{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:E5VUUKLA6NYUAU22LG2PN4PXYR","short_pith_number":"pith:E5VUUKLA","canonical_record":{"source":{"id":"1905.12442","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2019-05-29T13:34:29Z","cross_cats_sorted":["cs.DS","cs.IT","math.IT","stat.TH"],"title_canon_sha256":"52756e06a439c74bc004c86a5da43a58b8e5bf2a254195255a6cc136217df1f1","abstract_canon_sha256":"c08baafe8e399435641ea9dfe26922655bd7a7247861b0527b2bf0a0737d3436"},"schema_version":"1.0"},"canonical_sha256":"276b4a2960f37140535a59b4f6f1f7c46dc033277e693a8376955cd21bbecd4c","source":{"kind":"arxiv","id":"1905.12442","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1905.12442","created_at":"2026-05-17T23:44:18Z"},{"alias_kind":"arxiv_version","alias_value":"1905.12442v2","created_at":"2026-05-17T23:44:18Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1905.12442","created_at":"2026-05-17T23:44:18Z"},{"alias_kind":"pith_short_12","alias_value":"E5VUUKLA6NYU","created_at":"2026-05-18T12:33:15Z"},{"alias_kind":"pith_short_16","alias_value":"E5VUUKLA6NYUAU22","created_at":"2026-05-18T12:33:15Z"},{"alias_kind":"pith_short_8","alias_value":"E5VUUKLA","created_at":"2026-05-18T12:33:15Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:E5VUUKLA6NYUAU22LG2PN4PXYR","target":"record","payload":{"canonical_record":{"source":{"id":"1905.12442","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2019-05-29T13:34:29Z","cross_cats_sorted":["cs.DS","cs.IT","math.IT","stat.TH"],"title_canon_sha256":"52756e06a439c74bc004c86a5da43a58b8e5bf2a254195255a6cc136217df1f1","abstract_canon_sha256":"c08baafe8e399435641ea9dfe26922655bd7a7247861b0527b2bf0a0737d3436"},"schema_version":"1.0"},"canonical_sha256":"276b4a2960f37140535a59b4f6f1f7c46dc033277e693a8376955cd21bbecd4c","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:44:18.415679Z","signature_b64":"7zGPcLjaLUlTQdulvOvxwSkV2s4QlAwPbA+durFDhQ9Qx//lKriWoX7L6CbRE5mM8pZfvPZipWjuoeuvFqyJDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"276b4a2960f37140535a59b4f6f1f7c46dc033277e693a8376955cd21bbecd4c","last_reissued_at":"2026-05-17T23:44:18.414964Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:44:18.414964Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1905.12442","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-17T23:44:18Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"9LIjBKGd5GHqTFovl8TwzfwIWCzDucNWXQXii2puOrvEal6rtia3Ntt3ffjuWze5UtsHAIrlFNFOaet8zYCjDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-12T06:58:13.238364Z"},"content_sha256":"d81c139e7842a97a0fddcebc91b3a9d017e826aa7edbd725cc82f5fe960dab7b","schema_version":"1.0","event_id":"sha256:d81c139e7842a97a0fddcebc91b3a9d017e826aa7edbd725cc82f5fe960dab7b"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:E5VUUKLA6NYUAU22LG2PN4PXYR","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Rank-one Multi-Reference Factor Analysis","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.DS","cs.IT","math.IT","stat.TH"],"primary_cat":"math.ST","authors_text":"Boris Landa, Yariv Aizenbud, Yoel Shkolnisky","submitted_at":"2019-05-29T13:34:29Z","abstract_excerpt":"In recent years, there is a growing need for processing methods aimed at extracting useful information from large datasets. In many cases the challenge is to discover a low-dimensional structure in the data, often concealed by the existence of nuisance parameters and noise. Motivated by such challenges, we consider the problem of estimating a signal from its scaled, cyclically-shifted and noisy observations. We focus on the particularly challenging regime of low signal-to-noise ratio (SNR), where different observations cannot be shift-aligned. We show that an accurate estimation of the signal "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1905.12442","kind":"arxiv","version":2},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"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":"2026-05-17T23:44:18Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"peV7MnLnwCrqFXMDFbVSOb/Sjk8COwttQbSlxh/yb0j5YgLOdlplQzN8eUTb/tN0mf7UZuRRMZC9JUyEQuHqCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-12T06:58:13.239054Z"},"content_sha256":"9cc201c8a467b307e363e582103ae4a8e388168bc48f485d75adc6c556f93334","schema_version":"1.0","event_id":"sha256:9cc201c8a467b307e363e582103ae4a8e388168bc48f485d75adc6c556f93334"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/E5VUUKLA6NYUAU22LG2PN4PXYR/bundle.json","state_url":"https://pith