{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2016:7EXMIOHBCRCGBSH2X3QLD7P53P","short_pith_number":"pith:7EXMIOHB","schema_version":"1.0","canonical_sha256":"f92ec438e1144460c8fabee0b1fdfddbd55ab390ceafd6af27c668621770e922","source":{"kind":"arxiv","id":"1609.06674","version":3},"attestation_state":"computed","paper":{"title":"Efficient methods for the estimation of homogenized coefficients","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["math.AP"],"primary_cat":"math.NA","authors_text":"Jean-Christophe Mourrat","submitted_at":"2016-09-21T18:42:38Z","abstract_excerpt":"The main goal of this paper is to define and study new methods for the computation of effective coefficients in the homogenization of divergence-form operators with random coefficients. The methods introduced here are proved to have optimal computational complexity, and are shown numerically to display small constant prefactors. In the spirit of multiscale methods, the main idea is to rely on a progressive coarsening of the problem, which we implement via a generalization of the Green-Kubo formula. The technique can be applied more generally to compute the effective diffusivity of any additive"},"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":"1609.06674","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.NA","submitted_at":"2016-09-21T18:42:38Z","cross_cats_sorted":["math.AP"],"title_canon_sha256":"bf9e310cef02eb7f2db4270127f61b4d20faf62feec072dd595d369a57449ea9","abstract_canon_sha256":"3dd7f008c51cab6bd6313c7a9cf93ace5d772028189cb054740385e9ffa1f053"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:31:42.035341Z","signature_b64":"jZe78+OMbF8Bn4wmC70qB6+knFhVBuqRzy9k2wlS7urnLsCXCaOGXK+3bk2PnqovR8FEnsC19xb3pcDltFBUAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f92ec438e1144460c8fabee0b1fdfddbd55ab390ceafd6af27c668621770e922","last_reissued_at":"2026-05-18T00:31:42.034907Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:31:42.034907Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Efficient methods for the estimation of homogenized coefficients","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["math.AP"],"primary_cat":"math.NA","authors_text":"Jean-Christophe Mourrat","submitted_at":"2016-09-21T18:42:38Z","abstract_excerpt":"The main goal of this paper is to define and study new methods for the computation of effective coefficients in the homogenization of divergence-form operators with random coefficients. The methods introduced here are proved to have optimal computational complexity, and are shown numerically to display small constant prefactors. In the spirit of multiscale methods, the main idea is to rely on a progressive coarsening of the problem, which we implement via a generalization of the Green-Kubo formula. The technique can be applied more generally to compute the effective diffusivity of any additive"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1609.06674","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":""},"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":"1609.06674","created_at":"2026-05-18T00:31:42.034970+00:00"},{"alias_kind":"arxiv_version","alias_value":"1609.06674v3","created_at":"2026-05-18T00:31:42.034970+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1609.06674","created_at":"2026-05-18T00:31:42.034970+00:00"},{"alias_kind":"pith_short_12","alias_value":"7EXMIOHBCRCG","created_at":"2026-05-18T12:30:04.600751+00:00"},{"alias_kind":"pith_short_16","alias_value":"7EXMIOHBCRCGBSH2","created_at":"2026-05-18T12:30:04.600751+00:00"},{"alias_kind":"pith_short_8","alias_value":"7EXMIOHB","created_at":"2026-05-18T12:30:04.600751+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/7EXMIOHBCRCGBSH2X3QLD7P53P","json":"https://pith.science/pith/7EXMIOHBCRCGBSH2X3QLD7P53P.json","graph_json":"https://pith.science/api/pith-number/7EXMIOHBCRCGBSH2X3QLD7P53P/graph.json","events_json":"https://pith.science/api/pith-number/7EXMIOHBCRCGBSH2X3QLD7P53P/events.json","paper":"https://pith.science/paper/7EXMIOHB"},"agent_actions":{"view_html":"https://pith.science/pith/7EXMIOHBCRCGBSH2X3QLD7P53P","download_json":"https://pith.science/pith/7EXMIOHBCRCGBSH2X3QLD7P53P.json","view_paper":"https://pith.science/paper/7EXMIOHB","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1609.06674&json=true","fetch_graph":"https://pith.science/api/pith-number/7EXMIOHBCRCGBSH2X3QLD7P53P/graph.json","fetch_events":"https://pith.science/api/pith-number/7EXMIOHBCRCGBSH2X3QLD7P53P/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/7EXMIOHBCRCGBSH2X3QLD7P53P/action/timestamp_anchor","attest_storage":"https://pith.science/pith/7EXMIOHBCRCGBSH2X3QLD7P53P/action/storage_attestation","attest_author":"https://pith.science/pith/7EXMIOHBCRCGBSH2X3QLD7P53P/action/author_attestation","sign_citation":"https://pith.science/pith/7EXMIOHBCRCGBSH2X3QLD7P53P/action/citation_signature","submit_replication":"https://pith.science/pith/7EXMIOHBCRCGBSH2X3QLD7P53P/action/replication_record"}},"created_at":"2026-05-18T00:31:42.034970+00:00","updated_at":"2026-05-18T00:31:42.034970+00:00"}