{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:OFAFFMTJK7LB7PWOHEYODRXSTF","short_pith_number":"pith:OFAFFMTJ","canonical_record":{"source":{"id":"2101.02973","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2021-01-08T11:55:24Z","cross_cats_sorted":["cs.CE","cs.NA","math.NA"],"title_canon_sha256":"2da6b8ade60a79702c92a2829b0eea2883417ec938f8208a181fc8b9b854b53e","abstract_canon_sha256":"cba539086c9ccd546b4498c20c13a40bc58fc269f5588c75d6d909890cfd0a1a"},"schema_version":"1.0"},"canonical_sha256":"714052b26957d61fbece3930e1c6f299677ba1df26ebfdcccf419afa69c0c827","source":{"kind":"arxiv","id":"2101.02973","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2101.02973","created_at":"2026-07-05T02:09:56Z"},{"alias_kind":"arxiv_version","alias_value":"2101.02973v1","created_at":"2026-07-05T02:09:56Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2101.02973","created_at":"2026-07-05T02:09:56Z"},{"alias_kind":"pith_short_12","alias_value":"OFAFFMTJK7LB","created_at":"2026-07-05T02:09:56Z"},{"alias_kind":"pith_short_16","alias_value":"OFAFFMTJK7LB7PWO","created_at":"2026-07-05T02:09:56Z"},{"alias_kind":"pith_short_8","alias_value":"OFAFFMTJ","created_at":"2026-07-05T02:09:56Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:OFAFFMTJK7LB7PWOHEYODRXSTF","target":"record","payload":{"canonical_record":{"source":{"id":"2101.02973","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2021-01-08T11:55:24Z","cross_cats_sorted":["cs.CE","cs.NA","math.NA"],"title_canon_sha256":"2da6b8ade60a79702c92a2829b0eea2883417ec938f8208a181fc8b9b854b53e","abstract_canon_sha256":"cba539086c9ccd546b4498c20c13a40bc58fc269f5588c75d6d909890cfd0a1a"},"schema_version":"1.0"},"canonical_sha256":"714052b26957d61fbece3930e1c6f299677ba1df26ebfdcccf419afa69c0c827","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T02:09:56.144505Z","signature_b64":"z7IRJ5ccq6IkIHvX9uhptZseEs33yz2MrC1SjgQtNSV6z+qlzaKDq0mY8Gxa4u3bHmkWE8xNwIU8ULM7v1xPAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"714052b26957d61fbece3930e1c6f299677ba1df26ebfdcccf419afa69c0c827","last_reissued_at":"2026-07-05T02:09:56.144019Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T02:09:56.144019Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2101.02973","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T02:09:56Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"CAG7RMFIF6Sklzw3ogIqCQ3uPdJeqRATZ2L1aVzq9945z/pO3AT6KD3lsLODpyGTs9rui9UVfRVOJAL8ak1gDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T02:16:31.619955Z"},"content_sha256":"b5b0d54420508e0de1db7d5398f22e8a533f2132e9aef67f3d60908d522e96b5","schema_version":"1.0","event_id":"sha256:b5b0d54420508e0de1db7d5398f22e8a533f2132e9aef67f3d60908d522e96b5"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:OFAFFMTJK7LB7PWOHEYODRXSTF","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Topology Optimization with linearized buckling criteria in 250 lines of Matlab","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CE","cs.NA","math.NA"],"primary_cat":"math.OC","authors_text":"Federico Ferrari, James K. Guest, Ole Sigmund","submitted_at":"2021-01-08T11:55:24Z","abstract_excerpt":"We present a 250 line Matlab code for topology optimization for linearized buckling criteria. The code is conceived to handle stiffness, volume and Buckling Load Factors (BLFs) either as the objective function or as constraints. We use the Kreisselmeier-Steinhauser aggregation function in order to reduce multiple objectives (viz. constraints) to a single, differentiable one. Then, the problem is sequentially approximated by using MMA-like expansions and an OC-like scheme is tailored to update the variables. The inspection of the stress stiffness matrix leads to a vectorized implementation for "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2101.02973","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/2101.02973/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T02:09:56Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"nQkYp1UkblTipYiOamWrqZU1595cuua/nWTBQ8XzYLEbfmjP3G+2N6oLl7QSXKbFXNKaxEI732olq9jhnKdUDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T02:16:31.620906Z"},"content_sha256":"060d554da35d4b266fa23e8c4033bf736223fe3f743c88558eccac3e57e3497b","schema_version":"1.0","event_id":"sha256:060d554da35d4b266fa23e8c4033bf736223fe3f743c88558eccac3e57e3497b"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/OFAFFMTJK7LB7PWOHEYODRXSTF/bundle.json","state_url":"https://pith.science/pith/OFAFFMTJK7