{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2012:I75DUXY7OEQMPDGOEAJOJHXCP5","short_pith_number":"pith:I75DUXY7","canonical_record":{"source":{"id":"1212.0912","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2012-12-05T01:12:03Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"aaf42947833fd00ca2a67e15c955bf01a095835298c4433ed38c010c5483b0cc","abstract_canon_sha256":"3d888f3f3949600b7cfe0d0750c62346fabaaf62048adaadf6f59915c65690a0"},"schema_version":"1.0"},"canonical_sha256":"47fa3a5f1f7120c78cce2012e49ee27f632e28b1ce551990a0d5de4920a04594","source":{"kind":"arxiv","id":"1212.0912","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1212.0912","created_at":"2026-05-18T03:39:06Z"},{"alias_kind":"arxiv_version","alias_value":"1212.0912v1","created_at":"2026-05-18T03:39:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1212.0912","created_at":"2026-05-18T03:39:06Z"},{"alias_kind":"pith_short_12","alias_value":"I75DUXY7OEQM","created_at":"2026-05-18T12:27:09Z"},{"alias_kind":"pith_short_16","alias_value":"I75DUXY7OEQMPDGO","created_at":"2026-05-18T12:27:09Z"},{"alias_kind":"pith_short_8","alias_value":"I75DUXY7","created_at":"2026-05-18T12:27:09Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2012:I75DUXY7OEQMPDGOEAJOJHXCP5","target":"record","payload":{"canonical_record":{"source":{"id":"1212.0912","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2012-12-05T01:12:03Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"aaf42947833fd00ca2a67e15c955bf01a095835298c4433ed38c010c5483b0cc","abstract_canon_sha256":"3d888f3f3949600b7cfe0d0750c62346fabaaf62048adaadf6f59915c65690a0"},"schema_version":"1.0"},"canonical_sha256":"47fa3a5f1f7120c78cce2012e49ee27f632e28b1ce551990a0d5de4920a04594","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T03:39:06.981965Z","signature_b64":"piLuMLcYQ550BmH/4heGJp9DD8/qsMeDsxAbeKDc0kh6vcOo0CLDT8bX7X+PbdeBubIhCkquyME/oJK6/drJDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"47fa3a5f1f7120c78cce2012e49ee27f632e28b1ce551990a0d5de4920a04594","last_reissued_at":"2026-05-18T03:39:06.981357Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T03:39:06.981357Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1212.0912","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":"2026-05-18T03:39:06Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"6T1y34yfRYdklZwUXImQuorJQdwWtmW31NXTX7qDrf7bFKVXkM2Bpo8k1Av88SdqFBft76F+Oq2LkAz/L10UCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-02T13:54:49.908599Z"},"content_sha256":"2e9dde8219bcc212e659e58e21a604a9a8dc6ab35d2d877756832e68aa96a45e","schema_version":"1.0","event_id":"sha256:2e9dde8219bcc212e659e58e21a604a9a8dc6ab35d2d877756832e68aa96a45e"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2012:I75DUXY7OEQMPDGOEAJOJHXCP5","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Sparse seismic imaging using variable projection","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"math.OC","authors_text":"Aleksandr Y. Aravkin, Ning Tu, Tristan van Leeuwen","submitted_at":"2012-12-05T01:12:03Z","abstract_excerpt":"We consider an important class of signal processing problems where the signal of interest is known to be sparse, and can be recovered from data given auxiliary information about how the data was generated. For example, a sparse Green's function may be recovered from seismic experimental data using sparsity optimization when the source signature is known. Unfortunately, in practice this information is often missing, and must be recovered from data along with the signal using deconvolution techniques.\n  In this paper, we present a novel methodology to simultaneously solve for the sparse signal a"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1212.0912","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":""},"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":"2026-05-18T03:39:06Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"UETbvh+yyhn+XotoKGV2iyUJBHGbjumf6TfaY//z8Xnro3yd90UUzBDHBnWyTFX/eJxPklpkdNIsRHraiINmAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-02T13:54:49.908954Z"},"content_sha256":"8ef9667a6c47c2241920dfc665905263ac64f229572687d7b448f8f7c00cbbac","schema_version":"1.0","event_id":"sha256:8ef9667a6c47c2241920dfc665905263ac64f229572687d7b448f8f7c00cbbac"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/I75DUXY7OEQMPDGOEAJOJHXCP5/bundle.json","