{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2014:ZDTIPP7XQBTHY5XW2OVYFCMGOD","short_pith_number":"pith:ZDTIPP7X","canonical_record":{"source":{"id":"1406.5231","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2014-06-19T22:57:55Z","cross_cats_sorted":["stat.AP"],"title_canon_sha256":"5c45df5746d344a888b05165f02a04f9775e06b6273ecd442596b1c582d16c4a","abstract_canon_sha256":"6151b0db0f26c0a75ddac8766d3b2b1d229f74260ff9ee9eb696a2309a8ff0cf"},"schema_version":"1.0"},"canonical_sha256":"c8e687bff780667c76f6d3ab82898670c346cc0d39a9416375c515ab34e5e793","source":{"kind":"arxiv","id":"1406.5231","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1406.5231","created_at":"2026-05-18T02:48:54Z"},{"alias_kind":"arxiv_version","alias_value":"1406.5231v2","created_at":"2026-05-18T02:48:54Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1406.5231","created_at":"2026-05-18T02:48:54Z"},{"alias_kind":"pith_short_12","alias_value":"ZDTIPP7XQBTH","created_at":"2026-05-18T12:28:59Z"},{"alias_kind":"pith_short_16","alias_value":"ZDTIPP7XQBTHY5XW","created_at":"2026-05-18T12:28:59Z"},{"alias_kind":"pith_short_8","alias_value":"ZDTIPP7X","created_at":"2026-05-18T12:28:59Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2014:ZDTIPP7XQBTHY5XW2OVYFCMGOD","target":"record","payload":{"canonical_record":{"source":{"id":"1406.5231","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2014-06-19T22:57:55Z","cross_cats_sorted":["stat.AP"],"title_canon_sha256":"5c45df5746d344a888b05165f02a04f9775e06b6273ecd442596b1c582d16c4a","abstract_canon_sha256":"6151b0db0f26c0a75ddac8766d3b2b1d229f74260ff9ee9eb696a2309a8ff0cf"},"schema_version":"1.0"},"canonical_sha256":"c8e687bff780667c76f6d3ab82898670c346cc0d39a9416375c515ab34e5e793","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T02:48:54.421689Z","signature_b64":"T9FAIbc1r1OqMYYrG27odQiU5twJkNA4goajRKJDDm6lIOQrVndM7nRrneHy6dSvYQPJo5KLtUgxldqlgS9cAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c8e687bff780667c76f6d3ab82898670c346cc0d39a9416375c515ab34e5e793","last_reissued_at":"2026-05-18T02:48:54.421136Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T02:48:54.421136Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1406.5231","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":"2026-05-18T02:48:54Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"MPIkXt7B8cu3J20HEpg2fIHKbw01bUy9TogauDsrx7AMBhEh04+M/hpVkD9v2MkCVZbqh0Ohe1DkNNHAeZ+gAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-20T07:23:05.210891Z"},"content_sha256":"48313990d9cf276c6493ccd1e649d09695882584c40a92c22eaa06c7268f6a31","schema_version":"1.0","event_id":"sha256:48313990d9cf276c6493ccd1e649d09695882584c40a92c22eaa06c7268f6a31"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2014:ZDTIPP7XQBTHY5XW2OVYFCMGOD","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Reducing Basis Mismatch in Harmonic Signal Recovery via Alternating Convex Search","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.AP"],"primary_cat":"math.OC","authors_text":"Albert K. Oh, Jonathan M. Nichols, Rebecca M. Willett","submitted_at":"2014-06-19T22:57:55Z","abstract_excerpt":"The theory behind compressive sampling pre-supposes that a given sequence of observations may be exactly represented by a linear combination of a small number of basis vectors. In practice, however, even small deviations from an exact signal model can result in dramatic increases in estimation error; this is the so-called \"basis mismatch\" problem. This work provides one possible solution to this problem in the form of an iterative, biconvex search algorithm. The approach uses standard $\\ell_1$-minimization to find the signal model coefficients followed by a maximum likelihood estimate of the s"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1406.5231","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":"2026-05-18T02:48:54Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"tIA0jxp4y63nrR87m9RV9Z0f88b0vqflxvo2N4AwP1CMAS41tsggNOoq43xB3+c0XDJ97I5Y0Vjjs8HU73L2Bw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-20T07:23:05.211238Z"},"content_sha256":"331498d413bc0d2af8ebcbbf2b01630f06bd2fbfe7a248c34bde2f23aed938ee","schema_version":"1.0","event_id":"sha256:331498d413bc0d2af8ebcbbf2b01630f06bd2fbfe7a248c34bde2f23aed938ee"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/ZDTIPP7XQBTHY5XW2OVYFCMGOD/bundle.json","state_url":"https://pith.science/pith/ZDTIPP7XQBTHY5XW2OVYFCMGOD/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/ZDTIPP7XQBTHY5XW2OVYFCMGOD/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":"2026-06-20T07:23:05Z","links":{"resolver":"https://pith.science/pith/ZDTIPP7XQBTHY5XW2OVYFCMGOD","bundle":"https://pith.science/pith/ZDTIPP7XQBTHY5XW2OVYFCMGOD/bundle.json","state":"https://pith.science/pith/ZDTIPP7XQBTHY5XW2OVYFCMGOD/state.json","well_known_bundle":"https://pith.science/.well-known/pith/ZDTIPP7XQBTHY5XW2OVYFCMGOD/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2014:ZDTIPP7XQBTHY5XW2OVYFCMGOD","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":"6151b0db0f26c0a75ddac8766d3b2b1d229f74260ff9ee9eb696a2309a8ff0cf","cross_cats_sorted":["stat.AP"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2014-06-19T22:57:55Z","title_canon_sha256":"5c45df5746d344a888b05165f02a04f9775e06b6273ecd442596b1c582d16c4a"},"schema_version":"1.0","source":{"id":"1406.5231","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1406.5231","created_at":"2026-05-18T02:48:54Z"},{"alias_kind":"arxiv_version","alias_value":"1406.5231v2","created_at":"2026-05-18T02:48:54Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1406.5231","created_at":"2026-05-18T02:48:54Z"},{"alias_kind":"pith_short_12","alias_value":"ZDTIPP7XQBTH","created_at":"2026-05-18T12:28:59Z"},{"alias_kind":"pith_short_16","alias_value":"ZDTIPP7XQBTHY5XW","created_at":"2026-05-18T12:28:59Z"},{"alias_kind":"pith_short_8","alias_value":"ZDTIPP7X","created_at":"2026-05-18T12:28:59Z"}],"graph_snapshots":[{"event_id":"sha256:331498d413bc0d2af8ebcbbf2b01630f06bd2fbfe7a248c34bde2f23aed938ee","target":"graph","created_at":"2026-05-18T02:48:54Z","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":"The theory behind compressive sampling pre-supposes that a given sequence of observations may be exactly represented by a linear combination of a small number of basis vectors. In practice, however, even small deviations from an exact signal model can result in dramatic increases in estimation error; this is the so-called \"basis mismatch\" problem. This work provides one possible solution to this problem in the form of an iterative, biconvex search algorithm. The approach uses standard $\\ell_1$-minimization to find the signal model coefficients followed by a maximum likelihood estimate of the s","authors_text":"Albert K. Oh, Jonathan M. Nichols, Rebecca M. Willett","cross_cats":["stat.AP"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2014-06-19T22:57:55Z","title":"Reducing Basis Mismatch in Harmonic Signal Recovery via Alternating Convex Search"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1406.5231","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":"sha256:48313990d9cf276c6493ccd1e649d09695882584c40a92c22eaa06c7268f6a31","target":"record","created_at":"2026-05-18T02:48:54Z","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":"6151b0db0f26c0a75ddac8766d3b2b1d229f74260ff9ee9eb696a2309a8ff0cf","cross_cats_sorted":["stat.AP"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2014-06-19T22:57:55Z","title_canon_sha256":"5c45df5746d344a888b05165f02a04f9775e06b6273ecd442596b1c582d16c4a"},"schema_version":"1.0","source":{"id":"1406.5231","kind":"arxiv","version":2}},"canonical_sha256":"c8e687bff780667c76f6d3ab82898670c346cc0d39a9416375c515ab34e5e793","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c8e687bff780667c76f6d3ab82898670c346cc0d39a9416375c515ab34e5e793","first_computed_at":"2026-05-18T02:48:54.421136Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T02:48:54.421136Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"T9FAIbc1r1OqMYYrG27odQiU5twJkNA4goajRKJDDm6lIOQrVndM7nRrneHy6dSvYQPJo5KLtUgxldqlgS9cAw==","signature_status":"signed_v1","signed_at":"2026-05-18T02:48:54.421689Z","signed_message":"canonical_sha256_bytes"},"source_id":"1406.5231","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:48313990d9cf276c6493ccd1e649d09695882584c40a92c22eaa06c7268f6a31","sha256:331498d413bc0d2af8ebcbbf2b01630f06bd2fbfe7a248c34bde2f23aed938ee"],"state_sha256":"1b5a56245a92b4f3bfc6509907d2e0132a467f09c6ad66f0aa1548bd7d577337"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"v562q9sorhLgtSFOkK13SI/G3kxJQS+I2L/YoigxqJXNhmC5zVwawABT0KWyJcFAYLLZwZfxhv+oS9IBF0t3AA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-20T07:23:05.213294Z","bundle_sha256":"5fc20bb955762101c615b5ab4af96de9a11f80ccd2eec87e2a178aed0536581f"}}