{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:I7YBVGOHUGS7V4Y4UDPI34BKJD","short_pith_number":"pith:I7YBVGOH","canonical_record":{"source":{"id":"2412.03106","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.IT","submitted_at":"2024-12-04T08:12:35Z","cross_cats_sorted":["math.IT"],"title_canon_sha256":"9ee3dcb02dac951bc184f99a591b61cb78073867c8f8df3ea4a6e8077505ed77","abstract_canon_sha256":"b70e56e2a6d917d175db8742022da6700b8c611d1229f3c401bb26cac1816120"},"schema_version":"1.0"},"canonical_sha256":"47f01a99c7a1a5faf31ca0de8df02a48e0c5bb6f2b6f6ea321b1f68c208b784d","source":{"kind":"arxiv","id":"2412.03106","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.03106","created_at":"2026-07-05T09:44:25Z"},{"alias_kind":"arxiv_version","alias_value":"2412.03106v1","created_at":"2026-07-05T09:44:25Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.03106","created_at":"2026-07-05T09:44:25Z"},{"alias_kind":"pith_short_12","alias_value":"I7YBVGOHUGS7","created_at":"2026-07-05T09:44:25Z"},{"alias_kind":"pith_short_16","alias_value":"I7YBVGOHUGS7V4Y4","created_at":"2026-07-05T09:44:25Z"},{"alias_kind":"pith_short_8","alias_value":"I7YBVGOH","created_at":"2026-07-05T09:44:25Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:I7YBVGOHUGS7V4Y4UDPI34BKJD","target":"record","payload":{"canonical_record":{"source":{"id":"2412.03106","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.IT","submitted_at":"2024-12-04T08:12:35Z","cross_cats_sorted":["math.IT"],"title_canon_sha256":"9ee3dcb02dac951bc184f99a591b61cb78073867c8f8df3ea4a6e8077505ed77","abstract_canon_sha256":"b70e56e2a6d917d175db8742022da6700b8c611d1229f3c401bb26cac1816120"},"schema_version":"1.0"},"canonical_sha256":"47f01a99c7a1a5faf31ca0de8df02a48e0c5bb6f2b6f6ea321b1f68c208b784d","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:44:25.066446Z","signature_b64":"3Z/8gP907ZO42vZP6binK5x6ufNiqOc/QWMpgcWXK4/y4W05Mfm0t+XEOB52vSKfWyKiVi8vN8EBk3EaqjorDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"47f01a99c7a1a5faf31ca0de8df02a48e0c5bb6f2b6f6ea321b1f68c208b784d","last_reissued_at":"2026-07-05T09:44:25.066049Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:44:25.066049Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2412.03106","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T09:44:25Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"RgprCoiB4T5shMGtiVJszrCrLmjdjub2lhTYAzaKhD76jdrYfC5pX9N2S8loct6HLNwAarsVXaS/9AoPawTOBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T01:44:31.137965Z"},"content_sha256":"7eb40aaeef967534f6b242a727950d9eb8f6fdeadd6f6d1bd49dfb31dfc34d84","schema_version":"1.0","event_id":"sha256:7eb40aaeef967534f6b242a727950d9eb8f6fdeadd6f6d1bd49dfb31dfc34d84"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:I7YBVGOHUGS7V4Y4UDPI34BKJD","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Improved Turbo Message Passing for Compressive Robust Principal Component Analysis: Algorithm Design and Asymptotic Analysis","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["math.IT"],"primary_cat":"cs.IT","authors_text":"Junjie Ma, Xiaojun Yuan, Zhuohang He","submitted_at":"2024-12-04T08:12:35Z","abstract_excerpt":"Compressive Robust Principal Component Analysis (CRPCA) naturally arises in various applications as a means to recover a low-rank matrix low-rank matrix $\\boldsymbol{L}$ and a sparse matrix $\\boldsymbol{S}$ from compressive measurements. In this paper, we approach the problem from a Bayesian inference perspective. We establish a probabilistic model for the problem and develop an improved turbo message passing (ITMP) algorithm based on the sum-product rule and the appropriate approximations. Additionally, we establish a state evolution framework to characterize the asymptotic behavior of the IT"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.03106","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/2412.03106/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T09:44:25Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"CxgxOloNJfvd/5UDLArkhnRJihgCmTYPqZbXF00MgZYpQDPz1I865fUJHQM+ome/YbYKmOU443YQy3iKUvLMDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T01:44:31.138828Z"},"content_sha256":"34a2c91feafc6e392a1368000fc1c28a52b293cb79531f5002ba9fbc86950bd2","schema_version":"1.0","event_id":"sha256:34a2c91feafc6e392a1368000fc1c28a52b293cb79531f5002ba9fbc86950bd2"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/I7YBVGOHUGS7V4Y4UDPI34BKJD/bundle.json","state_url":"https://pith.science/pith/I7YBVGOHUGS7V4Y4UDPI34BKJD/