{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2015:SXZZPOKBOVVPYCIZBA2LF4XIEO","short_pith_number":"pith:SXZZPOKB","canonical_record":{"source":{"id":"1503.01631","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.CO","submitted_at":"2015-03-05T13:37:13Z","cross_cats_sorted":[],"title_canon_sha256":"9bff5385184539ab4f6608cbb7bbde1c55df6be9832cffe8812ce5f3a5b38105","abstract_canon_sha256":"0990cc6a7a3981136ccf0d87aeacc31c60929b878054f6913667d80c9c7b35ab"},"schema_version":"1.0"},"canonical_sha256":"95f397b941756afc09190834b2f2e82387a60649e6cf732c4d20fd4ad8c27825","source":{"kind":"arxiv","id":"1503.01631","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1503.01631","created_at":"2026-05-18T02:25:33Z"},{"alias_kind":"arxiv_version","alias_value":"1503.01631v1","created_at":"2026-05-18T02:25:33Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1503.01631","created_at":"2026-05-18T02:25:33Z"},{"alias_kind":"pith_short_12","alias_value":"SXZZPOKBOVVP","created_at":"2026-05-18T12:29:42Z"},{"alias_kind":"pith_short_16","alias_value":"SXZZPOKBOVVPYCIZ","created_at":"2026-05-18T12:29:42Z"},{"alias_kind":"pith_short_8","alias_value":"SXZZPOKB","created_at":"2026-05-18T12:29:42Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2015:SXZZPOKBOVVPYCIZBA2LF4XIEO","target":"record","payload":{"canonical_record":{"source":{"id":"1503.01631","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.CO","submitted_at":"2015-03-05T13:37:13Z","cross_cats_sorted":[],"title_canon_sha256":"9bff5385184539ab4f6608cbb7bbde1c55df6be9832cffe8812ce5f3a5b38105","abstract_canon_sha256":"0990cc6a7a3981136ccf0d87aeacc31c60929b878054f6913667d80c9c7b35ab"},"schema_version":"1.0"},"canonical_sha256":"95f397b941756afc09190834b2f2e82387a60649e6cf732c4d20fd4ad8c27825","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T02:25:33.248724Z","signature_b64":"QvhwHWfDgK4zKVwld8SIlfOnFp48GjIdg9YW6yxOAe+Gtt8jMStG7yBWAlqOnoLCmWP0wSBNQnPp15wkelPtCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"95f397b941756afc09190834b2f2e82387a60649e6cf732c4d20fd4ad8c27825","last_reissued_at":"2026-05-18T02:25:33.248268Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T02:25:33.248268Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1503.01631","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":"2026-05-18T02:25:33Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"oj0uamowr5iqur9GGn5H0fNhKg05EI8KM9HESDmzbpzMYquIZvum55LF46Hg3IOw9pAmAYNUbCTz8PoixdWSAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-04T15:36:23.540571Z"},"content_sha256":"126968b036de0413ea98d72adfa421fb4fe3edec1ee12304182426928cb7bdfb","schema_version":"1.0","event_id":"sha256:126968b036de0413ea98d72adfa421fb4fe3edec1ee12304182426928cb7bdfb"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2015:SXZZPOKBOVVPYCIZBA2LF4XIEO","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Application of Sequential Quasi-Monte Carlo to Autonomous Positioning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"stat.CO","authors_text":"Mathieu Gerber, Nicolas Chopin","submitted_at":"2015-03-05T13:37:13Z","abstract_excerpt":"Sequential Monte Carlo algorithms (also known as particle filters) are popular methods to approximate filtering (and related) distributions of state-space models. However, they converge at the slow $1/\\sqrt{N}$ rate, which may be an issue in real-time data-intensive scenarios. We give a brief outline of SQMC (Sequential Quasi-Monte Carlo), a variant of SMC based on low-discrepancy point sets proposed by Gerber and Chopin (2015), which converges at a faster rate, and we illustrate the greater performance of SQMC on autonomous positioning problems."},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1503.01631","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":"2026-05-18T02:25:33Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"CREyqHt7yKrhWa1M1V0uAfDseadDb1JGwasobkBvMgMD847gBpD2vn5RYIEpWdG3RvJVZ/62qPIf4Qe6toQDAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-04T15:36:23.541071Z"},"content_sha256":"7b366efd9d174b3f68cab556051b571b528bceb91450c56323d259e7db6bd052","schema_version":"1.0","event_id":"sha256:7b366efd9d174b3f68cab556051b571b528bceb91450c56323d259e7db6bd052"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/SXZZPOKBOVVPYCIZBA2LF4XIEO/bundle.json","state_url":"https://pith.science/pith/SXZZPOKBOVVPYCIZBA2LF4XIEO/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/SXZZPOKBOVVPYCIZBA2LF4XIEO/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":"2026-06-04T15:36:23Z","links":{"resolver":"https://pith.science/pith/SXZZPOKBOVVPYCIZBA2LF4XIEO","bundle":"https://pith.science/pith/SXZZPOKBOVVPYCIZBA2LF4XIEO/bundle.json","state":"https://pith.science/pith/SXZZPOKBOVVPYCIZBA2LF4XIEO/state.json","well_known_bundle":"https://pith.science/.well-known/pith/SXZZPOKBOVVPYCIZBA2LF4XIEO/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2015:SXZZPOKBOVVPYCIZBA2LF4XIEO","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":"0990cc6a7a3981136ccf0d87aeacc31c60929b878054f6913667d80c9c7b35ab","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.CO","submitted_at":"2015-03-05T13:37:13Z","title_canon_sha256":"9bff5385184539ab4f6608cbb7bbde1c55df6be9832cffe8812ce5f3a5b38105"},"schema_version":"1.0","source":{"id":"1503.01631","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1503.01631","created_at":"2026-05-18T02:25:33Z"},{"alias_kind":"arxiv_version","alias_value":"1503.01631v1","created_at":"2026-05-18T02:25:33Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1503.01631","created_at":"2026-05-18T02:25:33Z"},{"alias_kind":"pith_short_12","alias_value":"SXZZPOKBOVVP","created_at":"2026-05-18T12:29:42Z"},{"alias_kind":"pith_short_16","alias_value":"SXZZPOKBOVVPYCIZ","created_at":"2026-05-18T12:29:42Z"},{"alias_kind":"pith_short_8","alias_value":"SXZZPOKB","created_at":"2026-05-18T12:29:42Z"}],"graph_snapshots":[{"event_id":"sha256:7b366efd9d174b3f68cab556051b571b528bceb91450c56323d259e7db6bd052","target":"graph","created_at":"2026-05-18T02:25:33Z","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":"Sequential Monte Carlo algorithms (also known as particle filters) are popular methods to approximate filtering (and related) distributions of state-space models. However, they converge at the slow $1/\\sqrt{N}$ rate, which may be an issue in real-time data-intensive scenarios. We give a brief outline of SQMC (Sequential Quasi-Monte Carlo), a variant of SMC based on low-discrepancy point sets proposed by Gerber and Chopin (2015), which converges at a faster rate, and we illustrate the greater performance of SQMC on autonomous positioning problems.","authors_text":"Mathieu Gerber, Nicolas Chopin","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.CO","submitted_at":"2015-03-05T13:37:13Z","title":"Application of Sequential Quasi-Monte Carlo to Autonomous Positioning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1503.01631","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":"sha256:126968b036de0413ea98d72adfa421fb4fe3edec1ee12304182426928cb7bdfb","target":"record","created_at":"2026-05-18T02:25:33Z","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":"0990cc6a7a3981136ccf0d87aeacc31c60929b878054f6913667d80c9c7b35ab","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.CO","submitted_at":"2015-03-05T13:37:13Z","title_canon_sha256":"9bff5385184539ab4f6608cbb7bbde1c55df6be9832cffe8812ce5f3a5b38105"},"schema_version":"1.0","source":{"id":"1503.01631","kind":"arxiv","version":1}},"canonical_sha256":"95f397b941756afc09190834b2f2e82387a60649e6cf732c4d20fd4ad8c27825","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"95f397b941756afc09190834b2f2e82387a60649e6cf732c4d20fd4ad8c27825","first_computed_at":"2026-05-18T02:25:33.248268Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T02:25:33.248268Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"QvhwHWfDgK4zKVwld8SIlfOnFp48GjIdg9YW6yxOAe+Gtt8jMStG7yBWAlqOnoLCmWP0wSBNQnPp15wkelPtCw==","signature_status":"signed_v1","signed_at":"2026-05-18T02:25:33.248724Z","signed_message":"canonical_sha256_bytes"},"source_id":"1503.01631","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:126968b036de0413ea98d72adfa421fb4fe3edec1ee12304182426928cb7bdfb","sha256:7b366efd9d174b3f68cab556051b571b528bceb91450c56323d259e7db6bd052"],"state_sha256":"2f90ed3d7a01b5acdd6d5b0e4a00f37b31b2325bde851956d7ed28d157e65ed0"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Une2Q5RbJezymtCFDy/sOYTTZ3QuB3jMjSn+n62yNr45MZzq4bK2aHFwqsGm6uJKMxMlVXLII9qL7JOZXD/fCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-04T15:36:23.543778Z","bundle_sha256":"e7cb5c9662f66d6d38f6393e6454055ffdd123ee35e9b6e0adf3c210a5bcb71c"}}