{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2010:WGGPAPZEQIOPRIWWDUN54IOGAF","short_pith_number":"pith:WGGPAPZE","schema_version":"1.0","canonical_sha256":"b18cf03f24821cf8a2d61d1bde21c601544c6a0bcac4cdf21d0cd9d82fab5b75","source":{"kind":"arxiv","id":"1007.2377","version":3},"attestation_state":"computed","paper":{"title":"Performance bounds for expander-based compressed sensing in Poisson noise","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["math.IT"],"primary_cat":"cs.IT","authors_text":"Maxim Raginsky, Rebecca Willett, Robert Calderbank, Roummel Marcia, Sina Jafarpour, Zachary Harmany","submitted_at":"2010-07-14T16:52:06Z","abstract_excerpt":"This paper provides performance bounds for compressed sensing in the presence of Poisson noise using expander graphs. The Poisson noise model is appropriate for a variety of applications, including low-light imaging and digital streaming, where the signal-independent and/or bounded noise models used in the compressed sensing literature are no longer applicable. In this paper, we develop a novel sensing paradigm based on expander graphs and propose a MAP algorithm for recovering sparse or compressible signals from Poisson observations. The geometry of the expander graphs and the positivity of t"},"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":"1007.2377","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IT","submitted_at":"2010-07-14T16:52:06Z","cross_cats_sorted":["math.IT"],"title_canon_sha256":"5ec3c7bfdbff7585b4708669c5da2357072d50f32c15a8f9c779ba0517b35b4d","abstract_canon_sha256":"112aaefff8c7f923bec02d923c2d98870140c4503b7894cf0f6d6a064a30f21e"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T02:06:22.012290Z","signature_b64":"yeFx5F4zuK5R2l3thctzgfj6o2c+jSXkO8Uhqh7kXSX5Ufwb5nGLfh06Q6Qp9EYB43arbEsa9tUR2J94LKBBDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b18cf03f24821cf8a2d61d1bde21c601544c6a0bcac4cdf21d0cd9d82fab5b75","last_reissued_at":"2026-05-18T02:06:22.011680Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T02:06:22.011680Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Performance bounds for expander-based compressed sensing in Poisson noise","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["math.IT"],"primary_cat":"cs.IT","authors_text":"Maxim Raginsky, Rebecca Willett, Robert Calderbank, Roummel Marcia, Sina Jafarpour, Zachary Harmany","submitted_at":"2010-07-14T16:52:06Z","abstract_excerpt":"This paper provides performance bounds for compressed sensing in the presence of Poisson noise using expander graphs. The Poisson noise model is appropriate for a variety of applications, including low-light imaging and digital streaming, where the signal-independent and/or bounded noise models used in the compressed sensing literature are no longer applicable. In this paper, we develop a novel sensing paradigm based on expander graphs and propose a MAP algorithm for recovering sparse or compressible signals from Poisson observations. The geometry of the expander graphs and the positivity of t"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1007.2377","kind":"arxiv","version":3},"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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1007.2377","created_at":"2026-05-18T02:06:22.011763+00:00"},{"alias_kind":"arxiv_version","alias_value":"1007.2377v3","created_at":"2026-05-18T02:06:22.011763+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1007.2377","created_at":"2026-05-18T02:06:22.011763+00:00"},{"alias_kind":"pith_short_12","alias_value":"WGGPAPZEQIOP","created_at":"2026-05-18T12:26:15.391820+00:00"},{"alias_kind":"pith_short_16","alias_value":"WGGPAPZEQIOPRIWW","created_at":"2026-05-18T12:26:15.391820+00:00"},{"alias_kind":"pith_short_8","alias_value":"WGGPAPZE","created_at":"2026-05-18T12:26:15.391820+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/WGGPAPZEQIOPRIWWDUN54IOGAF","json":"https://pith.science/pith/WGGPAPZEQIOPRIWWDUN54IOGAF.json","graph_json":"https://pith.science/api/pith-number/WGGPAPZEQIOPRIWWDUN54IOGAF/graph.json","events_json":"https://pith.science/api/pith-number/WGGPAPZEQIOPRIWWDUN54IOGAF/events.json","paper":"https://pith.science/paper/WGGPAPZE"},"agent_actions":{"view_html":"https://pith.science/pith/WGGPAPZEQIOPRIWWDUN54IOGAF","download_json":"https://pith.science/pith/WGGPAPZEQIOPRIWWDUN54IOGAF.json","view_paper":"https://pith.science/paper/WGGPAPZE","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1007.2377&json=true","fetch_graph":"https://pith.science/api/pith-number/WGGPAPZEQIOPRIWWDUN54IOGAF/graph.json","fetch_events":"https://pith.science/api/pith-number/WGGPAPZEQIOPRIWWDUN54IOGAF/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/WGGPAPZEQIOPRIWWDUN54IOGAF/action/timestamp_anchor","attest_storage":"https://pith.science/pith/WGGPAPZEQIOPRIWWDUN54IOGAF/action/storage_attestation","attest_author":"https://pith.science/pith/WGGPAPZEQIOPRIWWDUN54IOGAF/action/author_attestation","sign_citation":"https://pith.science/pith/WGGPAPZEQIOPRIWWDUN54IOGAF/action/citation_signature","submit_replication":"https://pith.science/pith/WGGPAPZEQIOPRIWWDUN54IOGAF/action/replication_record"}},"created_at":"2026-05-18T02:06:22.011763+00:00","updated_at":"2026-05-18T02:06:22.011763+00:00"}