{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:LT6QTKWUIQKMJKU5QJFVCCVWXE","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":"8a65176d2f3ffbe31e59ec3c9422d5042e75ed551aea4b3e36d1d941ff5eb93f","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2017-02-01T19:24:05Z","title_canon_sha256":"cdeee7666feaa48550b0d8a172eed6801c006eca6eb84ad7c90360fd146f76b0"},"schema_version":"1.0","source":{"id":"1702.00422","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1702.00422","created_at":"2026-05-18T00:51:33Z"},{"alias_kind":"arxiv_version","alias_value":"1702.00422v1","created_at":"2026-05-18T00:51:33Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1702.00422","created_at":"2026-05-18T00:51:33Z"},{"alias_kind":"pith_short_12","alias_value":"LT6QTKWUIQKM","created_at":"2026-05-18T12:31:28Z"},{"alias_kind":"pith_short_16","alias_value":"LT6QTKWUIQKMJKU5","created_at":"2026-05-18T12:31:28Z"},{"alias_kind":"pith_short_8","alias_value":"LT6QTKWU","created_at":"2026-05-18T12:31:28Z"}],"graph_snapshots":[{"event_id":"sha256:1efa320870a07c1dfcd49918f7f2224cc43065d5f5cdaeb0320d97902fc85244","target":"graph","created_at":"2026-05-18T00:51:33Z","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"},"paper":{"abstract_excerpt":"This paper develops a unified methodology for probabilistic analysis and optimal control design for jump diffusion processes defined by polynomials. For such systems, the evolution of the moments of the state can be described via a system of linear ordinary differential equations. Typically, however, the moments are not closed and an infinite system of equations is required to compute statistical moments exactly. Existing methods for stochastic analysis, known as closure methods, focus on approximating this infinite system of equations with a finite dimensional system. This work develops an al","authors_text":"Abhyudai Singh, Andrew Lamperski, Khem Raj Ghusinga","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2017-02-01T19:24:05Z","title":"Analysis and Control of Stochastic Systems using Semidefinite Programming over Moments"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1702.00422","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:fce86091a9fa71d8ba4214d62c9de126c29cdd89f282ac53ca4760bc65107c29","target":"record","created_at":"2026-05-18T00:51:33Z","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":"8a65176d2f3ffbe31e59ec3c9422d5042e75ed551aea4b3e36d1d941ff5eb93f","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2017-02-01T19:24:05Z","title_canon_sha256":"cdeee7666feaa48550b0d8a172eed6801c006eca6eb84ad7c90360fd146f76b0"},"schema_version":"1.0","source":{"id":"1702.00422","kind":"arxiv","version":1}},"canonical_sha256":"5cfd09aad44414c4aa9d824b510ab6b927968a536099b448dc7e366974a14e5a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5cfd09aad44414c4aa9d824b510ab6b927968a536099b448dc7e366974a14e5a","first_computed_at":"2026-05-18T00:51:33.578399Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:51:33.578399Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"N7rGVm+HP6ko2E7rkN+Fzxp/2RRvCDYj5oS6A2Z20c/CrrF/bmrtb+h8lwramdDnOL+wKfH5N2NIstCkRjtCAw==","signature_status":"signed_v1","signed_at":"2026-05-18T00:51:33.578804Z","signed_message":"canonical_sha256_bytes"},"source_id":"1702.00422","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:fce86091a9fa71d8ba4214d62c9de126c29cdd89f282ac53ca4760bc65107c29","sha256:1efa320870a07c1dfcd49918f7f2224cc43065d5f5cdaeb0320d97902fc85244"],"state_sha256":"96437da32ce85ab6c8f73c570b323aa89f7ee66e3ead83c7f1fd5a55628e7c3f"}