{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2016:FPCS72EPPZ7K2FVJZEEGPRP3FP","short_pith_number":"pith:FPCS72EP","canonical_record":{"source":{"id":"1606.07231","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IT","submitted_at":"2016-06-23T08:59:20Z","cross_cats_sorted":["math.IT"],"title_canon_sha256":"670d6d8d0c11603b1c411601c8ce4737620cdb7915a262856d2e1aa0635b7477","abstract_canon_sha256":"1f7e9905bc38441b79a1cf0c337b672e5fd7005d3fca562222f3f43d916c4ecc"},"schema_version":"1.0"},"canonical_sha256":"2bc52fe88f7e7ead16a9c90867c5fb2bc5672e90e22a3ff21f2ca598ba00e134","source":{"kind":"arxiv","id":"1606.07231","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1606.07231","created_at":"2026-05-18T01:11:58Z"},{"alias_kind":"arxiv_version","alias_value":"1606.07231v1","created_at":"2026-05-18T01:11:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1606.07231","created_at":"2026-05-18T01:11:58Z"},{"alias_kind":"pith_short_12","alias_value":"FPCS72EPPZ7K","created_at":"2026-05-18T12:30:15Z"},{"alias_kind":"pith_short_16","alias_value":"FPCS72EPPZ7K2FVJ","created_at":"2026-05-18T12:30:15Z"},{"alias_kind":"pith_short_8","alias_value":"FPCS72EP","created_at":"2026-05-18T12:30:15Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2016:FPCS72EPPZ7K2FVJZEEGPRP3FP","target":"record","payload":{"canonical_record":{"source":{"id":"1606.07231","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IT","submitted_at":"2016-06-23T08:59:20Z","cross_cats_sorted":["math.IT"],"title_canon_sha256":"670d6d8d0c11603b1c411601c8ce4737620cdb7915a262856d2e1aa0635b7477","abstract_canon_sha256":"1f7e9905bc38441b79a1cf0c337b672e5fd7005d3fca562222f3f43d916c4ecc"},"schema_version":"1.0"},"canonical_sha256":"2bc52fe88f7e7ead16a9c90867c5fb2bc5672e90e22a3ff21f2ca598ba00e134","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:11:58.414948Z","signature_b64":"TucqF0eW01Z1UrcWlYXQHG0FhsqlLAf6Rv5D9NMlUpkRxTClC2mUO2if7Lpmc00SfoGlluBcMimGWKa/wi70DA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"2bc52fe88f7e7ead16a9c90867c5fb2bc5672e90e22a3ff21f2ca598ba00e134","last_reissued_at":"2026-05-18T01:11:58.414609Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:11:58.414609Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1606.07231","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":"2026-05-18T01:11:58Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ThlsDuouvWUWPRRVakhOQ77yPDLGf0Ors3hSWp6bsdd+Vdhw5JX7sCjRPMThxYyEc/F9hn3VC76YqA+txJlZCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-20T06:56:14.609585Z"},"content_sha256":"979b2b8276001c9634147dc26f801b893c1c4c85f8a2d9ae5df4038d0993617e","schema_version":"1.0","event_id":"sha256:979b2b8276001c9634147dc26f801b893c1c4c85f8a2d9ae5df4038d0993617e"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2016:FPCS72EPPZ7K2FVJZEEGPRP3FP","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A Compact Formulation for the $\\ell_{2,1}$ Mixed-Norm Minimization Problem","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["math.IT"],"primary_cat":"cs.IT","authors_text":"Christian Steffens, Marc E. Pfetsch, Marius Pesavento","submitted_at":"2016-06-23T08:59:20Z","abstract_excerpt":"Parameter estimation from multiple measurement vectors (MMVs) is a fundamental problem in many signal processing applications, e.g., spectral analysis and direction-of- arrival estimation. Recently, this problem has been address using prior information in form of a jointly sparse signal structure. A prominent approach for exploiting joint sparsity considers mixed-norm minimization in which, however, the problem size grows with the number of measurements and the desired resolution, respectively. In this work we derive an equivalent, compact reformulation of the $\\ell_{2,1}$ mixed-norm minimizat"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1606.07231","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":"2026-05-18T01:11:58Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"vGiFueEkA7fPnO8kwevjxNE5/K9VdpH9JBIXYNrU5waMAY1VcJNGQhjNIIk2IJ2XH0fMZB5wRw2SRGHzRd7mBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-20T06:56:14.609935Z"},"content_sha256":"a515f05e489aa54162d483d098ea86f4490329e146fc08d9c23025f1078bd106","schema_version":"1.0","event_id":"sha256:a515f05e489aa54162d483d098ea86f4490329e146fc08d9c23025f1078bd106"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/FPCS72EPPZ7K2FVJZEEGPRP3FP/bundle.json","state_url":"https://pith.science/pith/FPCS72EPPZ7K2FVJZEEGPRP3FP/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/FPCS72EPPZ7K2FVJZEEGPRP3FP/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":"2026-05-20T06:56:14Z","links":{"resolver":"https://pith.science/pith/FPCS72EPPZ7K2FVJZEEGPRP3FP","bundle":"https://pith.science/pith/FPCS72EPPZ7K2FVJZEEGPRP3FP/bundle.json","state":"https://pith.science/pith/FPCS72EPPZ7K2FVJZEEGPRP3FP/state.json","well_known_bundle":"https://pith.science/.well-known/pith/FPCS72EPPZ7K2FVJZEEGPRP3FP/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2016:FPCS72EPPZ7K2FVJZEEGPRP3FP","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":"1f7e9905bc38441b79a1cf0c337b672e5fd7005d3fca562222f3f43d916c4ecc","cross_cats_sorted":["math.IT"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IT","submitted_at":"2016-06-23T08:59:20Z","title_canon_sha256":"670d6d8d0c11603b1c411601c8ce4737620cdb7915a262856d2e1aa0635b7477"},"schema_version":"1.0","source":{"id":"1606.07231","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1606.07231","created_at":"2026-05-18T01:11:58Z"},{"alias_kind":"arxiv_version","alias_value":"1606.07231v1","created_at":"2026-05-18T01:11:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1606.07231","created_at":"2026-05-18T01:11:58Z"},{"alias_kind":"pith_short_12","alias_value":"FPCS72EPPZ7K","created_at":"2026-05-18T12:30:15Z"},{"alias_kind":"pith_short_16","alias_value":"FPCS72EPPZ7K2FVJ","created_at":"2026-05-18T12:30:15Z"},{"alias_kind":"pith_short_8","alias_value":"FPCS72EP","created_at":"2026-05-18T12:30:15Z"}],"graph_snapshots":[{"event_id":"sha256:a515f05e489aa54162d483d098ea86f4490329e146fc08d9c23025f1078bd106","target":"graph","created_at":"2026-05-18T01:11:58Z","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":"Parameter estimation from multiple measurement vectors (MMVs) is a fundamental problem in many signal processing applications, e.g., spectral analysis and direction-of- arrival estimation. Recently, this problem has been address using prior information in form of a jointly sparse signal structure. A prominent approach for exploiting joint sparsity considers mixed-norm minimization in which, however, the problem size grows with the number of measurements and the desired resolution, respectively. In this work we derive an equivalent, compact reformulation of the $\\ell_{2,1}$ mixed-norm minimizat","authors_text":"Christian Steffens, Marc E. Pfetsch, Marius Pesavento","cross_cats":["math.IT"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IT","submitted_at":"2016-06-23T08:59:20Z","title":"A Compact Formulation for the $\\ell_{2,1}$ Mixed-Norm Minimization Problem"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1606.07231","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":"sha256:979b2b8276001c9634147dc26f801b893c1c4c85f8a2d9ae5df4038d0993617e","target":"record","created_at":"2026-05-18T01:11:58Z","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":"1f7e9905bc38441b79a1cf0c337b672e5fd7005d3fca562222f3f43d916c4ecc","cross_cats_sorted":["math.IT"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IT","submitted_at":"2016-06-23T08:59:20Z","title_canon_sha256":"670d6d8d0c11603b1c411601c8ce4737620cdb7915a262856d2e1aa0635b7477"},"schema_version":"1.0","source":{"id":"1606.07231","kind":"arxiv","version":1}},"canonical_sha256":"2bc52fe88f7e7ead16a9c90867c5fb2bc5672e90e22a3ff21f2ca598ba00e134","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"2bc52fe88f7e7ead16a9c90867c5fb2bc5672e90e22a3ff21f2ca598ba00e134","first_computed_at":"2026-05-18T01:11:58.414609Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T01:11:58.414609Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"TucqF0eW01Z1UrcWlYXQHG0FhsqlLAf6Rv5D9NMlUpkRxTClC2mUO2if7Lpmc00SfoGlluBcMimGWKa/wi70DA==","signature_status":"signed_v1","signed_at":"2026-05-18T01:11:58.414948Z","signed_message":"canonical_sha256_bytes"},"source_id":"1606.07231","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:979b2b8276001c9634147dc26f801b893c1c4c85f8a2d9ae5df4038d0993617e","sha256:a515f05e489aa54162d483d098ea86f4490329e146fc08d9c23025f1078bd106"],"state_sha256":"a52c82eee116054136256d7ca479ec1bc140c22a00442bc3a13f7d43ad0584b3"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ktHUJIiWzcRpD3ooXPvc4LmdI7ivN05kWm7ajaVfqVJ9uWn35oGoPvl+nRwYvJl7TaK3l6Ngv3Uvccw2MRZ5Ag==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-20T06:56:14.611913Z","bundle_sha256":"c9457c6acd175704282833b2f340c18524f624c737da3f8d5ddb16d5d25a5ab6"}}