{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2016:BXFOGVRB2J4B6RNZJ7UGR6KZZP","short_pith_number":"pith:BXFOGVRB","canonical_record":{"source":{"id":"1605.01150","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cond-mat.stat-mech","submitted_at":"2016-05-04T05:59:29Z","cross_cats_sorted":["physics.data-an","q-bio.BM"],"title_canon_sha256":"dfa8bf811295a372cfbddaecee36dcee0b99dc72d4f8796eed321b4c4fefcbfe","abstract_canon_sha256":"05a1f3a219fd245a9d1b6dd8e3b697971183fc4b3ae9a44fa2e69b724baf3353"},"schema_version":"1.0"},"canonical_sha256":"0dcae35621d2781f45b94fe868f959cbdb3b38770ce0abbeb17ce76fe7bbb7ef","source":{"kind":"arxiv","id":"1605.01150","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1605.01150","created_at":"2026-05-18T01:10:05Z"},{"alias_kind":"arxiv_version","alias_value":"1605.01150v2","created_at":"2026-05-18T01:10:05Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1605.01150","created_at":"2026-05-18T01:10:05Z"},{"alias_kind":"pith_short_12","alias_value":"BXFOGVRB2J4B","created_at":"2026-05-18T12:30:09Z"},{"alias_kind":"pith_short_16","alias_value":"BXFOGVRB2J4B6RNZ","created_at":"2026-05-18T12:30:09Z"},{"alias_kind":"pith_short_8","alias_value":"BXFOGVRB","created_at":"2026-05-18T12:30:09Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2016:BXFOGVRB2J4B6RNZJ7UGR6KZZP","target":"record","payload":{"canonical_record":{"source":{"id":"1605.01150","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cond-mat.stat-mech","submitted_at":"2016-05-04T05:59:29Z","cross_cats_sorted":["physics.data-an","q-bio.BM"],"title_canon_sha256":"dfa8bf811295a372cfbddaecee36dcee0b99dc72d4f8796eed321b4c4fefcbfe","abstract_canon_sha256":"05a1f3a219fd245a9d1b6dd8e3b697971183fc4b3ae9a44fa2e69b724baf3353"},"schema_version":"1.0"},"canonical_sha256":"0dcae35621d2781f45b94fe868f959cbdb3b38770ce0abbeb17ce76fe7bbb7ef","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:10:05.294477Z","signature_b64":"A6kWXW9ce2HNTmnq9qsAf2DzypSupviJaPt+zL5Qm08/PRoDKj/2hwye+PhjJnJgokciuPfVlVxwBxUhq8fAAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"0dcae35621d2781f45b94fe868f959cbdb3b38770ce0abbeb17ce76fe7bbb7ef","last_reissued_at":"2026-05-18T01:10:05.293725Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:10:05.293725Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1605.01150","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":"2026-05-18T01:10:05Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"CD6sZs0busnD0pteoN0ZXG0hl/bgVWpv6VA3vQDtThx4c8KFjvMjgnRmj1BgFlWGZj1PGXg/8Msim24wF3alAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-30T08:52:32.766168Z"},"content_sha256":"1205940bc57e61b6d9eace901f95054fe4564e0d49385fcab43c39c2e349e812","schema_version":"1.0","event_id":"sha256:1205940bc57e61b6d9eace901f95054fe4564e0d49385fcab43c39c2e349e812"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2016:BXFOGVRB2J4B6RNZJ7UGR6KZZP","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Optimized Markov State Models for Metastable Systems","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["physics.data-an","q-bio.BM"],"primary_cat":"cond-mat.stat-mech","authors_text":"Enrico Guarnera, Eric Vanden-Eijnden","submitted_at":"2016-05-04T05:59:29Z","abstract_excerpt":"A method is proposed to identify target states that optimize a metastability index amongst a set of trial states and use these target states as milestones (or core sets) to build Markov State Models (MSMs). If the optimized metastability index is small, this automatically guarantees the accuracy of the MSM, in the sense that the transitions between the target milestones is indeed approximately Markovian. The method is simple to implement and use, it does not require that the dynamics on the trial milestones be Markovian, and it also offers the possibility to partition the system's state-space "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1605.01150","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":"2026-05-18T01:10:05Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"JLDy6pOlkJiEKaR+HNrHU3xxVXyAIiC8KRiswx9FkNMplXJHK0cm0FcU57FQ15uhBDGe+EGVj9v3EDB4oX4/DQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-30T08:52:32.766543Z"},"content_sha256":"1eef6a71f4622e8cbb768cff04a049ee798271c633db447c53b8d36f37a3b121","schema_version":"1.0","event_id":"sha256:1eef6a71f4622e8cbb768cff04a049ee798271c633db447c53b8d36f37a3b121"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/BXFOGVRB2J4B6RNZJ7UGR6KZZP/bundle.json","state_url":"https://pith.science/pith/BXFOGVRB2J4B6RNZJ7UGR6KZZP/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/BXFOGVRB2J4B6RNZJ7UGR6KZZP/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":"2026-05-30T08:52:32Z","links":{"resolver":"https://pith.science/pith/BXFOGVRB2J4B6RNZJ7UGR6KZZP","bundle":"https://pith.science/pith/BXFOGVRB2J4B6RNZJ7UGR6KZZP/bundle.json","state":"https://pith.science/pith/BXFOGVRB2J4B6RNZJ7UGR6KZZP/state.json","well_known_bundle":"https://pith.science/.well-known/pith/BXFOGVRB2J4B6RNZJ7UGR6KZZP/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2016:BXFOGVRB2J4B6RNZJ7UGR6KZZP","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":"05a1f3a219fd245a9d1b6dd8e3b697971183fc4b3ae9a44fa2e69b724baf3353","cross_cats_sorted":["physics.data-an","q-bio.BM"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cond-mat.stat-mech","submitted_at":"2016-05-04T05:59:29Z","title_canon_sha256":"dfa8bf811295a372cfbddaecee36dcee0b99dc72d4f8796eed321b4c4fefcbfe"},"schema_version":"1.0","source":{"id":"1605.01150","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1605.01150","created_at":"2026-05-18T01:10:05Z"},{"alias_kind":"arxiv_version","alias_value":"1605.01150v2","created_at":"2026-05-18T01:10:05Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1605.01150","created_at":"2026-05-18T01:10:05Z"},{"alias_kind":"pith_short_12","alias_value":"BXFOGVRB2J4B","created_at":"2026-05-18T12:30:09Z"},{"alias_kind":"pith_short_16","alias_value":"BXFOGVRB2J4B6RNZ","created_at":"2026-05-18T12:30:09Z"},{"alias_kind":"pith_short_8","alias_value":"BXFOGVRB","created_at":"2026-05-18T12:30:09Z"}],"graph_snapshots":[{"event_id":"sha256:1eef6a71f4622e8cbb768cff04a049ee798271c633db447c53b8d36f37a3b121","target":"graph","created_at":"2026-05-18T01:10:05Z","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":"A method is proposed to identify target states that optimize a metastability index amongst a set of trial states and use these target states as milestones (or core sets) to build Markov State Models (MSMs). If the optimized metastability index is small, this automatically guarantees the accuracy of the MSM, in the sense that the transitions between the target milestones is indeed approximately Markovian. The method is simple to implement and use, it does not require that the dynamics on the trial milestones be Markovian, and it also offers the possibility to partition the system's state-space ","authors_text":"Enrico Guarnera, Eric Vanden-Eijnden","cross_cats":["physics.data-an","q-bio.BM"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cond-mat.stat-mech","submitted_at":"2016-05-04T05:59:29Z","title":"Optimized Markov State Models for Metastable Systems"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1605.01150","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":"sha256:1205940bc57e61b6d9eace901f95054fe4564e0d49385fcab43c39c2e349e812","target":"record","created_at":"2026-05-18T01:10:05Z","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":"05a1f3a219fd245a9d1b6dd8e3b697971183fc4b3ae9a44fa2e69b724baf3353","cross_cats_sorted":["physics.data-an","q-bio.BM"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cond-mat.stat-mech","submitted_at":"2016-05-04T05:59:29Z","title_canon_sha256":"dfa8bf811295a372cfbddaecee36dcee0b99dc72d4f8796eed321b4c4fefcbfe"},"schema_version":"1.0","source":{"id":"1605.01150","kind":"arxiv","version":2}},"canonical_sha256":"0dcae35621d2781f45b94fe868f959cbdb3b38770ce0abbeb17ce76fe7bbb7ef","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"0dcae35621d2781f45b94fe868f959cbdb3b38770ce0abbeb17ce76fe7bbb7ef","first_computed_at":"2026-05-18T01:10:05.293725Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T01:10:05.293725Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"A6kWXW9ce2HNTmnq9qsAf2DzypSupviJaPt+zL5Qm08/PRoDKj/2hwye+PhjJnJgokciuPfVlVxwBxUhq8fAAA==","signature_status":"signed_v1","signed_at":"2026-05-18T01:10:05.294477Z","signed_message":"canonical_sha256_bytes"},"source_id":"1605.01150","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:1205940bc57e61b6d9eace901f95054fe4564e0d49385fcab43c39c2e349e812","sha256:1eef6a71f4622e8cbb768cff04a049ee798271c633db447c53b8d36f37a3b121"],"state_sha256":"ac7dfbce0a90385d99de52bb18a26cc488e2483ddfbcb57dd7c0f058cd0c347c"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"WctlyNg/0NkNqKTwKJdH4FmxO+pMkWEHnzrxRRTCw+Nfyt2PS7rfqkaWlJkT196mzEfw+6xnRJwza5XtDdewBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-30T08:52:32.768720Z","bundle_sha256":"615ec8b2580a4ce3ec69119b6a636a6e29e4b0cfb6d279985a167c92295a74da"}}