{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2016:HW5OWJV4YTVC7RMOY2RBRXRVV5","short_pith_number":"pith:HW5OWJV4","canonical_record":{"source":{"id":"1607.03592","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.CO","submitted_at":"2016-07-13T04:37:31Z","cross_cats_sorted":["cs.NA","stat.AP"],"title_canon_sha256":"9e67ed0d81b4f6b517c66c97064bafd91d2badf1a74158f644161634d0749ac1","abstract_canon_sha256":"c9b94b285536b9e65d9f04ebc9c677234ecb4e0a6eda91c4404ca608b620f847"},"schema_version":"1.0"},"canonical_sha256":"3dbaeb26bcc4ea2fc58ec6a218de35af6e68aa1a05c3823e8369dc929535aac1","source":{"kind":"arxiv","id":"1607.03592","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1607.03592","created_at":"2026-05-18T01:08:32Z"},{"alias_kind":"arxiv_version","alias_value":"1607.03592v2","created_at":"2026-05-18T01:08:32Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1607.03592","created_at":"2026-05-18T01:08:32Z"},{"alias_kind":"pith_short_12","alias_value":"HW5OWJV4YTVC","created_at":"2026-05-18T12:30:22Z"},{"alias_kind":"pith_short_16","alias_value":"HW5OWJV4YTVC7RMO","created_at":"2026-05-18T12:30:22Z"},{"alias_kind":"pith_short_8","alias_value":"HW5OWJV4","created_at":"2026-05-18T12:30:22Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2016:HW5OWJV4YTVC7RMOY2RBRXRVV5","target":"record","payload":{"canonical_record":{"source":{"id":"1607.03592","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.CO","submitted_at":"2016-07-13T04:37:31Z","cross_cats_sorted":["cs.NA","stat.AP"],"title_canon_sha256":"9e67ed0d81b4f6b517c66c97064bafd91d2badf1a74158f644161634d0749ac1","abstract_canon_sha256":"c9b94b285536b9e65d9f04ebc9c677234ecb4e0a6eda91c4404ca608b620f847"},"schema_version":"1.0"},"canonical_sha256":"3dbaeb26bcc4ea2fc58ec6a218de35af6e68aa1a05c3823e8369dc929535aac1","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:08:32.063710Z","signature_b64":"VbqD3lzFsz+Ebg6o9O/tCxMMqF64SX+kc+c8zDA2V6Ln2QAFAUzPA4NC6tzImtZdL/Lic9G64EhuHpAl4u7XAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3dbaeb26bcc4ea2fc58ec6a218de35af6e68aa1a05c3823e8369dc929535aac1","last_reissued_at":"2026-05-18T01:08:32.063129Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:08:32.063129Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1607.03592","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":"2026-05-18T01:08:32Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"OCfeaZfEWINWs/5uu3dVPo+04qIpwKF4z1LUkXKe5AjzddJ6vnbJb6+P/fcmLO1jSRTmMsnuO3wm64BF9XbhAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-25T07:06:50.419034Z"},"content_sha256":"f2e5177ac72a14d16e8805448420c30fc23e618a9ccdce03f8b24ff22dfbf5c4","schema_version":"1.0","event_id":"sha256:f2e5177ac72a14d16e8805448420c30fc23e618a9ccdce03f8b24ff22dfbf5c4"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2016:HW5OWJV4YTVC7RMOY2RBRXRVV5","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Cluster Sampling Filters for Non-Gaussian Data Assimilation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.NA","stat.AP"],"primary_cat":"stat.CO","authors_text":"Adrian Sandu, Ahmed Attia, Azam Moosavi","submitted_at":"2016-07-13T04:37:31Z","abstract_excerpt":"This paper presents a fully non-Gaussian version of the Hamiltonian Monte Carlo (HMC) sampling filter. The Gaussian prior assumption in the original HMC filter is relaxed. Specifically, a clustering step is introduced after the forecast phase of the filter, and the prior density function is estimated by fitting a Gaussian Mixture Model (GMM) to the prior ensemble. Using the data likelihood function, the posterior density is then formulated as a mixture density, and is sampled using a HMC approach (or any other scheme capable of sampling multimodal densities in high-dimensional subspaces). The "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1607.03592","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":"2026-05-18T01:08:32Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"DZAZmdPMD0KMH3FqwPPVVzMkKpbUfG469/bCGbJdiNbVZJie2nYr77rD46UEE1vvR1fWpW7kj9y5td6Qja5kDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-25T07:06:50.419379Z"},"content_sha256":"b994887f945a84c6d40f740013994382a91bc019f25b9c3fd3a2f996b170b727","schema_version":"1.0","event_id":"sha256:b994887f945a84c6d40f740013994382a91bc019f25b9c3fd3a2f996b170b727"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/HW5OWJV4YTVC7RMOY2RBRXRVV5/bundle.json","state_url":"https://pith.science/pith/HW5OWJV4YTVC7RMOY