{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2015:IY3PQ3CQIZFBL26SJLKWU2KRB7","short_pith_number":"pith:IY3PQ3CQ","schema_version":"1.0","canonical_sha256":"4636f86c50464a15ebd24ad56a69510fcf93b585cc858c2610a037fa09c2b4c8","source":{"kind":"arxiv","id":"1509.06145","version":3},"attestation_state":"computed","paper":{"title":"Caliber based spectral gap optimization of order parameters (SGOOP) for sampling complex molecular systems","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cond-mat.soft","physics.chem-ph"],"primary_cat":"cond-mat.stat-mech","authors_text":"B. J. Berne, Pratyush Tiwary","submitted_at":"2015-09-21T08:43:54Z","abstract_excerpt":"In modern day simulations of many-body systems much of the computational complexity is shifted to the identification of slowly changing molecular order parameters called collective variables (CV) or reaction coordinates. A vast array of enhanced sampling methods are based on the identification and biasing of these low-dimensional order parameters, whose fluctuations are important in driving rare events of interest. Here describe a new algorithm for finding optimal low-dimensional collective variables for use in enhanced sampling biasing methods like umbrella sampling, metadynamics and related "},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"1509.06145","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cond-mat.stat-mech","submitted_at":"2015-09-21T08:43:54Z","cross_cats_sorted":["cond-mat.soft","physics.chem-ph"],"title_canon_sha256":"5dac566853f965303edb0264293c5a0827c54a62fa9726d9fbba3de8b6e2b8ad","abstract_canon_sha256":"3cdf8efaf1fa924d1e25c756da76c0baf74bf2cc0685657be5876a5da1209661"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:16:17.947736Z","signature_b64":"5Qnk9CnswFdC6/oa5tmSMloXTo+WqXqZMN1XRzrgKSitpjkSq48OtxqZMXH72rzbfuzmVK6cg8lygNFzTGwSAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"4636f86c50464a15ebd24ad56a69510fcf93b585cc858c2610a037fa09c2b4c8","last_reissued_at":"2026-05-18T01:16:17.946975Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:16:17.946975Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Caliber based spectral gap optimization of order parameters (SGOOP) for sampling complex molecular systems","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cond-mat.soft","physics.chem-ph"],"primary_cat":"cond-mat.stat-mech","authors_text":"B. J. Berne, Pratyush Tiwary","submitted_at":"2015-09-21T08:43:54Z","abstract_excerpt":"In modern day simulations of many-body systems much of the computational complexity is shifted to the identification of slowly changing molecular order parameters called collective variables (CV) or reaction coordinates. A vast array of enhanced sampling methods are based on the identification and biasing of these low-dimensional order parameters, whose fluctuations are important in driving rare events of interest. Here describe a new algorithm for finding optimal low-dimensional collective variables for use in enhanced sampling biasing methods like umbrella sampling, metadynamics and related "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1509.06145","kind":"arxiv","version":3},"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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1509.06145","created_at":"2026-05-18T01:16:17.947100+00:00"},{"alias_kind":"arxiv_version","alias_value":"1509.06145v3","created_at":"2026-05-18T01:16:17.947100+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1509.06145","created_at":"2026-05-18T01:16:17.947100+00:00"},{"alias_kind":"pith_short_12","alias_value":"IY3PQ3CQIZFB","created_at":"2026-05-18T12:29:27.538025+00:00"},{"alias_kind":"pith_short_16","alias_value":"IY3PQ3CQIZFBL26S","created_at":"2026-05-18T12:29:27.538025+00:00"},{"alias_kind":"pith_short_8","alias_value":"IY3PQ3CQ","created_at":"2026-05-18T12:29:27.538025+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/IY3PQ3CQIZFBL26SJLKWU2KRB7","json":"https://pith.science/pith/IY3PQ3CQIZFBL26SJLKWU2KRB7.json","graph_json":"https://pith.science/api/pith-number/IY3PQ3CQIZFBL26SJLKWU2KRB7/graph.json","events_json":"https://pith.science/api/pith-number/IY3PQ3CQIZFBL26SJLKWU2KRB7/events.json","paper":"https://pith.science/paper/IY3PQ3CQ"},"agent_actions":{"view_html":"https://pith.science/pith/IY3PQ3CQIZFBL26SJLKWU2KRB7","download_json":"https://pith.science/pith/IY3PQ3CQIZFBL26SJLKWU2KRB7.json","view_paper":"https://pith.science/paper/IY3PQ3CQ","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1509.06145&json=true","fetch_graph":"https://pith.science/api/pith-number/IY3PQ3CQIZFBL26SJLKWU2KRB7/graph.json","fetch_events":"https://pith.science/api/pith-number/IY3PQ3CQIZFBL26SJLKWU2KRB7/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/IY3PQ3CQIZFBL26SJLKWU2KRB7/action/timestamp_anchor","attest_storage":"https://pith.science/pith/IY3PQ3CQIZFBL26SJLKWU2KRB7/action/storage_attestation","attest_author":"https://pith.science/pith/IY3PQ3CQIZFBL26SJLKWU2KRB7/action/author_attestation","sign_citation":"https://pith.science/pith/IY3PQ3CQIZFBL26SJLKWU2KRB7/action/citation_signature","submit_replication":"https://pith.science/pith/IY3PQ3CQIZFBL26SJLKWU2KRB7/action/replication_record"}},"created_at":"2026-05-18T01:16:17.947100+00:00","updated_at":"2026-05-18T01:16:17.947100+00:00"}