.science/pith/E5VUUKLA6NYUAU22LG2PN4PXYR/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/E5VUUKLA6NYUAU22LG2PN4PXYR/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":"2026-06-12T06:58:13Z","links":{"resolver":"https://pith.science/pith/E5VUUKLA6NYUAU22LG2PN4PXYR","bundle":"https://pith.science/pith/E5VUUKLA6NYUAU22LG2PN4PXYR/bundle.json","state":"https://pith.science/pith/E5VUUKLA6NYUAU22LG2PN4PXYR/state.json","well_known_bundle":"https://pith.science/.well-known/pith/E5VUUKLA6NYUAU22LG2PN4PXYR/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:E5VUUKLA6NYUAU22LG2PN4PXYR","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":"c08baafe8e399435641ea9dfe26922655bd7a7247861b0527b2bf0a0737d3436","cross_cats_sorted":["cs.DS","cs.IT","math.IT","stat.TH"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2019-05-29T13:34:29Z","title_canon_sha256":"52756e06a439c74bc004c86a5da43a58b8e5bf2a254195255a6cc136217df1f1"},"schema_version":"1.0","source":{"id":"1905.12442","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1905.12442","created_at":"2026-05-17T23:44:18Z"},{"alias_kind":"arxiv_version","alias_value":"1905.12442v2","created_at":"2026-05-17T23:44:18Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1905.12442","created_at":"2026-05-17T23:44:18Z"},{"alias_kind":"pith_short_12","alias_value":"E5VUUKLA6NYU","created_at":"2026-05-18T12:33:15Z"},{"alias_kind":"pith_short_16","alias_value":"E5VUUKLA6NYUAU22","created_at":"2026-05-18T12:33:15Z"},{"alias_kind":"pith_short_8","alias_value":"E5VUUKLA","created_at":"2026-05-18T12:33:15Z"}],"graph_snapshots":[{"event_id":"sha256:9cc201c8a467b307e363e582103ae4a8e388168bc48f485d75adc6c556f93334","target":"graph","created_at":"2026-05-17T23:44:18Z","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":"In recent years, there is a growing need for processing methods aimed at extracting useful information from large datasets. In many cases the challenge is to discover a low-dimensional structure in the data, often concealed by the existence of nuisance parameters and noise. Motivated by such challenges, we consider the problem of estimating a signal from its scaled, cyclically-shifted and noisy observations. We focus on the particularly challenging regime of low signal-to-noise ratio (SNR), where different observations cannot be shift-aligned. We show that an accurate estimation of the signal ","authors_text":"Boris Landa, Yariv Aizenbud, Yoel Shkolnisky","cross_cats":["cs.DS","cs.IT","math.IT","stat.TH"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2019-05-29T13:34:29Z","title":"Rank-one Multi-Reference Factor Analysis"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1905.12442","kind":"arxiv","version":2},"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:d81c139e7842a97a0fddcebc91b3a9d017e826aa7edbd725cc82f5fe960dab7b","target":"record","created_at":"2026-05-17T23:44:18Z","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":"c08baafe8e399435641ea9dfe26922655bd7a7247861b0527b2bf0a0737d3436","cross_cats_sorted":["cs.DS","cs.IT","math.IT","stat.TH"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2019-05-29T13:34:29Z","title_canon_sha256":"52756e06a439c74bc004c86a5da43a58b8e5bf2a254195255a6cc136217df1f1"},"schema_version":"1.0","source":{"id":"1905.12442","kind":"arxiv","version":2}},"canonical_sha256":"276b4a2960f37140535a59b4f6f1f7c46dc033277e693a8376955cd21bbecd4c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"276b4a2960f37140535a59b4f6f1f7c46dc033277e693a8376955cd21bbecd4c","first_computed_at":"2026-05-17T23:44:18.414964Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:44:18.414964Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"7zGPcLjaLUlTQdulvOvxwSkV2s4QlAwPbA+durFDhQ9Qx//lKriWoX7L6CbRE5mM8pZfvPZipWjuoeuvFqyJDA==","signature_status":"signed_v1","signed_at":"2026-05-17T23:44:18.415679Z","signed_message":"canonical_sha256_bytes"},"source_id":"1905.12442","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d81c139e7842a97a0fddcebc91b3a9d017e826aa7edbd725cc82f5fe960dab7b","sha256:9cc201c8a467b307e363e582103ae4a8e388168bc48f485d75adc6c556f93334"],"state_sha256":"335b3c49297ab9c8caca1094b3ec4234f6d6b1f48faffdcf4fa9de4ff916993a"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"SAaJOeN6GtpQYsjFcPwA6IefQTyMjHKQzCrhC0DkVH3OtzwYEDLdk1S6epFC2v7+qvQxL8RF6tO1Gfz8DrIlAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-12T06:58:13.242550Z","bundle_sha256":"25aab8ace0bb9324ab9f4ad6e0cbb2ba4f51764a6c028189948b1779f958ac8b"}}