{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:BOWKA36VIRDMRQ73QQCQTOYRNQ","short_pith_number":"pith:BOWKA36V","canonical_record":{"source":{"id":"2302.00711","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"math.OC","submitted_at":"2023-02-01T19:08:15Z","cross_cats_sorted":[],"title_canon_sha256":"35c5e825710f1498dbc22f789934180ab8059e23c7708be9f30f584e5ff9733f","abstract_canon_sha256":"0872be2f6886f8b368ba7c2bbf81b334ce2505f9f66d2dfcde469c7fcaa45b9b"},"schema_version":"1.0"},"canonical_sha256":"0baca06fd54446c8c3fb840509bb116c36cd7ebb0e48a81a892efc60dd92cc77","source":{"kind":"arxiv","id":"2302.00711","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2302.00711","created_at":"2026-07-05T05:38:11Z"},{"alias_kind":"arxiv_version","alias_value":"2302.00711v1","created_at":"2026-07-05T05:38:11Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2302.00711","created_at":"2026-07-05T05:38:11Z"},{"alias_kind":"pith_short_12","alias_value":"BOWKA36VIRDM","created_at":"2026-07-05T05:38:11Z"},{"alias_kind":"pith_short_16","alias_value":"BOWKA36VIRDMRQ73","created_at":"2026-07-05T05:38:11Z"},{"alias_kind":"pith_short_8","alias_value":"BOWKA36V","created_at":"2026-07-05T05:38:11Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:BOWKA36VIRDMRQ73QQCQTOYRNQ","target":"record","payload":{"canonical_record":{"source":{"id":"2302.00711","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"math.OC","submitted_at":"2023-02-01T19:08:15Z","cross_cats_sorted":[],"title_canon_sha256":"35c5e825710f1498dbc22f789934180ab8059e23c7708be9f30f584e5ff9733f","abstract_canon_sha256":"0872be2f6886f8b368ba7c2bbf81b334ce2505f9f66d2dfcde469c7fcaa45b9b"},"schema_version":"1.0"},"canonical_sha256":"0baca06fd54446c8c3fb840509bb116c36cd7ebb0e48a81a892efc60dd92cc77","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:38:11.473585Z","signature_b64":"gUY7eHmqW/TEObBAHtsG8IYe7kvo4JfDMG9xV0nqTjDJwj411EmrdtqdLQv4DCt2fBttJ7AlsNCbbuBn77plAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"0baca06fd54446c8c3fb840509bb116c36cd7ebb0e48a81a892efc60dd92cc77","last_reissued_at":"2026-07-05T05:38:11.473122Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:38:11.473122Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2302.00711","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":"2026-07-05T05:38:11Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"lIsS0wIJYj2uNzCPu2eG+b5ljMXKTZURW2UtnkWO+D6kEkmNHva4vVGA/OoV9vcqHrsvrP7rGGDINgTxnq/oCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-12T02:58:24.847440Z"},"content_sha256":"2395d9063486af9ab4540d488bf092bdad14cd8c854dafabb439b29f385d772a","schema_version":"1.0","event_id":"sha256:2395d9063486af9ab4540d488bf092bdad14cd8c854dafabb439b29f385d772a"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:BOWKA36VIRDMRQ73QQCQTOYRNQ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Generating Linear, Semidefinite, and Second-order Cone Optimization Problems for Numerical Experiments","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"math.OC","authors_text":"Brandon Augustino, Mohammadhossein Mohammadisiahroudi, Ramin Fakhimi, Tam\\'as Terlaky","submitted_at":"2023-02-01T19:08:15Z","abstract_excerpt":"The numerical performance of algorithms can be studied using test sets or procedures that generate such problems. This paper proposes various methods for generating linear, semidefinite, and second-order cone optimization problems. Specifically, we are interested in problem instances requiring a known optimal solution, a known optimal partition, a specific interior solution, or all these together. In the proposed problem generators, different characteristics of optimization problems, including dimension, size, condition number, degeneracy, optimal partition, and sparsity, can be chosen to faci"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2302.00711","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/2302.00711/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":"2026-07-05T05:38:11Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"RM86Buag0thHYlHWt9uqPraVC58LrnhRrkpiiHQ8MVmgajGI6A8iX36P01b9Pd8dG02pDAZwpvwkkTabRq0CDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-12T02:58:24.847867Z"},"content_sha256":"e4bf88f3be0ab6a2734c05eb3a13ae99fbd566b716818f908bd9d8e0d73e4781","schema_version":"1.0","event_id":"sha256:e4bf88f3be0ab6a2734c05eb3a13ae99fbd566b716818f908bd9d8e0d73e4781"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/BOWKA36VIRDMRQ73QQCQTOYRNQ/bundle.json","state_url":"https://pith.science/