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/I7YBVGOHUGS7V4Y4UDPI34BKJD/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":"2026-08-06T01:44:31Z","links":{"resolver":"https://pith.science/pith/I7YBVGOHUGS7V4Y4UDPI34BKJD","bundle":"https://pith.science/pith/I7YBVGOHUGS7V4Y4UDPI34BKJD/bundle.json","state":"https://pith.science/pith/I7YBVGOHUGS7V4Y4UDPI34BKJD/state.json","well_known_bundle":"https://pith.science/.well-known/pith/I7YBVGOHUGS7V4Y4UDPI34BKJD/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:I7YBVGOHUGS7V4Y4UDPI34BKJD","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":"b70e56e2a6d917d175db8742022da6700b8c611d1229f3c401bb26cac1816120","cross_cats_sorted":["math.IT"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.IT","submitted_at":"2024-12-04T08:12:35Z","title_canon_sha256":"9ee3dcb02dac951bc184f99a591b61cb78073867c8f8df3ea4a6e8077505ed77"},"schema_version":"1.0","source":{"id":"2412.03106","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.03106","created_at":"2026-07-05T09:44:25Z"},{"alias_kind":"arxiv_version","alias_value":"2412.03106v1","created_at":"2026-07-05T09:44:25Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.03106","created_at":"2026-07-05T09:44:25Z"},{"alias_kind":"pith_short_12","alias_value":"I7YBVGOHUGS7","created_at":"2026-07-05T09:44:25Z"},{"alias_kind":"pith_short_16","alias_value":"I7YBVGOHUGS7V4Y4","created_at":"2026-07-05T09:44:25Z"},{"alias_kind":"pith_short_8","alias_value":"I7YBVGOH","created_at":"2026-07-05T09:44:25Z"}],"graph_snapshots":[{"event_id":"sha256:34a2c91feafc6e392a1368000fc1c28a52b293cb79531f5002ba9fbc86950bd2","target":"graph","created_at":"2026-07-05T09:44:25Z","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/2412.03106/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Compressive Robust Principal Component Analysis (CRPCA) naturally arises in various applications as a means to recover a low-rank matrix low-rank matrix $\\boldsymbol{L}$ and a sparse matrix $\\boldsymbol{S}$ from compressive measurements. In this paper, we approach the problem from a Bayesian inference perspective. We establish a probabilistic model for the problem and develop an improved turbo message passing (ITMP) algorithm based on the sum-product rule and the appropriate approximations. Additionally, we establish a state evolution framework to characterize the asymptotic behavior of the IT","authors_text":"Junjie Ma, Xiaojun Yuan, Zhuohang He","cross_cats":["math.IT"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.IT","submitted_at":"2024-12-04T08:12:35Z","title":"Improved Turbo Message Passing for Compressive Robust Principal Component Analysis: Algorithm Design and Asymptotic Analysis"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.03106","kind":"arxiv","version":1},"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":"sha256:7eb40aaeef967534f6b242a727950d9eb8f6fdeadd6f6d1bd49dfb31dfc34d84","target":"record","created_at":"2026-07-05T09:44:25Z","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":"b70e56e2a6d917d175db8742022da6700b8c611d1229f3c401bb26cac1816120","cross_cats_sorted":["math.IT"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.IT","submitted_at":"2024-12-04T08:12:35Z","title_canon_sha256":"9ee3dcb02dac951bc184f99a591b61cb78073867c8f8df3ea4a6e8077505ed77"},"schema_version":"1.0","source":{"id":"2412.03106","kind":"arxiv","version":1}},"canonical_sha256":"47f01a99c7a1a5faf31ca0de8df02a48e0c5bb6f2b6f6ea321b1f68c208b784d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"47f01a99c7a1a5faf31ca0de8df02a48e0c5bb6f2b6f6ea321b1f68c208b784d","first_computed_at":"2026-07-05T09:44:25.066049Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:44:25.066049Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"3Z/8gP907ZO42vZP6binK5x6ufNiqOc/QWMpgcWXK4/y4W05Mfm0t+XEOB52vSKfWyKiVi8vN8EBk3EaqjorDg==","signature_status":"signed_v1","signed_at":"2026-07-05T09:44:25.066446Z","signed_message":"canonical_sha256_bytes"},"source_id":"2412.03106","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:7eb40aaeef967534f6b242a727950d9eb8f6fdeadd6f6d1bd49dfb31dfc34d84","sha256:34a2c91feafc6e392a1368000fc1c28a52b293cb79531f5002ba9fbc86950bd2"],"state_sha256":"670b6d461917fbeb320e6c572538acbfe97f16b89d236612365a68fb63ce2c16"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"jm/1CVs94/j4F93CI7cpmRbvj+i7JrleFlxiMVBVUuDiNTVcaB0IGgdm8CSVelaCfw1hpv1B6b4r0YBsxrEiAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-06T01:44:31.146026Z","bundle_sha256":"de7dbcc274bc53e7d30231c07716be66160a093aa5e244b9b0994d657d851edb"}}