{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:BXHUWWTRVSJPBUXJJMNVNLTXYV","short_pith_number":"pith:BXHUWWTR","canonical_record":{"source":{"id":"2509.00259","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-08-29T22:00:48Z","cross_cats_sorted":[],"title_canon_sha256":"0c605aee780265944be393584ccc53cfdb780d834dfa3727eb77c3fbbca6907e","abstract_canon_sha256":"261cabf9382198342f5123df7466103fa0552aa521b75e0b62dae767380eac37"},"schema_version":"1.0"},"canonical_sha256":"0dcf4b5a71ac92f0d2e94b1b56ae77c578d19da28beace29dfcbacb01f452362","source":{"kind":"arxiv","id":"2509.00259","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2509.00259","created_at":"2026-07-05T12:02:12Z"},{"alias_kind":"arxiv_version","alias_value":"2509.00259v1","created_at":"2026-07-05T12:02:12Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2509.00259","created_at":"2026-07-05T12:02:12Z"},{"alias_kind":"pith_short_12","alias_value":"BXHUWWTRVSJP","created_at":"2026-07-05T12:02:12Z"},{"alias_kind":"pith_short_16","alias_value":"BXHUWWTRVSJPBUXJ","created_at":"2026-07-05T12:02:12Z"},{"alias_kind":"pith_short_8","alias_value":"BXHUWWTR","created_at":"2026-07-05T12:02:12Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:BXHUWWTRVSJPBUXJJMNVNLTXYV","target":"record","payload":{"canonical_record":{"source":{"id":"2509.00259","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-08-29T22:00:48Z","cross_cats_sorted":[],"title_canon_sha256":"0c605aee780265944be393584ccc53cfdb780d834dfa3727eb77c3fbbca6907e","abstract_canon_sha256":"261cabf9382198342f5123df7466103fa0552aa521b75e0b62dae767380eac37"},"schema_version":"1.0"},"canonical_sha256":"0dcf4b5a71ac92f0d2e94b1b56ae77c578d19da28beace29dfcbacb01f452362","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T12:02:12.465834Z","signature_b64":"/WJ0tLNGLVKo/4r/HUWEN4ewkCGG+S7POG0yJ9AEK1k+COWXfLn71gG0HTWa+LdwaD4RQvsktE3yzfdOk1lNAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"0dcf4b5a71ac92f0d2e94b1b56ae77c578d19da28beace29dfcbacb01f452362","last_reissued_at":"2026-07-05T12:02:12.465394Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T12:02:12.465394Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2509.00259","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":"2026-07-05T12:02:12Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"vpEM691Av+3h2Qwpx/rTPp99Ku+o+GGChtsVQQl9u5/sp2ux08PV9sY2xuSa8fReXuuNSijDG2GgIOq2dx+iBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T05:48:04.982037Z"},"content_sha256":"454da8f689958f72d92a981e7b4d23f2d9cbbae1eb9d024d5a0a365af152baa0","schema_version":"1.0","event_id":"sha256:454da8f689958f72d92a981e7b4d23f2d9cbbae1eb9d024d5a0a365af152baa0"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:BXHUWWTRVSJPBUXJJMNVNLTXYV","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Quantum-Optimized Selective State Space Model for Efficient Time Series Prediction","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Alexandru Topirceanu, Mihai Udrescu, Stefan-Alexandru Jura","submitted_at":"2025-08-29T22:00:48Z","abstract_excerpt":"Long-range time series forecasting remains challenging, as it requires capturing non-stationary and multi-scale temporal dependencies while maintaining noise robustness, efficiency, and stability. Transformer-based architectures such as Autoformer and Informer improve generalization but suffer from quadratic complexity and degraded performance on very long time horizons. State space models, notably S-Mamba, provide linear-time updates but often face unstable training dynamics, sensitivity to initialization, and limited robustness for multivariate forecasting. To address such challenges, we pro"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2509.00259","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/2509.00259/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":"2026-07-05T12:02:12Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"1qRe/6f3v/xlFkxiU/J7t1WSZmMPx3GSC/zeNfVnAkqufPwwGPjOrxvVCf/KaC1sOfD46vnVo5EMijneKgtqCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T05:48:04.982418Z"},"content_sha256":"bfeefec0ec0beca71b0152de81426693bb581b30f76f3dd8a79a0bb8aee84ff3","schema_version":"1.0","event_id":"sha256:bfeefec0ec0beca71b0152de81426693bb581b30f76f3dd8a79a0bb8aee84ff3"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/BXHUWWTRVSJPBUXJJMNVNLTXYV/bundle.json","state_url":"https://pith.science/pith/BXHUWWTRVSJPBUXJJMNVNLTXYV/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/BXHUWWTRVSJPBUXJJMNVNLTXYV/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":"2026-08-19T05:48:04Z","links":{"resolver":"https://pith.science/pith/BXHUWWTRVSJPBUXJJMNVNLTXYV","bundle":"https://pith.science/pith/BXHUWWTRVSJPBUXJJMNVNLTXYV/bundle.json","state":"https://pith.science/pith/BXHUWWTRVSJPBUXJJMNVNLTXYV/state.json","well_known_bundle":"https://pith.science/.well-known/pith/BXHUWWTRVSJPBUXJJMNVNLTXYV/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:BXHUWWTRVSJPBUXJJMNVNLTXYV","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":"261cabf9382198342f5123df7466103fa0552aa521b75e0b62dae767380eac37","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-08-29T22:00:48Z","title_canon_sha256":"0c605aee780265944be393584ccc53cfdb780d834dfa3727eb77c3fbbca6907e"},"schema_version":"1.0","source":{"id":"2509.00259","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2509.00259","created_at":"2026-07-05T12:02:12Z"},{"alias_kind":"arxiv_version","alias_value":"2509.00259v1","created_at":"2026-07-05T12:02:12Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2509.00259","created_at":"2026-07-05T12:02:12Z"},{"alias_kind":"pith_short_12","alias_value":"BXHUWWTRVSJP","created_at":"2026-07-05T12:02:12Z"},{"alias_kind":"pith_short_16","alias_value":"BXHUWWTRVSJPBUXJ","created_at":"2026-07-05T12:02:12Z"},{"alias_kind":"pith_short_8","alias_value":"BXHUWWTR","created_at":"2026-07-05T12:02:12Z"}],"graph_snapshots":[{"event_id":"sha256:bfeefec0ec0beca71b0152de81426693bb581b30f76f3dd8a79a0bb8aee84ff3","target":"graph","created_at":"2026-07-05T12:02:12Z","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/2509.00259/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Long-range time series forecasting remains challenging, as it requires capturing non-stationary and multi-scale temporal dependencies while maintaining noise robustness, efficiency, and stability. Transformer-based architectures such as Autoformer and Informer improve generalization but suffer from quadratic complexity and degraded performance on very long time horizons. State space models, notably S-Mamba, provide linear-time updates but often face unstable training dynamics, sensitivity to initialization, and limited robustness for multivariate forecasting. To address such challenges, we pro","authors_text":"Alexandru Topirceanu, Mihai Udrescu, Stefan-Alexandru Jura","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-08-29T22:00:48Z","title":"Quantum-Optimized Selective State Space Model for Efficient Time Series Prediction"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2509.00259","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":"sha256:454da8f689958f72d92a981e7b4d23f2d9cbbae1eb9d024d5a0a365af152baa0","target":"record","created_at":"2026-07-05T12:02:12Z","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":"261cabf9382198342f5123df7466103fa0552aa521b75e0b62dae767380eac37","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-08-29T22:00:48Z","title_canon_sha256":"0c605aee780265944be393584ccc53cfdb780d834dfa3727eb77c3fbbca6907e"},"schema_version":"1.0","source":{"id":"2509.00259","kind":"arxiv","version":1}},"canonical_sha256":"0dcf4b5a71ac92f0d2e94b1b56ae77c578d19da28beace29dfcbacb01f452362","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"0dcf4b5a71ac92f0d2e94b1b56ae77c578d19da28beace29dfcbacb01f452362","first_computed_at":"2026-07-05T12:02:12.465394Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T12:02:12.465394Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"/WJ0tLNGLVKo/4r/HUWEN4ewkCGG+S7POG0yJ9AEK1k+COWXfLn71gG0HTWa+LdwaD4RQvsktE3yzfdOk1lNAQ==","signature_status":"signed_v1","signed_at":"2026-07-05T12:02:12.465834Z","signed_message":"canonical_sha256_bytes"},"source_id":"2509.00259","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:454da8f689958f72d92a981e7b4d23f2d9cbbae1eb9d024d5a0a365af152baa0","sha256:bfeefec0ec0beca71b0152de81426693bb581b30f76f3dd8a79a0bb8aee84ff3"],"state_sha256":"b7b8e1576aeb4102fbb531b2dc257ecd240abfabaa10478d44cdb0cffd1b9a6f"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"jWZWiMsyCpF0egM1iuz7v0V91zvwTkaV2s5U/MKYfKZRv3Rbl2XPHHjvtsRjH+lejuyg2+4kUG22n20ga30BBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-19T05:48:04.984761Z","bundle_sha256":"9e498a3777b7c60f80f2a1ebc3895d50ee84423ab167d566312543f7558845f3"}}