{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:5JDFCGNLAW6HTXH7OLZCWTQXYF","short_pith_number":"pith:5JDFCGNL","schema_version":"1.0","canonical_sha256":"ea465119ab05bc79dcff72f22b4e17c15d61189811c764fa96719a410e937e10","source":{"kind":"arxiv","id":"2408.11766","version":1},"attestation_state":"computed","paper":{"title":"Model-free spectral reconstruction via Lagrange duality","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["quant-ph"],"primary_cat":"hep-lat","authors_text":"Scott Lawrence","submitted_at":"2024-08-21T16:39:37Z","abstract_excerpt":"Various physical quantities -- including real-time response, inclusive cross-sections, and decay rates -- may not be directly determined from Euclidean correlators. They are, however, easily determined from the spectral density, motivating the task of estimating a spectral density from a Euclidean correlator. This spectral reconstruction problem can be written as an ill-posed inverse Laplace transform; incorporating positivity constraints allows one to obtain finite-sized bounds on the region of spectral density functions consistent with the Euclidean data. Expressing the reconstruction proble"},"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":"2408.11766","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"hep-lat","submitted_at":"2024-08-21T16:39:37Z","cross_cats_sorted":["quant-ph"],"title_canon_sha256":"60bec9e8ea1c693674c93482ba6aed561a18fb861f37dfe3f90cbbe1570488b7","abstract_canon_sha256":"84945c6d825ab33fbc3094b54fc0d3f8a6edd8cc010c2f6e222890165c53fa54"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:57:48.813521Z","signature_b64":"8xBzkiPTYoVplia2USM7S3otOl3xrTmw+2tREotOOAbCsxuP8o4fOUfMxacbvabgKrqHFWVkHY5ymZqB2AD5Bw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ea465119ab05bc79dcff72f22b4e17c15d61189811c764fa96719a410e937e10","last_reissued_at":"2026-07-05T08:57:48.813027Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:57:48.813027Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Model-free spectral reconstruction via Lagrange duality","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["quant-ph"],"primary_cat":"hep-lat","authors_text":"Scott Lawrence","submitted_at":"2024-08-21T16:39:37Z","abstract_excerpt":"Various physical quantities -- including real-time response, inclusive cross-sections, and decay rates -- may not be directly determined from Euclidean correlators. They are, however, easily determined from the spectral density, motivating the task of estimating a spectral density from a Euclidean correlator. This spectral reconstruction problem can be written as an ill-posed inverse Laplace transform; incorporating positivity constraints allows one to obtain finite-sized bounds on the region of spectral density functions consistent with the Euclidean data. Expressing the reconstruction proble"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2408.11766","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2408.11766/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"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":"2408.11766","created_at":"2026-07-05T08:57:48.813076+00:00"},{"alias_kind":"arxiv_version","alias_value":"2408.11766v1","created_at":"2026-07-05T08:57:48.813076+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2408.11766","created_at":"2026-07-05T08:57:48.813076+00:00"},{"alias_kind":"pith_short_12","alias_value":"5JDFCGNLAW6H","created_at":"2026-07-05T08:57:48.813076+00:00"},{"alias_kind":"pith_short_16","alias_value":"5JDFCGNLAW6HTXH7","created_at":"2026-07-05T08:57:48.813076+00:00"},{"alias_kind":"pith_short_8","alias_value":"5JDFCGNL","created_at":"2026-07-05T08:57:48.813076+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":6,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2606.19503","citing_title":"Kernel transformations and bounds for smeared spectral functions","ref_index":36,"is_internal_anchor":false},{"citing_arxiv_id":"2606.09791","citing_title":"Certified spectral functions from lattice Monte Carlo data","ref_index":22,"is_internal_anchor":false},{"citing_arxiv_id":"2606.28167","citing_title":"Spectral densities from Euclidean correlators via integral transforms: theoretical framework","ref_index":26,"is_internal_anchor":false},{"citing_arxiv_id":"2605.20509","citing_title":"The Causal Bootstrap: Bounding Smeared Spectral Functions from Non-Perturbative Euclidean Data","ref_index":31,"is_internal_anchor":false},{"citing_arxiv_id":"2601.21155","citing_title":"Nucleon axial-vector form factor and radius from radiatively-corrected antineutrino scattering data","ref_index":109,"is_internal_anchor":false},{"citing_arxiv_id":"2604.10284","citing_title":"Some progress on the use of the variational method in quantum field theory","ref_index":101,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/5JDFCGNLAW6HTXH7OLZCWTQXYF","json":"https://pith.science/pith/5JDFCGNLAW6HTXH7OLZCWTQXYF.json","graph_json":"https://pith.science/api/pith-number/5JDFCGNLAW6HTXH7OLZCWTQXYF/graph.json","events_json":"https://pith.science/api/pith-number/5JDFCGNLAW6HTXH7OLZCWTQXYF/events.json","paper":"https://pith.science/paper/5JDFCGNL"},"agent_actions":{"view_html":"https://pith.science/pith/5JDFCGNLAW6HTXH7OLZCWTQXYF","download_json":"https://pith.science/pith/5JDFCGNLAW6HTXH7OLZCWTQXYF.json","view_paper":"https://pith.science/paper/5JDFCGNL","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2408.11766&json=true","fetch_graph":"https://pith.science/api/pith-number/5JDFCGNLAW6HTXH7OLZCWTQXYF/graph.json","fetch_events":"https://pith.science/api/pith-number/5JDFCGNLAW6HTXH7OLZCWTQXYF/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/5JDFCGNLAW6HTXH7OLZCWTQXYF/action/timestamp_anchor","attest_storage":"https://pith.science/pith/5JDFCGNLAW6HTXH7OLZCWTQXYF/action/storage_attestation","attest_author":"https://pith.science/pith/5JDFCGNLAW6HTXH7OLZCWTQXYF/action/author_attestation","sign_citation":"https://pith.science/pith/5JDFCGNLAW6HTXH7OLZCWTQXYF/action/citation_signature","submit_replication":"https://pith.science/pith/5JDFCGNLAW6HTXH7OLZCWTQXYF/action/replication_record"}},"created_at":"2026-07-05T08:57:48.813076+00:00","updated_at":"2026-07-05T08:57:48.813076+00:00"}