{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2016:XDQMSYOWFU5ELXXPIEGZNRN6KN","short_pith_number":"pith:XDQMSYOW","schema_version":"1.0","canonical_sha256":"b8e0c961d62d3a45deef410d96c5be5361beef7c9c9ff8ae6221d923625c8675","source":{"kind":"arxiv","id":"1609.07154","version":1},"attestation_state":"computed","paper":{"title":"A posteriori error estimates for a Virtual Elements Method for the Steklov eigenvalue problem","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"math.NA","authors_text":"David Mora, Gonzalo Rivera, Rodolfo Rodr\\'iguez","submitted_at":"2016-09-22T20:16:30Z","abstract_excerpt":"The paper deals with the a posteriori error analysis of a virtual element method for the Steklov eigenvalue problem. The virtual element method has the advantage of using general polygonal meshes, which allows implementing very efficiently mesh refinement strategies. We introduce a residual type a posteriori error estimator and prove its reliability and efficiency. We use the corresponding error estimator to drive an adaptive scheme. Finally, we report the results of a couple of numerical tests, that allow us to assess the performance of this approach."},"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":"1609.07154","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.NA","submitted_at":"2016-09-22T20:16:30Z","cross_cats_sorted":[],"title_canon_sha256":"950685c1477b4a5844e39d7e9a015f44fadf4afae87aabc0535a2ce08d275c09","abstract_canon_sha256":"691497b68496afb16d34eab6f6b2ce95e19bbf2b829715eb01585dd834e8875d"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:04:02.137243Z","signature_b64":"f/GtdfaDWv0R24P8ACflu+oErC0fPnlWLFaNgmGSHt8WKLMQ0A+nZKTosNTKBkkPGY9YZUxhB8kpmw/tlCQZCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b8e0c961d62d3a45deef410d96c5be5361beef7c9c9ff8ae6221d923625c8675","last_reissued_at":"2026-05-18T01:04:02.136522Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:04:02.136522Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"A posteriori error estimates for a Virtual Elements Method for the Steklov eigenvalue problem","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"math.NA","authors_text":"David Mora, Gonzalo Rivera, Rodolfo Rodr\\'iguez","submitted_at":"2016-09-22T20:16:30Z","abstract_excerpt":"The paper deals with the a posteriori error analysis of a virtual element method for the Steklov eigenvalue problem. The virtual element method has the advantage of using general polygonal meshes, which allows implementing very efficiently mesh refinement strategies. We introduce a residual type a posteriori error estimator and prove its reliability and efficiency. We use the corresponding error estimator to drive an adaptive scheme. Finally, we report the results of a couple of numerical tests, that allow us to assess the performance of this approach."},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1609.07154","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":""},"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":"1609.07154","created_at":"2026-05-18T01:04:02.136640+00:00"},{"alias_kind":"arxiv_version","alias_value":"1609.07154v1","created_at":"2026-05-18T01:04:02.136640+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1609.07154","created_at":"2026-05-18T01:04:02.136640+00:00"},{"alias_kind":"pith_short_12","alias_value":"XDQMSYOWFU5E","created_at":"2026-05-18T12:30:51.357362+00:00"},{"alias_kind":"pith_short_16","alias_value":"XDQMSYOWFU5ELXXP","created_at":"2026-05-18T12:30:51.357362+00:00"},{"alias_kind":"pith_short_8","alias_value":"XDQMSYOW","created_at":"2026-05-18T12:30:51.357362+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/XDQMSYOWFU5ELXXPIEGZNRN6KN","json":"https://pith.science/pith/XDQMSYOWFU5ELXXPIEGZNRN6KN.json","graph_json":"https://pith.science/api/pith-number/XDQMSYOWFU5ELXXPIEGZNRN6KN/graph.json","events_json":"https://pith.science/api/pith-number/XDQMSYOWFU5ELXXPIEGZNRN6KN/events.json","paper":"https://pith.science/paper/XDQMSYOW"},"agent_actions":{"view_html":"https://pith.science/pith/XDQMSYOWFU5ELXXPIEGZNRN6KN","download_json":"https://pith.science/pith/XDQMSYOWFU5ELXXPIEGZNRN6KN.json","view_paper":"https://pith.science/paper/XDQMSYOW","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1609.07154&json=true","fetch_graph":"https://pith.science/api/pith-number/XDQMSYOWFU5ELXXPIEGZNRN6KN/graph.json","fetch_events":"https://pith.science/api/pith-number/XDQMSYOWFU5ELXXPIEGZNRN6KN/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/XDQMSYOWFU5ELXXPIEGZNRN6KN/action/timestamp_anchor","attest_storage":"https://pith.science/pith/XDQMSYOWFU5ELXXPIEGZNRN6KN/action/storage_attestation","attest_author":"https://pith.science/pith/XDQMSYOWFU5ELXXPIEGZNRN6KN/action/author_attestation","sign_citation":"https://pith.science/pith/XDQMSYOWFU5ELXXPIEGZNRN6KN/action/citation_signature","submit_replication":"https://pith.science/pith/XDQMSYOWFU5ELXXPIEGZNRN6KN/action/replication_record"}},"created_at":"2026-05-18T01:04:02.136640+00:00","updated_at":"2026-05-18T01:04:02.136640+00:00"}