{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:ATBF2NPEJCH76R6CPUJBQI7OYB","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":"6ec076e6949ab2700de683405f946db0084b4636cea33f10f1544adee2d70c21","cross_cats_sorted":["cs.NA","math.NA"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"math.OC","submitted_at":"2026-06-04T02:41:16Z","title_canon_sha256":"cf25850cf054e5eafc595cb788f9e391ebb5517145d1da5b73eee7a4bd052c2e"},"schema_version":"1.0","source":{"id":"2606.05617","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.05617","created_at":"2026-06-05T01:14:56Z"},{"alias_kind":"arxiv_version","alias_value":"2606.05617v1","created_at":"2026-06-05T01:14:56Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.05617","created_at":"2026-06-05T01:14:56Z"},{"alias_kind":"pith_short_12","alias_value":"ATBF2NPEJCH7","created_at":"2026-06-05T01:14:56Z"},{"alias_kind":"pith_short_16","alias_value":"ATBF2NPEJCH76R6C","created_at":"2026-06-05T01:14:56Z"},{"alias_kind":"pith_short_8","alias_value":"ATBF2NPE","created_at":"2026-06-05T01:14:56Z"}],"graph_snapshots":[{"event_id":"sha256:8068b7dba1040b896981102588ab1026188fdd40e31a1cfa7642956f74a6c94c","target":"graph","created_at":"2026-06-05T01:14:56Z","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/2606.05617/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We develop parallel and batch-cutting variants of the norm-minimization-based outer approximation algorithm for convex vector optimization. The standard algorithm solves $N_k$ independent subproblems at each iteration~$k$ to evaluate all vertices of the current polyhedral approximation, but processes only the single best cut. We propose two improvements. First, we parallelize the \\revise{subproblem evaluations} across $\\nw$ workers, reducing per-iteration wall-clock time. Second, we introduce a batch-cutting strategy that adds up to $K$ supporting halfspaces per iteration, using information fr","authors_text":"Mohammed Alshahrani","cross_cats":["cs.NA","math.NA"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"math.OC","submitted_at":"2026-06-04T02:41:16Z","title":"On Parallel and Batch-Cutting Strategies for Norm-Minimization-Based Convex Vector Optimization"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.05617","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":"sha256:8d8237bb6048040621ded4ae5e3670217d0c39b5259ce938a652c795613b9d56","target":"record","created_at":"2026-06-05T01:14:56Z","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":"6ec076e6949ab2700de683405f946db0084b4636cea33f10f1544adee2d70c21","cross_cats_sorted":["cs.NA","math.NA"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"math.OC","submitted_at":"2026-06-04T02:41:16Z","title_canon_sha256":"cf25850cf054e5eafc595cb788f9e391ebb5517145d1da5b73eee7a4bd052c2e"},"schema_version":"1.0","source":{"id":"2606.05617","kind":"arxiv","version":1}},"canonical_sha256":"04c25d35e4488fff47c27d121823eec05376e18ffbea8610092d034635758233","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"04c25d35e4488fff47c27d121823eec05376e18ffbea8610092d034635758233","first_computed_at":"2026-06-05T01:14:56.575411Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-05T01:14:56.575411Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"fnb7CqV+T9D7aQUyDfUSQJ6qwIiAstpfznq67wo5oXQFrmq/AZZAFCI4uJoWnMIncUyPn/11QdhsSxAu6prkCw==","signature_status":"signed_v1","signed_at":"2026-06-05T01:14:56.575842Z","signed_message":"canonical_sha256_bytes"},"source_id":"2606.05617","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:8d8237bb6048040621ded4ae5e3670217d0c39b5259ce938a652c795613b9d56","sha256:8068b7dba1040b896981102588ab1026188fdd40e31a1cfa7642956f74a6c94c"],"state_sha256":"95e7bad333045d14ff0d1c34e778990a9d3510c9aa2ebf850f8e5ba3841799bd"}