{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2016:JBTG2VBWVSHJIVGHKZDIHNH2JG","short_pith_number":"pith:JBTG2VBW","schema_version":"1.0","canonical_sha256":"48666d5436ac8e9454c7564683b4fa498ad3e8bac62a0e4d581f18d53c8f94a9","source":{"kind":"arxiv","id":"1610.09856","version":2},"attestation_state":"computed","paper":{"title":"Density-of-states","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"hep-lat","authors_text":"Kurt Langfeld","submitted_at":"2016-10-31T10:36:26Z","abstract_excerpt":"Although Monte Carlo calculations using Importance Sampling have matured into the most widely employed method for determining first principle results in QCD, they spectacularly fail for theories with a sign problem or for which certain rare configurations play an important role. Non-Markovian Random walks, based upon iterative refinements of the density-of-states, overcome such overlap problems. I will review the Linear Logarithmic Relaxation (LLR) method and, in particular, focus onto ergodicity and exponential error suppression. Applications include the high-state Potts model, SU(2) and SU(3"},"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":"1610.09856","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"hep-lat","submitted_at":"2016-10-31T10:36:26Z","cross_cats_sorted":[],"title_canon_sha256":"e23b5b55215690692c10780111298a9319172e3ab45e40d5850dd3b486e1bd6e","abstract_canon_sha256":"d58f7999fe453fb9bf953f07c64a78ae3e44a15c3f35372f86f58b00ace916e5"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:52:14.168471Z","signature_b64":"DnIEZK8xMmqvPV11ZdgXObfWbIqdQyUKJ1CgK+VWzfN7J5Q2zcEk3xFXPRNcOzGWygkua5MyOuVWB97Ebi7qDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"48666d5436ac8e9454c7564683b4fa498ad3e8bac62a0e4d581f18d53c8f94a9","last_reissued_at":"2026-05-18T00:52:14.167964Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:52:14.167964Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Density-of-states","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"hep-lat","authors_text":"Kurt Langfeld","submitted_at":"2016-10-31T10:36:26Z","abstract_excerpt":"Although Monte Carlo calculations using Importance Sampling have matured into the most widely employed method for determining first principle results in QCD, they spectacularly fail for theories with a sign problem or for which certain rare configurations play an important role. Non-Markovian Random walks, based upon iterative refinements of the density-of-states, overcome such overlap problems. I will review the Linear Logarithmic Relaxation (LLR) method and, in particular, focus onto ergodicity and exponential error suppression. Applications include the high-state Potts model, SU(2) and SU(3"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1610.09856","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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1610.09856","created_at":"2026-05-18T00:52:14.168039+00:00"},{"alias_kind":"arxiv_version","alias_value":"1610.09856v2","created_at":"2026-05-18T00:52:14.168039+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1610.09856","created_at":"2026-05-18T00:52:14.168039+00:00"},{"alias_kind":"pith_short_12","alias_value":"JBTG2VBWVSHJ","created_at":"2026-05-18T12:30:25.849896+00:00"},{"alias_kind":"pith_short_16","alias_value":"JBTG2VBWVSHJIVGH","created_at":"2026-05-18T12:30:25.849896+00:00"},{"alias_kind":"pith_short_8","alias_value":"JBTG2VBW","created_at":"2026-05-18T12:30:25.849896+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/JBTG2VBWVSHJIVGHKZDIHNH2JG","json":"https://pith.science/pith/JBTG2VBWVSHJIVGHKZDIHNH2JG.json","graph_json":"https://pith.science/api/pith-number/JBTG2VBWVSHJIVGHKZDIHNH2JG/graph.json","events_json":"https://pith.science/api/pith-number/JBTG2VBWVSHJIVGHKZDIHNH2JG/events.json","paper":"https://pith.science/paper/JBTG2VBW"},"agent_actions":{"view_html":"https://pith.science/pith/JBTG2VBWVSHJIVGHKZDIHNH2JG","download_json":"https://pith.science/pith/JBTG2VBWVSHJIVGHKZDIHNH2JG.json","view_paper":"https://pith.science/paper/JBTG2VBW","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1610.09856&json=true","fetch_graph":"https://pith.science/api/pith-number/JBTG2VBWVSHJIVGHKZDIHNH2JG/graph.json","fetch_events":"https://pith.science/api/pith-number/JBTG2VBWVSHJIVGHKZDIHNH2JG/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/JBTG2VBWVSHJIVGHKZDIHNH2JG/action/timestamp_anchor","attest_storage":"https://pith.science/pith/JBTG2VBWVSHJIVGHKZDIHNH2JG/action/storage_attestation","attest_author":"https://pith.science/pith/JBTG2VBWVSHJIVGHKZDIHNH2JG/action/author_attestation","sign_citation":"https://pith.science/pith/JBTG2VBWVSHJIVGHKZDIHNH2JG/action/citation_signature","submit_replication":"https://pith.science/pith/JBTG2VBWVSHJIVGHKZDIHNH2JG/action/replication_record"}},"created_at":"2026-05-18T00:52:14.168039+00:00","updated_at":"2026-05-18T00:52:14.168039+00:00"}