{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:2Y5PRXLUYDILM4SPXMJCZQJAWX","short_pith_number":"pith:2Y5PRXLU","schema_version":"1.0","canonical_sha256":"d63af8dd74c0d0b6724fbb122cc120b5efdeec8fc1b418c4bb3815565aa86ff7","source":{"kind":"arxiv","id":"2508.11938","version":1},"attestation_state":"computed","paper":{"title":"Wavelets for power spectral density estimation of gravitational wave data","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["astro-ph.IM","physics.data-an"],"primary_cat":"gr-qc","authors_text":"Chao-Wan-Zhen Wang, Fu-Wen Shu, Guo-Qing Huang, Jin-Bao Zhu","submitted_at":"2025-08-16T06:41:58Z","abstract_excerpt":"Power spectral density (PSD) estimation is a critical step in gravitational wave (GW) detectors data analysis. The Welch method is a typical non-parametric spectral estimation approach that estimates the PSD of stationary noise by averaging periodograms of several time segments, or by taking the median of periodograms to adapt to non-stationary noise. In this work, we propose a wavelet-based approach for fast PSD estimation of both stationary and non-stationary noise. For stationary noise, we apply wavelet smoothing to the periodogram, avoiding the segmentation step in the Welch method, and en"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2508.11938","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"gr-qc","submitted_at":"2025-08-16T06:41:58Z","cross_cats_sorted":["astro-ph.IM","physics.data-an"],"title_canon_sha256":"26c7b0937b1ccd791954b3ab08f3a8ff2f25de73e49afc0c7ad8bdc46514844e","abstract_canon_sha256":"f38b34561d3bdaf8eb7ca25ee2164b2c5565104e0c9ddc4c47ab6cdc4dca6545"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:54:57.445740Z","signature_b64":"QhTiWVY5QnsmfdXbORSDI7g7Q+GOKdpwXb7e6e3ONKC8T/RfdE9/8QOVmyDUvHuewW06J/V33ngSDT0kQSe/Bg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d63af8dd74c0d0b6724fbb122cc120b5efdeec8fc1b418c4bb3815565aa86ff7","last_reissued_at":"2026-07-05T11:54:57.445331Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:54:57.445331Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Wavelets for power spectral density estimation of gravitational wave data","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["astro-ph.IM","physics.data-an"],"primary_cat":"gr-qc","authors_text":"Chao-Wan-Zhen Wang, Fu-Wen Shu, Guo-Qing Huang, Jin-Bao Zhu","submitted_at":"2025-08-16T06:41:58Z","abstract_excerpt":"Power spectral density (PSD) estimation is a critical step in gravitational wave (GW) detectors data analysis. The Welch method is a typical non-parametric spectral estimation approach that estimates the PSD of stationary noise by averaging periodograms of several time segments, or by taking the median of periodograms to adapt to non-stationary noise. In this work, we propose a wavelet-based approach for fast PSD estimation of both stationary and non-stationary noise. For stationary noise, we apply wavelet smoothing to the periodogram, avoiding the segmentation step in the Welch method, and en"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2508.11938","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/2508.11938/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2508.11938","created_at":"2026-07-05T11:54:57.445390+00:00"},{"alias_kind":"arxiv_version","alias_value":"2508.11938v1","created_at":"2026-07-05T11:54:57.445390+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2508.11938","created_at":"2026-07-05T11:54:57.445390+00:00"},{"alias_kind":"pith_short_12","alias_value":"2Y5PRXLUYDIL","created_at":"2026-07-05T11:54:57.445390+00:00"},{"alias_kind":"pith_short_16","alias_value":"2Y5PRXLUYDILM4SP","created_at":"2026-07-05T11:54:57.445390+00:00"},{"alias_kind":"pith_short_8","alias_value":"2Y5PRXLU","created_at":"2026-07-05T11:54:57.445390+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/2Y5PRXLUYDILM4SPXMJCZQJAWX","json":"https://pith.science/pith/2Y5PRXLUYDILM4SPXMJCZQJAWX.json","graph_json":"https://pith.science/api/pith-number/2Y5PRXLUYDILM4SPXMJCZQJAWX/graph.json","events_json":"https://pith.science/api/pith-number/2Y5PRXLUYDILM4SPXMJCZQJAWX/events.json","paper":"https://pith.science/paper/2Y5PRXLU"},"agent_actions":{"view_html":"https://pith.science/pith/2Y5PRXLUYDILM4SPXMJCZQJAWX","download_json":"https://pith.science/pith/2Y5PRXLUYDILM4SPXMJCZQJAWX.json","view_paper":"https://pith.science/paper/2Y5PRXLU","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2508.11938&json=true","fetch_graph":"https://pith.science/api/pith-number/2Y5PRXLUYDILM4SPXMJCZQJAWX/graph.json","fetch_events":"https://pith.science/api/pith-number/2Y5PRXLUYDILM4SPXMJCZQJAWX/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/2Y5PRXLUYDILM4SPXMJCZQJAWX/action/timestamp_anchor","attest_storage":"https://pith.science/pith/2Y5PRXLUYDILM4SPXMJCZQJAWX/action/storage_attestation","attest_author":"https://pith.science/pith/2Y5PRXLUYDILM4SPXMJCZQJAWX/action/author_attestation","sign_citation":"https://pith.science/pith/2Y5PRXLUYDILM4SPXMJCZQJAWX/action/citation_signature","submit_replication":"https://pith.science/pith/2Y5PRXLUYDILM4SPXMJCZQJAWX/action/replication_record"}},"created_at":"2026-07-05T11:54:57.445390+00:00","updated_at":"2026-07-05T11:54:57.445390+00:00"}