://pith.science/pith/RXW5GL6MKC3UMZUNJKD7MYPN4G","download_json":"https://pith.science/pith/RXW5GL6MKC3UMZUNJKD7MYPN4G.json","view_paper":"https://pith.science/paper/RXW5GL6M","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1902.00315&json=true","fetch_graph":"https://pith.science/api/pith-number/RXW5GL6MKC3UMZUNJKD7MYPN4G/graph.json","fetch_events":"https://pith.science/api/pith-number/RXW5GL6MKC3UMZUNJKD7MYPN4G/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/RXW5GL6MKC3UMZUNJKD7MYPN4G/action/timestamp_anchor","attest_storage":"https://pith.science/pith/RXW5GL6MKC3UMZUNJKD7MYPN4G/action/storage_attestation","attest_author":"https://pith.science/pith/RXW5GL6MKC3UMZUNJKD7MYPN4G/action/author_attestation","sign_citation":"https://pith.science/pith/RXW5GL6MKC3UMZUNJKD7MYPN4G/action/citation_signature","submit_replication":"https://pith.science/pith/RXW5GL6MKC3UMZUNJKD7MYPN4G/action/replication_record"}},"created_at":"2026-07-05T00:25:54.495881+00:00","updated_at":"2026-07-05T00:25:54.495881+00:00"}