{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2018:6HL5GVXUKLROFNNVQGZML4PAYD","short_pith_number":"pith:6HL5GVXU","schema_version":"1.0","canonical_sha256":"f1d7d356f452e2e2b5b581b2c5f1e0c0db4cd0866de40a35047321a852620a3f","source":{"kind":"arxiv","id":"1811.07715","version":1},"attestation_state":"computed","paper":{"title":"Histogram-Free Multicanonical Monte Carlo Sampling to Calculate the Density of States","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cond-mat.stat-mech","stat.CO"],"primary_cat":"physics.comp-ph","authors_text":"Alfred C. K. Farris, Markus Eisenbach, Ying Wai Li","submitted_at":"2018-11-15T20:26:43Z","abstract_excerpt":"We report a new multicanonical Monte Carlo algorithm to obtain the density of states for physical systems with continuous state variables in statistical mechanics. Our algorithm is able to obtain a closed-form expression for the density of states expressed in a chosen basis set, instead of a numerical array of finite resolution as in previous variants of this class of MC methods such as the multicanonical sampling and Wang-Landau sampling. This is enabled by storing the visited states directly and avoiding the explicit collection of a histogram. This practice also has the advantage of avoiding"},"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":"1811.07715","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"physics.comp-ph","submitted_at":"2018-11-15T20:26:43Z","cross_cats_sorted":["cond-mat.stat-mech","stat.CO"],"title_canon_sha256":"9ca5f34b1034930bed966c15efc6c25887ba9a14b685f7c25dde86c8b74d4cff","abstract_canon_sha256":"689dcca06343805878d2f375521793c8f99dff59722a98e980f2d5bc801811d3"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:00:23.644732Z","signature_b64":"f+A2774hgnUoYp4LaIqwMLZqlVRFIJwDKV3wRRLmiH8bfsNIBzaGWkrIC4dfK1avUnK+DRFwYzuCsclqLS7fDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f1d7d356f452e2e2b5b581b2c5f1e0c0db4cd0866de40a35047321a852620a3f","last_reissued_at":"2026-05-18T00:00:23.644137Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:00:23.644137Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Histogram-Free Multicanonical Monte Carlo Sampling to Calculate the Density of States","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cond-mat.stat-mech","stat.CO"],"primary_cat":"physics.comp-ph","authors_text":"Alfred C. K. Farris, Markus Eisenbach, Ying Wai Li","submitted_at":"2018-11-15T20:26:43Z","abstract_excerpt":"We report a new multicanonical Monte Carlo algorithm to obtain the density of states for physical systems with continuous state variables in statistical mechanics. Our algorithm is able to obtain a closed-form expression for the density of states expressed in a chosen basis set, instead of a numerical array of finite resolution as in previous variants of this class of MC methods such as the multicanonical sampling and Wang-Landau sampling. This is enabled by storing the visited states directly and avoiding the explicit collection of a histogram. This practice also has the advantage of avoiding"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1811.07715","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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1811.07715","created_at":"2026-05-18T00:00:23.644233+00:00"},{"alias_kind":"arxiv_version","alias_value":"1811.07715v1","created_at":"2026-05-18T00:00:23.644233+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1811.07715","created_at":"2026-05-18T00:00:23.644233+00:00"},{"alias_kind":"pith_short_12","alias_value":"6HL5GVXUKLRO","created_at":"2026-05-18T12:32:08.215937+00:00"},{"alias_kind":"pith_short_16","alias_value":"6HL5GVXUKLROFNNV","created_at":"2026-05-18T12:32:08.215937+00:00"},{"alias_kind":"pith_short_8","alias_value":"6HL5GVXU","created_at":"2026-05-18T12:32:08.215937+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/6HL5GVXUKLROFNNVQGZML4PAYD","json":"https://pith.science/pith/6HL5GVXUKLROFNNVQGZML4PAYD.json","graph_json":"https://pith.science/api/pith-number/6HL5GVXUKLROFNNVQGZML4PAYD/graph.json","events_json":"https://pith.science/api/pith-number/6HL5GVXUKLROFNNVQGZML4PAYD/events.json","paper":"https://pith.science/paper/6HL5GVXU"},"agent_actions":{"view_html":"https://pith.science/pith/6HL5GVXUKLROFNNVQGZML4PAYD","download_json":"https://pith.science/pith/6HL5GVXUKLROFNNVQGZML4PAYD.json","view_paper":"https://pith.science/paper/6HL5GVXU","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1811.07715&json=true","fetch_graph":"https://pith.science/api/pith-number/6HL5GVXUKLROFNNVQGZML4PAYD/graph.json","fetch_events":"https://pith.science/api/pith-number/6HL5GVXUKLROFNNVQGZML4PAYD/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/6HL5GVXUKLROFNNVQGZML4PAYD/action/timestamp_anchor","attest_storage":"https://pith.science/pith/6HL5GVXUKLROFNNVQGZML4PAYD/action/storage_attestation","attest_author":"https://pith.science/pith/6HL5GVXUKLROFNNVQGZML4PAYD/action/author_attestation","sign_citation":"https://pith.science/pith/6HL5GVXUKLROFNNVQGZML4PAYD/action/citation_signature","submit_replication":"https://pith.science/pith/6HL5GVXUKLROFNNVQGZML4PAYD/action/replication_record"}},"created_at":"2026-05-18T00:00:23.644233+00:00","updated_at":"2026-05-18T00:00:23.644233+00:00"}