{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:NCCD67ENK3WDOPPSJA7XWNMJXS","short_pith_number":"pith:NCCD67EN","canonical_record":{"source":{"id":"2606.28483","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"quant-ph","submitted_at":"2026-06-26T18:00:00Z","cross_cats_sorted":[],"title_canon_sha256":"a14758d20c1d41207d668ac02937d3820331f8f0b13c12b34b92d83796aa579a","abstract_canon_sha256":"0a0b7b40c8e9d04c101d2c0a3194cdad11968c497c3bdfa783f3f088a928b279"},"schema_version":"1.0"},"canonical_sha256":"68843f7c8d56ec373df2483f7b3589bca6901c2aabe790b584bcf987f26ba7cb","source":{"kind":"arxiv","id":"2606.28483","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.28483","created_at":"2026-06-30T00:15:15Z"},{"alias_kind":"arxiv_version","alias_value":"2606.28483v1","created_at":"2026-06-30T00:15:15Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.28483","created_at":"2026-06-30T00:15:15Z"},{"alias_kind":"pith_short_12","alias_value":"NCCD67ENK3WD","created_at":"2026-06-30T00:15:15Z"},{"alias_kind":"pith_short_16","alias_value":"NCCD67ENK3WDOPPS","created_at":"2026-06-30T00:15:15Z"},{"alias_kind":"pith_short_8","alias_value":"NCCD67EN","created_at":"2026-06-30T00:15:15Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:NCCD67ENK3WDOPPSJA7XWNMJXS","target":"record","payload":{"canonical_record":{"source":{"id":"2606.28483","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"quant-ph","submitted_at":"2026-06-26T18:00:00Z","cross_cats_sorted":[],"title_canon_sha256":"a14758d20c1d41207d668ac02937d3820331f8f0b13c12b34b92d83796aa579a","abstract_canon_sha256":"0a0b7b40c8e9d04c101d2c0a3194cdad11968c497c3bdfa783f3f088a928b279"},"schema_version":"1.0"},"canonical_sha256":"68843f7c8d56ec373df2483f7b3589bca6901c2aabe790b584bcf987f26ba7cb","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-30T00:15:15.554948Z","signature_b64":"8AwZo35TinCabDgEeJ6LBzFyoddYhl6QeRAxsVUzDk9yk9fQoPzWBCK920Ug14HiTSYWHlJZdbvKwMi9rW3mBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"68843f7c8d56ec373df2483f7b3589bca6901c2aabe790b584bcf987f26ba7cb","last_reissued_at":"2026-06-30T00:15:15.554525Z","signature_status":"signed_v1","first_computed_at":"2026-06-30T00:15:15.554525Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2606.28483","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-06-30T00:15:15Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"gnH6F3DI+cgUohGoALFNlqFlbD4+Sa41WyYRXwe/ngkbZGvgnwpybg79tYfje3Wfhzk5gXEp10MhMV/5h6FGDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-17T03:46:06.765021Z"},"content_sha256":"080ed7c8172e71f6591bbd938fd55407e6e09302d60c05d4f01c32040cf777aa","schema_version":"1.0","event_id":"sha256:080ed7c8172e71f6591bbd938fd55407e6e09302d60c05d4f01c32040cf777aa"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:NCCD67ENK3WDOPPSJA7XWNMJXS","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Quantum Fourier Generative Models Trainable at Large Scale","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"quant-ph","authors_text":"Cenk T\\\"uys\\\"uz, Michele Grossi, Oleksandr Kyriienko","submitted_at":"2026-06-26T18:00:00Z","abstract_excerpt":"We propose an algorithmic framework for building and training quantum generative models corresponding to multivariate probability distributions. Our model uses parallel Fourier feature maps for embedding continuous-valued variables combined with a forrelation-type quantum circuit for tuning Fourier coefficients of the quantum model. Crucially, we develop a distinct training strategy where training is enabled at large scale by log-likelihood loss with unbiased Monte Carlo estimator based on Parseval's identity. Unlike prior work that relied on maximal mean