2RBRXRVV5/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/HW5OWJV4YTVC7RMOY2RBRXRVV5/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":"2026-06-25T07:06:50Z","links":{"resolver":"https://pith.science/pith/HW5OWJV4YTVC7RMOY2RBRXRVV5","bundle":"https://pith.science/pith/HW5OWJV4YTVC7RMOY2RBRXRVV5/bundle.json","state":"https://pith.science/pith/HW5OWJV4YTVC7RMOY2RBRXRVV5/state.json","well_known_bundle":"https://pith.science/.well-known/pith/HW5OWJV4YTVC7RMOY2RBRXRVV5/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2016:HW5OWJV4YTVC7RMOY2RBRXRVV5","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":"c9b94b285536b9e65d9f04ebc9c677234ecb4e0a6eda91c4404ca608b620f847","cross_cats_sorted":["cs.NA","stat.AP"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.CO","submitted_at":"2016-07-13T04:37:31Z","title_canon_sha256":"9e67ed0d81b4f6b517c66c97064bafd91d2badf1a74158f644161634d0749ac1"},"schema_version":"1.0","source":{"id":"1607.03592","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1607.03592","created_at":"2026-05-18T01:08:32Z"},{"alias_kind":"arxiv_version","alias_value":"1607.03592v2","created_at":"2026-05-18T01:08:32Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1607.03592","created_at":"2026-05-18T01:08:32Z"},{"alias_kind":"pith_short_12","alias_value":"HW5OWJV4YTVC","created_at":"2026-05-18T12:30:22Z"},{"alias_kind":"pith_short_16","alias_value":"HW5OWJV4YTVC7RMO","created_at":"2026-05-18T12:30:22Z"},{"alias_kind":"pith_short_8","alias_value":"HW5OWJV4","created_at":"2026-05-18T12:30:22Z"}],"graph_snapshots":[{"event_id":"sha256:b994887f945a84c6d40f740013994382a91bc019f25b9c3fd3a2f996b170b727","target":"graph","created_at":"2026-05-18T01:08:32Z","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":"This paper presents a fully non-Gaussian version of the Hamiltonian Monte Carlo (HMC) sampling filter. The Gaussian prior assumption in the original HMC filter is relaxed. Specifically, a clustering step is introduced after the forecast phase of the filter, and the prior density function is estimated by fitting a Gaussian Mixture Model (GMM) to the prior ensemble. Using the data likelihood function, the posterior density is then formulated as a mixture density, and is sampled using a HMC approach (or any other scheme capable of sampling multimodal densities in high-dimensional subspaces). The ","authors_text":"Adrian Sandu, Ahmed Attia, Azam Moosavi","cross_cats":["cs.NA","stat.AP"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.CO","submitted_at":"2016-07-13T04:37:31Z","title":"Cluster Sampling Filters for Non-Gaussian Data Assimilation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1607.03592","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:f2e5177ac72a14d16e8805448420c30fc23e618a9ccdce03f8b24ff22dfbf5c4","target":"record","created_at":"2026-05-18T01:08:32Z","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":"c9b94b285536b9e65d9f04ebc9c677234ecb4e0a6eda91c4404ca608b620f847","cross_cats_sorted":["cs.NA","stat.AP"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.CO","submitted_at":"2016-07-13T04:37:31Z","title_canon_sha256":"9e67ed0d81b4f6b517c66c97064bafd91d2badf1a74158f644161634d0749ac1"},"schema_version":"1.0","source":{"id":"1607.03592","kind":"arxiv","version":2}},"canonical_sha256":"3dbaeb26bcc4ea2fc58ec6a218de35af6e68aa1a05c3823e8369dc929535aac1","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3dbaeb26bcc4ea2fc58ec6a218de35af6e68aa1a05c3823e8369dc929535aac1","first_computed_at":"2026-05-18T01:08:32.063129Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T01:08:32.063129Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"VbqD3lzFsz+Ebg6o9O/tCxMMqF64SX+kc+c8zDA2V6Ln2QAFAUzPA4NC6tzImtZdL/Lic9G64EhuHpAl4u7XAQ==","signature_status":"signed_v1","signed_at":"2026-05-18T01:08:32.063710Z","signed_message":"canonical_sha256_bytes"},"source_id":"1607.03592","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:f2e5177ac72a14d16e8805448420c30fc23e618a9ccdce03f8b24ff22dfbf5c4","sha256:b994887f945a84c6d40f740013994382a91bc019f25b9c3fd3a2f996b170b727"],"state_sha256":"572ccee6e48fd6c74fac0fdd7bab8c3a470602875da88c30d2892c395ab4eccb"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"npuvPvBWgGH5meDdQpoyb376imKs2iwLzQQfQz73zpLXXhHIK8H9MfyUr0ZxvOod1hpKKg807r2C+tx15kmIAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-25T07:06:50.421178Z","bundle_sha256":"4cc42a7ec2d395df7b18b49596e52ce47776c00ad423bbfd2cd06ff9c8fdd2fa"}}