{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:TSF5EUW3G6NZN72W5T3P6XR6HP","short_pith_number":"pith:TSF5EUW3","schema_version":"1.0","canonical_sha256":"9c8bd252db379b96ff56ecf6ff5e3e3bd3d80b719920bd83a48d931ea483b7f2","source":{"kind":"arxiv","id":"2402.14276","version":1},"attestation_state":"computed","paper":{"title":"Bispectrum Unbiasing for Dilation-Invariant Multi-reference Alignment","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.IT","math.IT"],"primary_cat":"eess.SP","authors_text":"Anna Little, Liping Yin, Matthew Hirn","submitted_at":"2024-02-22T04:31:19Z","abstract_excerpt":"Motivated by modern data applications such as cryo-electron microscopy, the goal of classic multi-reference alignment (MRA) is to recover an unknown signal $f: \\mathbb{R} \\to \\mathbb{R}$ from many observations that have been randomly translated and corrupted by additive noise. We consider a generalization of classic MRA where signals are also corrupted by a random scale change, i.e. dilation. We propose a novel data-driven unbiasing procedure which can recover an unbiased estimator of the bispectrum of the unknown signal, given knowledge of the dilation distribution. Lastly, we invert the reco"},"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":"2402.14276","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.SP","submitted_at":"2024-02-22T04:31:19Z","cross_cats_sorted":["cs.IT","math.IT"],"title_canon_sha256":"d0d3a2341a2708e789824a9bb52eca71c0ac02f3db49ad2a28ee324e73eb6c87","abstract_canon_sha256":"83d2bce967299dead041b2df270e1e2dafcb9fd2ab4b29cf85fd76bb0be4d2ac"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:48:07.982195Z","signature_b64":"kwr+dDxUWAI7aWbWAdTWPiBjYfaZ9iQ7B6PXSG6rCKt33Cq3+cFxzIM6FVKvpSjSpujn6X++yKjZWJ0Ct5EgBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"9c8bd252db379b96ff56ecf6ff5e3e3bd3d80b719920bd83a48d931ea483b7f2","last_reissued_at":"2026-07-05T07:48:07.981729Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:48:07.981729Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Bispectrum Unbiasing for Dilation-Invariant Multi-reference Alignment","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.IT","math.IT"],"primary_cat":"eess.SP","authors_text":"Anna Little, Liping Yin, Matthew Hirn","submitted_at":"2024-02-22T04:31:19Z","abstract_excerpt":"Motivated by modern data applications such as cryo-electron microscopy, the goal of classic multi-reference alignment (MRA) is to recover an unknown signal $f: \\mathbb{R} \\to \\mathbb{R}$ from many observations that have been randomly translated and corrupted by additive noise. We consider a generalization of classic MRA where signals are also corrupted by a random scale change, i.e. dilation. We propose a novel data-driven unbiasing procedure which can recover an unbiased estimator of the bispectrum of the unknown signal, given knowledge of the dilation distribution. Lastly, we invert the reco"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2402.14276","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/2402.14276/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":"2402.14276","created_at":"2026-07-05T07:48:07.981786+00:00"},{"alias_kind":"arxiv_version","alias_value":"2402.14276v1","created_at":"2026-07-05T07:48:07.981786+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2402.14276","created_at":"2026-07-05T07:48:07.981786+00:00"},{"alias_kind":"pith_short_12","alias_value":"TSF5EUW3G6NZ","created_at":"2026-07-05T07:48:07.981786+00:00"},{"alias_kind":"pith_short_16","alias_value":"TSF5EUW3G6NZN72W","created_at":"2026-07-05T07:48:07.981786+00:00"},{"alias_kind":"pith_short_8","alias_value":"TSF5EUW3","created_at":"2026-07-05T07:48:07.981786+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":1,"sample":[{"citing_arxiv_id":"2411.17434","citing_title":"Recovering a group from few orbits","ref_index":57,"is_internal_anchor":true}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/TSF5EUW3G6NZN72W5T3P6XR6HP","json":"https://pith.science/pith/TSF5EUW3G6NZN72W5T3P6XR6HP.json","graph_json":"https://pith.science/api/pith-number/TSF5EUW3G6NZN72W5T3P6XR6HP/graph.json","events_json":"https://pith.science/api/pith-number/TSF5EUW3G6NZN72W5T3P6XR6HP/events.json","paper":"https://pith.science/paper/TSF5EUW3"},"agent_actions":{"view_html":"https://pith.science/pith/TSF5EUW3G6NZN72W5T3P6XR6HP","download_json":"https://pith.science/pith/TSF5EUW3G6NZN72W5T3P6XR6HP.json","view_paper":"https://pith.science/paper/TSF5EUW3","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2402.14276&json=true","fetch_graph":"https://pith.science/api/pith-number/TSF5EUW3G6NZN72W5T3P6XR6HP/graph.json","fetch_events":"https://pith.science/api/pith-number/TSF5EUW3G6NZN72W5T3P6XR6HP/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/TSF5EUW3G6NZN72W5T3P6XR6HP/action/timestamp_anchor","attest_storage":"https://pith.science/pith/TSF5EUW3G6NZN72W5T3P6XR6HP/action/storage_attestation","attest_author":"https://pith.science/pith/TSF5EUW3G6NZN72W5T3P6XR6HP/action/author_attestation","sign_citation":"https://pith.science/pith/TSF5EUW3G6NZN72W5T3P6XR6HP/action/citation_signature","submit_replication":"https://pith.science/pith/TSF5EUW3G6NZN72W5T3P6XR6HP/action/replication_record"}},"created_at":"2026-07-05T07:48:07.981786+00:00","updated_at":"2026-07-05T07:48:07.981786+00:00"}