discrepancy (MMD) loss, our approach g"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.28483","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/2606.28483/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-06-30T00:15:15Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"DmR3zXyWVh/ksn9jcwnF/EJu2QwwHkPqL8548ATqSNlbbTen1BpgwY+hvCedbdgB3OChKrN7vouM0l0JF+CpCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-17T03:46:06.765682Z"},"content_sha256":"ccd878af8595f9928784d2dc9079810989f7686cae27904aeb85b4d02804785b","schema_version":"1.0","event_id":"sha256:ccd878af8595f9928784d2dc9079810989f7686cae27904aeb85b4d02804785b"},{"event_type":"integrity_finding","subject_pith_number":"pith:2026:NCCD67ENK3WDOPPSJA7XWNMJXS","target":"integrity","payload":{"note":"DOI in the printed bibliography is fragmented by whitespace or line breaks. A longer candidate (10.6084/m9.figshare.32789952(2026) was visible in the surrounding text but could not be confirmed against doi.org as printed.","snippet":"C. T¨ uys¨ uzet al.,https://doi.org/10.6084/m9. figshare.32789952(2026), Public dataset repository","arxiv_id":"2606.28483","detector":"doi_compliance","evidence":{"ref_index":55,"verdict_class":"incontrovertible","resolved_title":null,"printed_excerpt":"C. T¨ uys¨ uzet al.,https://doi.org/10.6084/m9. figshare.32789952(2026), Public dataset repository","reconstructed_doi":"10.6084/m9.figshare.32789952(2026"},"severity":"advisory","ref_index":55,"audited_at":"2026-07-09T13:37:05.439425Z","event_type":"pith.integrity.v1","detected_doi":"10.6084/m9.figshare.32789952(2026","detector_url":"https://pith.science/pith-integrity-protocol#doi_compliance","external_url":null,"finding_type":"recoverable_identifier","evidence_hash":"09191fa6f6dbf4fb7195bb45e7820f81ceef681756977dc72d480af9f1df7cc4","paper_version":1,"verdict_class":"incontrovertible","resolved_title":null,"detector_version":"1.0.0","detected_arxiv_id":null,"integrity_event_id":9059,"payload_sha256":"720e8c575afeb2923da2bd71c571319f35e42ed963cf84ed3c8707443867e849","signature_b64":"1aBgTqXLN/zJqQbL+QBdRrm3g7vY2L/6aKHGtk3MgYQqJAtSxlI0dnJpOSjkvULXbXNOSgJ0mETqydPMab5jBg==","signing_key_id":"pith-v1-2026-05"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-09T13:37:46Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"6CmNjoPPuihadfcYlouCx5jgtZ2AByH6iz2R/wR91SFp72zIdmIGDeHFUKg/VdvsdNYF5LqZR4aE81S+LQoLAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-17T03:46:06.770087Z"},"content_sha256":"24fd9eb415a0367689a20abf976be3f41179aa89e2917d1bf55588011f3907c1","schema_version":"1.0","event_id":"sha256:24fd9eb415a0367689a20abf976be3f41179aa89e2917d1bf55588011f3907c1"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/NCCD67ENK3WDOPPSJA7XWNMJXS/bundle.json","state_url":"https://pith.science/pith/NCCD67ENK3WDOPPSJA7XWNMJXS/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/NCCD67ENK3WDOPPSJA7XWNMJXS/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-17T03:46:06Z","links":{"resolver":"https://pith.science/pith/NCCD67ENK3WDOPPSJA7XWNMJXS","bundle":"https://pith.science/pith/NCCD67ENK3WDOPPSJA7XWNMJXS/bundle.json","state":"https://pith.science/pith/NCCD67ENK3WDOPPSJA7XWNMJXS/state.json","well_known_bundle":"https://pith.science/.well-known/pith/NCCD67ENK3WDOPPSJA7XWNMJXS/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:NCCD67ENK3WDOPPSJA7XWNMJXS","merge_version":"pith-open-graph-merge-v1","event_count":3,"valid_event_count":3,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"0a0b7b40c8e9d04c101d2c0a3194cdad11968c497c3bdfa783f3f088a928b279","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"quant-ph","submitted_at":"2026-06-26T18:00:00Z","title_canon_sha256":"a14758d