pith/BOWKA36VIRDMRQ73QQCQTOYRNQ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/BOWKA36VIRDMRQ73QQCQTOYRNQ/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":"2026-07-12T02:58:24Z","links":{"resolver":"https://pith.science/pith/BOWKA36VIRDMRQ73QQCQTOYRNQ","bundle":"https://pith.science/pith/BOWKA36VIRDMRQ73QQCQTOYRNQ/bundle.json","state":"https://pith.science/pith/BOWKA36VIRDMRQ73QQCQTOYRNQ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/BOWKA36VIRDMRQ73QQCQTOYRNQ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:BOWKA36VIRDMRQ73QQCQTOYRNQ","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":"0872be2f6886f8b368ba7c2bbf81b334ce2505f9f66d2dfcde469c7fcaa45b9b","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"math.OC","submitted_at":"2023-02-01T19:08:15Z","title_canon_sha256":"35c5e825710f1498dbc22f789934180ab8059e23c7708be9f30f584e5ff9733f"},"schema_version":"1.0","source":{"id":"2302.00711","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2302.00711","created_at":"2026-07-05T05:38:11Z"},{"alias_kind":"arxiv_version","alias_value":"2302.00711v1","created_at":"2026-07-05T05:38:11Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2302.00711","created_at":"2026-07-05T05:38:11Z"},{"alias_kind":"pith_short_12","alias_value":"BOWKA36VIRDM","created_at":"2026-07-05T05:38:11Z"},{"alias_kind":"pith_short_16","alias_value":"BOWKA36VIRDMRQ73","created_at":"2026-07-05T05:38:11Z"},{"alias_kind":"pith_short_8","alias_value":"BOWKA36V","created_at":"2026-07-05T05:38:11Z"}],"graph_snapshots":[{"event_id":"sha256:e4bf88f3be0ab6a2734c05eb3a13ae99fbd566b716818f908bd9d8e0d73e4781","target":"graph","created_at":"2026-07-05T05:38:11Z","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/2302.00711/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The numerical performance of algorithms can be studied using test sets or procedures that generate such problems. This paper proposes various methods for generating linear, semidefinite, and second-order cone optimization problems. Specifically, we are interested in problem instances requiring a known optimal solution, a known optimal partition, a specific interior solution, or all these together. In the proposed problem generators, different characteristics of optimization problems, including dimension, size, condition number, degeneracy, optimal partition, and sparsity, can be chosen to faci","authors_text":"Brandon Augustino, Mohammadhossein Mohammadisiahroudi, Ramin Fakhimi, Tam\\'as Terlaky","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"math.OC","submitted_at":"2023-02-01T19:08:15Z","title":"Generating Linear, Semidefinite, and Second-order Cone Optimization Problems for Numerical Experiments"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2302.00711","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":"sha256:2395d9063486af9ab4540d488bf092bdad14cd8c854dafabb439b29f385d772a","target":"record","created_at":"2026-07-05T05:38:11Z","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":"0872be2f6886f8b368ba7c2bbf81b334ce2505f9f66d2dfcde469c7fcaa45b9b","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"math.OC","submitted_at":"2023-02-01T19:08:15Z","title_canon_sha256":"35c5e825710f1498dbc22f789934180ab8059e23c7708be9f30f584e5ff9733f"},"schema_version":"1.0","source":{"id":"2302.00711","kind":"arxiv","version":1}},"canonical_sha256":"0baca06fd54446c8c3fb840509bb116c36cd7ebb0e48a81a892efc60dd92cc77","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"0baca06fd54446c8c3fb840509bb116c36cd7ebb0e48a81a892efc60dd92cc77","first_computed_at":"2026-07-05T05:38:11.473122Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:38:11.473122Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"gUY7eHmqW/TEObBAHtsG8IYe7kvo4JfDMG9xV0nqTjDJwj411EmrdtqdLQv4DCt2fBttJ7AlsNCbbuBn77plAQ==","signature_status":"signed_v1","signed_at":"2026-07-05T05:38:11.473585Z","signed_message":"canonical_sha256_bytes"},"source_id":"2302.00711","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:2395d9063486af9ab4540d488bf092bdad14cd8c854dafabb439b29f385d772a","sha256:e4bf88f3be0ab6a2734c05eb3a13ae99fbd566b716818f908bd9d8e0d73e4781"],"state_sha256":"da38371496576f20958f49243b05dfa822b55b14d6277641716d3a9791529b19"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"xsYAXBrxYK4pGfp+3bs8HI87/WX5hzXI+TJbX8Br6n6HhucFnoJnhegfZb3ntq3vA2psWM9BQOlvar9lHLEFCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-12T02:58:24.850587Z","bundle_sha256":"99c4e0f3087d2d929cafa4d1e706377d4ae190fa0e07206b8dce7c5db4078cb0"}}