{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:WLFSZUGOMH64CBYVGSCX7FTNL4","short_pith_number":"pith:WLFSZUGO","schema_version":"1.0","canonical_sha256":"b2cb2cd0ce61fdc1071534857f966d5f104c8999d970bec00690d8282fa537a1","source":{"kind":"arxiv","id":"2408.10217","version":1},"attestation_state":"computed","paper":{"title":"Inference of Heterogeneous Material Properties via Infinite-Dimensional Integrated DIC","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.NA","math.OC"],"primary_cat":"math.NA","authors_text":"DingCheng Luo, Joseph Kirchhoff, Omar Ghattas, Thomas O'Leary-Roseberry","submitted_at":"2024-07-22T19:20:40Z","abstract_excerpt":"We present a scalable and efficient framework for the inference of spatially-varying parameters of continuum materials from image observations of their deformations. Our goal is the nondestructive identification of arbitrary damage, defects, anomalies and inclusions without knowledge of their morphology or strength. Since these effects cannot be directly observed, we pose their identification as an inverse problem. Our approach builds on integrated digital image correlation (IDIC, Besnard Hild, Roux, 2006), which poses the image registration and material inference as a monolithic inverse probl"},"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":"2408.10217","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.NA","submitted_at":"2024-07-22T19:20:40Z","cross_cats_sorted":["cs.NA","math.OC"],"title_canon_sha256":"e86e832f8305c1f7f0dca35f5ca115beb952b5789d55f658ee0ad55022b9deaf","abstract_canon_sha256":"c15770b45733a5d90490eff3c235d5bbe4d7f79ad790ce82d74b998a8bf13c03"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:57:07.730124Z","signature_b64":"lc5Cag8hNHTUPiJcuOlQoclHfUZQqCO9l1pbOf+qA+EKYx00UT1kYit2VHJFRh1bkuuwl+iZrAPCTg36qcUTAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b2cb2cd0ce61fdc1071534857f966d5f104c8999d970bec00690d8282fa537a1","last_reissued_at":"2026-07-05T08:57:07.729505Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:57:07.729505Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Inference of Heterogeneous Material Properties via Infinite-Dimensional Integrated DIC","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.NA","math.OC"],"primary_cat":"math.NA","authors_text":"DingCheng Luo, Joseph Kirchhoff, Omar Ghattas, Thomas O'Leary-Roseberry","submitted_at":"2024-07-22T19:20:40Z","abstract_excerpt":"We present a scalable and efficient framework for the inference of spatially-varying parameters of continuum materials from image observations of their deformations. Our goal is the nondestructive identification of arbitrary damage, defects, anomalies and inclusions without knowledge of their morphology or strength. Since these effects cannot be directly observed, we pose their identification as an inverse problem. Our approach builds on integrated digital image correlation (IDIC, Besnard Hild, Roux, 2006), which poses the image registration and material inference as a monolithic inverse probl"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2408.10217","kind":"arxiv","version":1},"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/2408.10217/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":"2408.10217","created_at":"2026-07-05T08:57:07.729579+00:00"},{"alias_kind":"arxiv_version","alias_value":"2408.10217v1","created_at":"2026-07-05T08:57:07.729579+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2408.10217","created_at":"2026-07-05T08:57:07.729579+00:00"},{"alias_kind":"pith_short_12","alias_value":"WLFSZUGOMH64","created_at":"2026-07-05T08:57:07.729579+00:00"},{"alias_kind":"pith_short_16","alias_value":"WLFSZUGOMH64CBYV","created_at":"2026-07-05T08:57:07.729579+00:00"},{"alias_kind":"pith_short_8","alias_value":"WLFSZUGO","created_at":"2026-07-05T08:57:07.729579+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2603.12365","citing_title":"Optimal Experimental Design for Reliable Learning of History-Dependent Constitutive Laws","ref_index":65,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/WLFSZUGOMH64CBYVGSCX7FTNL4","json":"https://pith.science/pith/WLFSZUGOMH64CBYVGSCX7FTNL4.json","graph_json":"https://pith.science/api/pith-number/WLFSZUGOMH64CBYVGSCX7FTNL4/graph.json","events_json":"https://pith.science/api/pith-number/WLFSZUGOMH64CBYVGSCX7FTNL4/events.json","paper":"https://pith.science/paper/WLFSZUGO"},"agent_actions":{"view_html":"https://pith.science/pith/WLFSZUGOMH64CBYVGSCX7FTNL4","download_json":"https://pith.science/pith/WLFSZUGOMH64CBYVGSCX7FTNL4.json","view_paper":"https://pith.science/paper/WLFSZUGO","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2408.10217&json=true","fetch_graph":"https://pith.science/api/pith-number/WLFSZUGOMH64CBYVGSCX7FTNL4/graph.json","fetch_events":"https://pith.science/api/pith-number/WLFSZUGOMH64CBYVGSCX7FTNL4/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/WLFSZUGOMH64CBYVGSCX7FTNL4/action/timestamp_anchor","attest_storage":"https://pith.science/pith/WLFSZUGOMH64CBYVGSCX7FTNL4/action/storage_attestation","attest_author":"https://pith.science/pith/WLFSZUGOMH64CBYVGSCX7FTNL4/action/author_attestation","sign_citation":"https://pith.science/pith/WLFSZUGOMH64CBYVGSCX7FTNL4/action/citation_signature","submit_replication":"https://pith.science/pith/WLFSZUGOMH64CBYVGSCX7FTNL4/action/replication_record"}},"created_at":"2026-07-05T08:57:07.729579+00:00","updated_at":"2026-07-05T08:57:07.729579+00:00"}