20c1d41207d668ac02937d3820331f8f0b13c12b34b92d83796aa579a"},"schema_version":"1.0","source":{"id":"2606.28483","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.28483","created_at":"2026-06-30T00:15:15Z"},{"alias_kind":"arxiv_version","alias_value":"2606.28483v1","created_at":"2026-06-30T00:15:15Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.28483","created_at":"2026-06-30T00:15:15Z"},{"alias_kind":"pith_short_12","alias_value":"NCCD67ENK3WD","created_at":"2026-06-30T00:15:15Z"},{"alias_kind":"pith_short_16","alias_value":"NCCD67ENK3WDOPPS","created_at":"2026-06-30T00:15:15Z"},{"alias_kind":"pith_short_8","alias_value":"NCCD67EN","created_at":"2026-06-30T00:15:15Z"}],"graph_snapshots":[{"event_id":"sha256:ccd878af8595f9928784d2dc9079810989f7686cae27904aeb85b4d02804785b","target":"graph","created_at":"2026-06-30T00:15:15Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2606.28483/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We propose an algorithmic framework for building and training quantum generative models corresponding to multivariate probability distributions. Our model uses parallel Fourier feature maps for embedding continuous-valued variables combined with a forrelation-type quantum circuit for tuning Fourier coefficients of the quantum model. Crucially, we develop a distinct training strategy where training is enabled at large scale by log-likelihood loss with unbiased Monte Carlo estimator based on Parseval's identity. Unlike prior work that relied on maximal mean discrepancy (MMD) loss, our approach g","authors_text":"Cenk T\\\"uys\\\"uz, Michele Grossi, Oleksandr Kyriienko","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"quant-ph","submitted_at":"2026-06-26T18:00:00Z","title":"Quantum Fourier Generative Models Trainable at Large Scale"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.28483","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:080ed7c8172e71f6591bbd938fd55407e6e09302d60c05d4f01c32040cf777aa","target":"record","created_at":"2026-06-30T00:15:15Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"0a0b7b40c8e9d04c101d2c0a3194cdad11968c497c3bdfa783f3f088a928b279","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"quant-ph","submitted_at":"2026-06-26T18:00:00Z","title_canon_sha256":"a14758d20c1d41207d668ac02937d3820331f8f0b13c12b34b92d83796aa579a"},"schema_version":"1.0","source":{"id":"2606.28483","kind":"arxiv","version":1}},"canonical_sha256":"68843f7c8d56ec373df2483f7b3589bca6901c2aabe790b584bcf987f26ba7cb","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"68843f7c8d56ec373df2483f7b3589bca6901c2aabe790b584bcf987f26ba7cb","first_computed_at":"2026-06-30T00:15:15.554525Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-30T00:15:15.554525Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"8AwZo35TinCabDgEeJ6LBzFyoddYhl6QeRAxsVUzDk9yk9fQoPzWBCK920Ug14HiTSYWHlJZdbvKwMi9rW3mBg==","signature_status":"signed_v1","signed_at":"2026-06-30T00:15:15.554948Z","signed_message":"canonical_sha256_bytes"},"source_id":"2606.28483","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:080ed7c8172e71f6591bbd938fd55407e6e09302d60c05d4f01c32040cf777aa","sha256:ccd878af8595f9928784d2dc9079810989f7686cae27904aeb85b4d02804785b","sha256:24fd9eb415a0367689a20abf976be3f41179aa89e2917d1bf55588011f3907c1"],"state_sha256":"927f8d0bfe3199f3857d4c728de96dd4228a592d1477dd5c262c03d7f9d5ab79"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"AkkQCYDM+oGdXFYwP/2JHGwiZuOuQF7g9zfMM/2pJUdMlvP/b8F/zJUEnETPSWHizP0Ozosg71Ak6ypVftYYCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-17T03:46:06.772384Z","bundle_sha256":"05bd9755d30e1fee6128900b4c15471f216ccee47bd1f2c103400d77e3042f5f"}}