LB7PWOHEYODRXSTF/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/OFAFFMTJK7LB7PWOHEYODRXSTF/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-04T02:16:31Z","links":{"resolver":"https://pith.science/pith/OFAFFMTJK7LB7PWOHEYODRXSTF","bundle":"https://pith.science/pith/OFAFFMTJK7LB7PWOHEYODRXSTF/bundle.json","state":"https://pith.science/pith/OFAFFMTJK7LB7PWOHEYODRXSTF/state.json","well_known_bundle":"https://pith.science/.well-known/pith/OFAFFMTJK7LB7PWOHEYODRXSTF/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:OFAFFMTJK7LB7PWOHEYODRXSTF","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"cba539086c9ccd546b4498c20c13a40bc58fc269f5588c75d6d909890cfd0a1a","cross_cats_sorted":["cs.CE","cs.NA","math.NA"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2021-01-08T11:55:24Z","title_canon_sha256":"2da6b8ade60a79702c92a2829b0eea2883417ec938f8208a181fc8b9b854b53e"},"schema_version":"1.0","source":{"id":"2101.02973","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2101.02973","created_at":"2026-07-05T02:09:56Z"},{"alias_kind":"arxiv_version","alias_value":"2101.02973v1","created_at":"2026-07-05T02:09:56Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2101.02973","created_at":"2026-07-05T02:09:56Z"},{"alias_kind":"pith_short_12","alias_value":"OFAFFMTJK7LB","created_at":"2026-07-05T02:09:56Z"},{"alias_kind":"pith_short_16","alias_value":"OFAFFMTJK7LB7PWO","created_at":"2026-07-05T02:09:56Z"},{"alias_kind":"pith_short_8","alias_value":"OFAFFMTJ","created_at":"2026-07-05T02:09:56Z"}],"graph_snapshots":[{"event_id":"sha256:060d554da35d4b266fa23e8c4033bf736223fe3f743c88558eccac3e57e3497b","target":"graph","created_at":"2026-07-05T02:09:56Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2101.02973/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We present a 250 line Matlab code for topology optimization for linearized buckling criteria. The code is conceived to handle stiffness, volume and Buckling Load Factors (BLFs) either as the objective function or as constraints. We use the Kreisselmeier-Steinhauser aggregation function in order to reduce multiple objectives (viz. constraints) to a single, differentiable one. Then, the problem is sequentially approximated by using MMA-like expansions and an OC-like scheme is tailored to update the variables. The inspection of the stress stiffness matrix leads to a vectorized implementation for ","authors_text":"Federico Ferrari, James K. Guest, Ole Sigmund","cross_cats":["cs.CE","cs.NA","math.NA"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2021-01-08T11:55:24Z","title":"Topology Optimization with linearized buckling criteria in 250 lines of Matlab"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2101.02973","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:b5b0d54420508e0de1db7d5398f22e8a533f2132e9aef67f3d60908d522e96b5","target":"record","created_at":"2026-07-05T02:09:56Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"cba539086c9ccd546b4498c20c13a40bc58fc269f5588c75d6d909890cfd0a1a","cross_cats_sorted":["cs.CE","cs.NA","math.NA"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2021-01-08T11:55:24Z","title_canon_sha256":"2da6b8ade60a79702c92a2829b0eea2883417ec938f8208a181fc8b9b854b53e"},"schema_version":"1.0","source":{"id":"2101.02973","kind":"arxiv","version":1}},"canonical_sha256":"714052b26957d61fbece3930e1c6f299677ba1df26ebfdcccf419afa69c0c827","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"714052b26957d61fbece3930e1c6f299677ba1df26ebfdcccf419afa69c0c827","first_computed_at":"2026-07-05T02:09:56.144019Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T02:09:56.144019Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"z7IRJ5ccq6IkIHvX9uhptZseEs33yz2MrC1SjgQtNSV6z+qlzaKDq0mY8Gxa4u3bHmkWE8xNwIU8ULM7v1xPAA==","signature_status":"signed_v1","signed_at":"2026-07-05T02:09:56.144505Z","signed_message":"canonical_sha256_bytes"},"source_id":"2101.02973","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b5b0d54420508e0de1db7d5398f22e8a533f2132e9aef67f3d60908d522e96b5","sha256:060d554da35d4b266fa23e8c4033bf736223fe3f743c88558eccac3e57e3497b"],"state_sha256":"7f9ba73f1fe299ad1cb50f1657c57ab7566f51d95aeeae600feee2e6a8a0dc75"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"VlfUEc/398Iko16GcgRD9CgrViu46cl59DH3gISniu9B1wz3MEihFAvRSemVGYjFYaXqFABNlfeelaVPphvICw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-04T02:16:31.627477Z","bundle_sha256":"7253310c1d1b586d7d736094f3503f0cbd58a483a6010ca339a7c49c947727d5"}}