{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:DVITGJLQTVX35FVQVI4V7AHG42","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":"88597b5e4abd8fe0ec1eb0ee9fcbe8d6e4b731e81caa94d9a0aec1790c0749af","cross_cats_sorted":["stat.ME","stat.TH"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"math.ST","submitted_at":"2025-07-03T11:53:31Z","title_canon_sha256":"7d6d6e9baf64319e2c287ff02da55db920b106db6ca5d9e7f68f03e56986645e"},"schema_version":"1.0","source":{"id":"2507.02552","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2507.02552","created_at":"2026-06-02T03:04:33Z"},{"alias_kind":"arxiv_version","alias_value":"2507.02552v4","created_at":"2026-06-02T03:04:33Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.02552","created_at":"2026-06-02T03:04:33Z"},{"alias_kind":"pith_short_12","alias_value":"DVITGJLQTVX3","created_at":"2026-06-02T03:04:33Z"},{"alias_kind":"pith_short_16","alias_value":"DVITGJLQTVX35FVQ","created_at":"2026-06-02T03:04:33Z"},{"alias_kind":"pith_short_8","alias_value":"DVITGJLQ","created_at":"2026-06-02T03:04:33Z"}],"graph_snapshots":[{"event_id":"sha256:05717de1b778a2e537568debbe3a6b405ea1424306db88ed8ed442bd06cc5579","target":"graph","created_at":"2026-06-02T03:04:33Z","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"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2507.02552/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"This paper investigates the detection and estimation of a single change in high-dimensional linear models. We derive minimax lower bounds for the detection boundary and the estimation rate, which uncover a phase transition governed by the sparsity of the covariance-weighted differential parameter. This form of \"inherent sparsity\" captures a delicate interplay between the covariance structure of the regressors and the change in regression coefficients on the detectability of a change point. Complementing the lower bounds, we introduce two covariance scanning-based methods, McScan and QcSan, whi","authors_text":"Haeran Cho, Housen Li","cross_cats":["stat.ME","stat.TH"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"math.ST","submitted_at":"2025-07-03T11:53:31Z","title":"Covariance scanning for adaptively optimal change point detection in high-dimensional linear models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.02552","kind":"arxiv","version":4},"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":"sha256:3c4ad75260b8c83e77f2a6d9d21fcab9c66ff5828cc43fccb805191a67f617cf","target":"record","created_at":"2026-06-02T03:04:33Z","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":"88597b5e4abd8fe0ec1eb0ee9fcbe8d6e4b731e81caa94d9a0aec1790c0749af","cross_cats_sorted":["stat.ME","stat.TH"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"math.ST","submitted_at":"2025-07-03T11:53:31Z","title_canon_sha256":"7d6d6e9baf64319e2c287ff02da55db920b106db6ca5d9e7f68f03e56986645e"},"schema_version":"1.0","source":{"id":"2507.02552","kind":"arxiv","version":4}},"canonical_sha256":"1d513325709d6fbe96b0aa395f80e6e69fef5992745b9026dd61cee12b343297","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"1d513325709d6fbe96b0aa395f80e6e69fef5992745b9026dd61cee12b343297","first_computed_at":"2026-06-02T03:04:33.277615Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-02T03:04:33.277615Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ZYnyKejpS+ncVTE/E+ukr/oY90iL+DIcLSyxUtq2FIbYChYGkBG8FpRVMsogX4NN7jEbLosYPjnfrVCdI0vSDg==","signature_status":"signed_v1","signed_at":"2026-06-02T03:04:33.278102Z","signed_message":"canonical_sha256_bytes"},"source_id":"2507.02552","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:3c4ad75260b8c83e77f2a6d9d21fcab9c66ff5828cc43fccb805191a67f617cf","sha256:05717de1b778a2e537568debbe3a6b405ea1424306db88ed8ed442bd06cc5579"],"state_sha256":"8e4a2949f646eb99945c7bc2d493ec79bf2570deabd1aab56db803cf73839bcc"}