state_url":"https://pith.science/pith/I75DUXY7OEQMPDGOEAJOJHXCP5/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/I75DUXY7OEQMPDGOEAJOJHXCP5/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":"2026-06-02T13:54:49Z","links":{"resolver":"https://pith.science/pith/I75DUXY7OEQMPDGOEAJOJHXCP5","bundle":"https://pith.science/pith/I75DUXY7OEQMPDGOEAJOJHXCP5/bundle.json","state":"https://pith.science/pith/I75DUXY7OEQMPDGOEAJOJHXCP5/state.json","well_known_bundle":"https://pith.science/.well-known/pith/I75DUXY7OEQMPDGOEAJOJHXCP5/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2012:I75DUXY7OEQMPDGOEAJOJHXCP5","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":"3d888f3f3949600b7cfe0d0750c62346fabaaf62048adaadf6f59915c65690a0","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2012-12-05T01:12:03Z","title_canon_sha256":"aaf42947833fd00ca2a67e15c955bf01a095835298c4433ed38c010c5483b0cc"},"schema_version":"1.0","source":{"id":"1212.0912","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1212.0912","created_at":"2026-05-18T03:39:06Z"},{"alias_kind":"arxiv_version","alias_value":"1212.0912v1","created_at":"2026-05-18T03:39:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1212.0912","created_at":"2026-05-18T03:39:06Z"},{"alias_kind":"pith_short_12","alias_value":"I75DUXY7OEQM","created_at":"2026-05-18T12:27:09Z"},{"alias_kind":"pith_short_16","alias_value":"I75DUXY7OEQMPDGO","created_at":"2026-05-18T12:27:09Z"},{"alias_kind":"pith_short_8","alias_value":"I75DUXY7","created_at":"2026-05-18T12:27:09Z"}],"graph_snapshots":[{"event_id":"sha256:8ef9667a6c47c2241920dfc665905263ac64f229572687d7b448f8f7c00cbbac","target":"graph","created_at":"2026-05-18T03:39:06Z","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":"We consider an important class of signal processing problems where the signal of interest is known to be sparse, and can be recovered from data given auxiliary information about how the data was generated. For example, a sparse Green's function may be recovered from seismic experimental data using sparsity optimization when the source signature is known. Unfortunately, in practice this information is often missing, and must be recovered from data along with the signal using deconvolution techniques.\n  In this paper, we present a novel methodology to simultaneously solve for the sparse signal a","authors_text":"Aleksandr Y. Aravkin, Ning Tu, Tristan van Leeuwen","cross_cats":["stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2012-12-05T01:12:03Z","title":"Sparse seismic imaging using variable projection"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1212.0912","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":"sha256:2e9dde8219bcc212e659e58e21a604a9a8dc6ab35d2d877756832e68aa96a45e","target":"record","created_at":"2026-05-18T03:39:06Z","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":"3d888f3f3949600b7cfe0d0750c62346fabaaf62048adaadf6f59915c65690a0","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2012-12-05T01:12:03Z","title_canon_sha256":"aaf42947833fd00ca2a67e15c955bf01a095835298c4433ed38c010c5483b0cc"},"schema_version":"1.0","source":{"id":"1212.0912","kind":"arxiv","version":1}},"canonical_sha256":"47fa3a5f1f7120c78cce2012e49ee27f632e28b1ce551990a0d5de4920a04594","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"47fa3a5f1f7120c78cce2012e49ee27f632e28b1ce551990a0d5de4920a04594","first_computed_at":"2026-05-18T03:39:06.981357Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T03:39:06.981357Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"piLuMLcYQ550BmH/4heGJp9DD8/qsMeDsxAbeKDc0kh6vcOo0CLDT8bX7X+PbdeBubIhCkquyME/oJK6/drJDw==","signature_status":"signed_v1","signed_at":"2026-05-18T03:39:06.981965Z","signed_message":"canonical_sha256_bytes"},"source_id":"1212.0912","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:2e9dde8219bcc212e659e58e21a604a9a8dc6ab35d2d877756832e68aa96a45e","sha256:8ef9667a6c47c2241920dfc665905263ac64f229572687d7b448f8f7c00cbbac"],"state_sha256":"f3fb4c6136fa54bc12058082cc22b5d2582705f2e241cb088741c0c4dd742001"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"raEJanuCio4ESrd2d82FikIE+Cu6vMOMnc0LPBLBrg1zWks0dCAibJ3lmU4CDG82TxBs/kyX0hNAWgxTXO4PCQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-02T13:54:49.910966Z","bundle_sha256":"6d626ee5d6d45d327abec1bcb8d9c5b7e6daf9f3361cf074d16fe0aad11cddb0"}}