{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2019:WEOZDHIZWQBK45NWJNLO3DSE6X","short_pith_number":"pith:WEOZDHIZ","schema_version":"1.0","canonical_sha256":"b11d919d19b402ae75b64b56ed8e44f5eba8c3da78ad8d881bba2481c7e4ea56","source":{"kind":"arxiv","id":"1901.05408","version":1},"attestation_state":"computed","paper":{"title":"Reconstructing parton distribution functions from Ioffe time data: from Bayesian methods to Neural Networks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["hep-ph","nucl-th"],"primary_cat":"hep-lat","authors_text":"Alexander Rothkopf, Joseph Karpie, Kostas Orginos, Savvas Zafeiropoulos","submitted_at":"2019-01-16T17:46:36Z","abstract_excerpt":"The computation of the parton distribution functions (PDF) or distribution amplitudes (DA) of hadrons from first principles lattice QCD constitutes a central open problem. In this study, we present and evaluate the efficiency of a selection of methods for inverse problems to reconstruct the full $x$-dependence of PDFs. Our starting point are the so called Ioffe time PDFs, which are accessible from Euclidean time calculations in conjunction with a matching procedure. Using realistic mock data tests, we find that the ill-posed incomplete Fourier transform underlying the reconstruction requires c"},"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":"1901.05408","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"hep-lat","submitted_at":"2019-01-16T17:46:36Z","cross_cats_sorted":["hep-ph","nucl-th"],"title_canon_sha256":"5e1af45401ff84cf67a3c2a3029743133e54c047b2e7ad82799eb232a196912a","abstract_canon_sha256":"d34f11ce1172bc887e3dd6dc0d731d0a557a7c7b577e7dc3d4323ee716e06a14"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:47:26.586099Z","signature_b64":"ibv1EOUrkBAkS6kkmqcGt6Rh4eMMspL3V5cNI3apT35GRgclpnu0RGCpcHIvH/GOl2JKh2tdWlhM9CLAzOPWCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b11d919d19b402ae75b64b56ed8e44f5eba8c3da78ad8d881bba2481c7e4ea56","last_reissued_at":"2026-05-17T23:47:26.585608Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:47:26.585608Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Reconstructing parton distribution functions from Ioffe time data: from Bayesian methods to Neural Networks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["hep-ph","nucl-th"],"primary_cat":"hep-lat","authors_text":"Alexander Rothkopf, Joseph Karpie, Kostas Orginos, Savvas Zafeiropoulos","submitted_at":"2019-01-16T17:46:36Z","abstract_excerpt":"The computation of the parton distribution functions (PDF) or distribution amplitudes (DA) of hadrons from first principles lattice QCD constitutes a central open problem. In this study, we present and evaluate the efficiency of a selection of methods for inverse problems to reconstruct the full $x$-dependence of PDFs. Our starting point are the so called Ioffe time PDFs, which are accessible from Euclidean time calculations in conjunction with a matching procedure. Using realistic mock data tests, we find that the ill-posed incomplete Fourier transform underlying the reconstruction requires c"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1901.05408","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":"1901.05408","created_at":"2026-05-17T23:47:26.585685+00:00"},{"alias_kind":"arxiv_version","alias_value":"1901.05408v1","created_at":"2026-05-17T23:47:26.585685+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1901.05408","created_at":"2026-05-17T23:47:26.585685+00:00"},{"alias_kind":"pith_short_12","alias_value":"WEOZDHIZWQBK","created_at":"2026-05-18T12:33:30.264802+00:00"},{"alias_kind":"pith_short_16","alias_value":"WEOZDHIZWQBK45NW","created_at":"2026-05-18T12:33:30.264802+00:00"},{"alias_kind":"pith_short_8","alias_value":"WEOZDHIZ","created_at":"2026-05-18T12:33:30.264802+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":3,"internal_anchor_count":2,"sample":[{"citing_arxiv_id":"2504.17706","citing_title":"Inverse problem in the LaMET framework","ref_index":30,"is_internal_anchor":true},{"citing_arxiv_id":"2512.06121","citing_title":"Pion and Kaon PDFs from Lattice QCD via Large Momentum Effective Theory and Short-Distance Factorization","ref_index":62,"is_internal_anchor":true},{"citing_arxiv_id":"2604.21476","citing_title":"Reconstructing the full kinematic dependence of GPDs from pseudo-distributions","ref_index":46,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/WEOZDHIZWQBK45NWJNLO3DSE6X","json":"https://pith.science/pith/WEOZDHIZWQBK45NWJNLO3DSE6X.json","graph_json":"https://pith.science/api/pith-number/WEOZDHIZWQBK45NWJNLO3DSE6X/graph.json","events_json":"https://pith.science/api/pith-number/WEOZDHIZWQBK45NWJNLO3DSE6X/events.json","paper":"https://pith.science/paper/WEOZDHIZ"},"agent_actions":{"view_html":"https://pith.science/pith/WEOZDHIZWQBK45NWJNLO3DSE6X","download_json":"https://pith.science/pith/WEOZDHIZWQBK45NWJNLO3DSE6X.json","view_paper":"https://pith.science/paper/WEOZDHIZ","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1901.05408&json=true","fetch_graph":"https://pith.science/api/pith-number/WEOZDHIZWQBK45NWJNLO3DSE6X/graph.json","fetch_events":"https://pith.science/api/pith-number/WEOZDHIZWQBK45NWJNLO3DSE6X/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/WEOZDHIZWQBK45NWJNLO3DSE6X/action/timestamp_anchor","attest_storage":"https://pith.science/pith/WEOZDHIZWQBK45NWJNLO3DSE6X/action/storage_attestation","attest_author":"https://pith.science/pith/WEOZDHIZWQBK45NWJNLO3DSE6X/action/author_attestation","sign_citation":"https://pith.science/pith/WEOZDHIZWQBK45NWJNLO3DSE6X/action/citation_signature","submit_replication":"https://pith.science/pith/WEOZDHIZWQBK45NWJNLO3DSE6X/action/replication_record"}},"created_at":"2026-05-17T23:47:26.585685+00:00","updated_at":"2026-05-17T23:47:26.585685+00:00"}