{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2015:344MX6WEQZQCC3FKPXCOZZEC4F","short_pith_number":"pith:344MX6WE","canonical_record":{"source":{"id":"1508.05808","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SI","submitted_at":"2015-04-24T17:45:51Z","cross_cats_sorted":["cs.DC","cs.IT","math.IT"],"title_canon_sha256":"209466841c4949af7cbd2046d5ba32b93249a8b87c64ba8202dc8fd5feb8c0a7","abstract_canon_sha256":"b1f11670efa9c7d934442e64b4c58f7f8a86f0da0b380e59aa5adff93ecf1a06"},"schema_version":"1.0"},"canonical_sha256":"df38cbfac48660216caa7dc4ece482e17fbfda87106fedc06b05666fa3537321","source":{"kind":"arxiv","id":"1508.05808","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1508.05808","created_at":"2026-05-18T01:34:15Z"},{"alias_kind":"arxiv_version","alias_value":"1508.05808v1","created_at":"2026-05-18T01:34:15Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1508.05808","created_at":"2026-05-18T01:34:15Z"},{"alias_kind":"pith_short_12","alias_value":"344MX6WEQZQC","created_at":"2026-05-18T12:29:02Z"},{"alias_kind":"pith_short_16","alias_value":"344MX6WEQZQCC3FK","created_at":"2026-05-18T12:29:02Z"},{"alias_kind":"pith_short_8","alias_value":"344MX6WE","created_at":"2026-05-18T12:29:02Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2015:344MX6WEQZQCC3FKPXCOZZEC4F","target":"record","payload":{"canonical_record":{"source":{"id":"1508.05808","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SI","submitted_at":"2015-04-24T17:45:51Z","cross_cats_sorted":["cs.DC","cs.IT","math.IT"],"title_canon_sha256":"209466841c4949af7cbd2046d5ba32b93249a8b87c64ba8202dc8fd5feb8c0a7","abstract_canon_sha256":"b1f11670efa9c7d934442e64b4c58f7f8a86f0da0b380e59aa5adff93ecf1a06"},"schema_version":"1.0"},"canonical_sha256":"df38cbfac48660216caa7dc4ece482e17fbfda87106fedc06b05666fa3537321","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:34:15.016974Z","signature_b64":"iq4lgI8b+hfszporEtkM8IEWHF821Vl7MoZM3s/Bj3eAzScCymVo+/wq9P+6I0+0zNbhl56LcEXXeLpeqiSSBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"df38cbfac48660216caa7dc4ece482e17fbfda87106fedc06b05666fa3537321","last_reissued_at":"2026-05-18T01:34:15.016253Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:34:15.016253Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1508.05808","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":"2026-05-18T01:34:15Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"LLdItvBX5nPixw3lSoVQ8MwPsVxG+6t5eK3Rj5cZyXyrF0aTBivvWXD8CdQw7BdRePGXUqYeg0csItJdf1BlDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-31T09:32:04.984012Z"},"content_sha256":"851104ced512ec288d71338bb980630a3abb3dda32574048c6e3c2988f9c9ff3","schema_version":"1.0","event_id":"sha256:851104ced512ec288d71338bb980630a3abb3dda32574048c6e3c2988f9c9ff3"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2015:344MX6WEQZQCC3FKPXCOZZEC4F","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Distributed Autoregressive Moving Average Graph Filters","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.DC","cs.IT","math.IT"],"primary_cat":"cs.SI","authors_text":"Andrea Simonetto, Andreas Loukas, Geert Leus","submitted_at":"2015-04-24T17:45:51Z","abstract_excerpt":"We introduce the concept of autoregressive moving average (ARMA) filters on a graph and show how they can be implemented in a distributed fashion. Our graph filter design philosophy is independent of the particular graph, meaning that the filter coefficients are derived irrespective of the graph. In contrast to finite-impulse response (FIR) graph filters, ARMA graph filters are robust against changes in the signal and/or graph. In addition, when time-varying signals are considered, we prove that the proposed graph filters behave as ARMA filters in the graph domain and, depending on the impleme"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1508.05808","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":"2026-05-18T01:34:15Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"7FJnrnuCLm1/IWzV/KMtF7u36NRtmydO6t5QpKK2YU3VwXq2VJ5EhAp1aKYcMmN79jLfQGE8tpE5Dr+HhB86CA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-31T09:32:04.984582Z"},"content_sha256":"6f4a70522f4c0eb9bce6d9d94bcb2ce05151f7d703b25abcdd719b4e09ef95fd","schema_version":"1.0","event_id":"sha256:6f4a70522f4c0eb9bce6d9d94bcb2ce05151f7d703b25abcdd719b4e09ef95fd"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/344MX6WEQZQCC3FKPXCOZZEC4F/bundle.json","state_url":"https://pith.science/pith/344MX6WEQZQCC3FKPXCOZZEC4F/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/344MX6WEQZQCC3FKPXCOZZEC4F/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":"2026-05-31T09:32:04Z","links":{"resolver":"https://pith.science/pith/344MX6WEQZQCC3FKPXCOZZEC4F","bundle":"https://pith.science/pith/344MX6WEQZQCC3FKPXCOZZEC4F/bundle.json","state":"https://pith.science/pith/344MX6WEQZQCC3FKPXCOZZEC4F/state.json","well_known_bundle":"https://pith.science/.well-known/pith/344MX6WEQZQCC3FKPXCOZZEC4F/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2015:344MX6WEQZQCC3FKPXCOZZEC4F","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":"b1f11670efa9c7d934442e64b4c58f7f8a86f0da0b380e59aa5adff93ecf1a06","cross_cats_sorted":["cs.DC","cs.IT","math.IT"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SI","submitted_at":"2015-04-24T17:45:51Z","title_canon_sha256":"209466841c4949af7cbd2046d5ba32b93249a8b87c64ba8202dc8fd5feb8c0a7"},"schema_version":"1.0","source":{"id":"1508.05808","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1508.05808","created_at":"2026-05-18T01:34:15Z"},{"alias_kind":"arxiv_version","alias_value":"1508.05808v1","created_at":"2026-05-18T01:34:15Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1508.05808","created_at":"2026-05-18T01:34:15Z"},{"alias_kind":"pith_short_12","alias_value":"344MX6WEQZQC","created_at":"2026-05-18T12:29:02Z"},{"alias_kind":"pith_short_16","alias_value":"344MX6WEQZQCC3FK","created_at":"2026-05-18T12:29:02Z"},{"alias_kind":"pith_short_8","alias_value":"344MX6WE","created_at":"2026-05-18T12:29:02Z"}],"graph_snapshots":[{"event_id":"sha256:6f4a70522f4c0eb9bce6d9d94bcb2ce05151f7d703b25abcdd719b4e09ef95fd","target":"graph","created_at":"2026-05-18T01:34:15Z","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 introduce the concept of autoregressive moving average (ARMA) filters on a graph and show how they can be implemented in a distributed fashion. Our graph filter design philosophy is independent of the particular graph, meaning that the filter coefficients are derived irrespective of the graph. In contrast to finite-impulse response (FIR) graph filters, ARMA graph filters are robust against changes in the signal and/or graph. In addition, when time-varying signals are considered, we prove that the proposed graph filters behave as ARMA filters in the graph domain and, depending on the impleme","authors_text":"Andrea Simonetto, Andreas Loukas, Geert Leus","cross_cats":["cs.DC","cs.IT","math.IT"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SI","submitted_at":"2015-04-24T17:45:51Z","title":"Distributed Autoregressive Moving Average Graph Filters"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1508.05808","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":"sha256:851104ced512ec288d71338bb980630a3abb3dda32574048c6e3c2988f9c9ff3","target":"record","created_at":"2026-05-18T01:34:15Z","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":"b1f11670efa9c7d934442e64b4c58f7f8a86f0da0b380e59aa5adff93ecf1a06","cross_cats_sorted":["cs.DC","cs.IT","math.IT"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SI","submitted_at":"2015-04-24T17:45:51Z","title_canon_sha256":"209466841c4949af7cbd2046d5ba32b93249a8b87c64ba8202dc8fd5feb8c0a7"},"schema_version":"1.0","source":{"id":"1508.05808","kind":"arxiv","version":1}},"canonical_sha256":"df38cbfac48660216caa7dc4ece482e17fbfda87106fedc06b05666fa3537321","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"df38cbfac48660216caa7dc4ece482e17fbfda87106fedc06b05666fa3537321","first_computed_at":"2026-05-18T01:34:15.016253Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T01:34:15.016253Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"iq4lgI8b+hfszporEtkM8IEWHF821Vl7MoZM3s/Bj3eAzScCymVo+/wq9P+6I0+0zNbhl56LcEXXeLpeqiSSBg==","signature_status":"signed_v1","signed_at":"2026-05-18T01:34:15.016974Z","signed_message":"canonical_sha256_bytes"},"source_id":"1508.05808","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:851104ced512ec288d71338bb980630a3abb3dda32574048c6e3c2988f9c9ff3","sha256:6f4a70522f4c0eb9bce6d9d94bcb2ce05151f7d703b25abcdd719b4e09ef95fd"],"state_sha256":"53dc29cb8137b8f5c4f4991dffbad7eac029949a7c4674045ee4dda4d2552678"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"pvivjGvyUxXtdZaCZS5jFI3l/thZPH53SkZuFu/1QFZkKiyRJOCyTu39ZtE5nSToKGFf0cV3j4/9ccg4XcigBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-31T09:32:04.988286Z","bundle_sha256":"d212f4da051db3cd04dfc90384a20d5573c1282373ba1bb90af5211f0ffffdaa"}}