{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:IHAF3WVSGDMUHEB6W7Y5GRQHZB","short_pith_number":"pith:IHAF3WVS","schema_version":"1.0","canonical_sha256":"41c05ddab230d943903eb7f1d34607c86e2c6e8c8b685079c03033e0da5fe9df","source":{"kind":"arxiv","id":"2606.05066","version":1},"attestation_state":"computed","paper":{"title":"Fermionic non-Gaussianity via Bell sampling: monotones and efficient quantum algorithms","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"quant-ph","authors_text":"Poetri Sonya Tarabunga","submitted_at":"2026-06-03T16:29:05Z","abstract_excerpt":"Fermionic non-Gaussianity is an essential resource for unlocking the full computational power of fermionic quantum platforms. In this work we develop monotones and efficient quantum algorithms for fermionic non-Gaussianity, all built on the eigenvalue structure of the operator $\\Lambda = \\sum_{j=1}^{2n}\\gamma_j\\otimes\\gamma_j$ defined on two copies of an $n$-mode fermionic state, accessible via Bell sampling. In particular, we introduce the \\emph{bridge degree} of even pure states, a novel non-Gaussianity monotone defined as the largest eigenvalue sector of $\\Lambda$ populated by two copies of"},"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":"2606.05066","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"quant-ph","submitted_at":"2026-06-03T16:29:05Z","cross_cats_sorted":[],"title_canon_sha256":"6f9fd709a1f8de1a81e678c836dd652e16f4279c1afd8c7ca3a8f86b12e1ead6","abstract_canon_sha256":"4c4cd42d0f46d753466fa83b7bce4b76f7acaef719625519436c6ae6abd492f5"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-04T01:10:04.874272Z","signature_b64":"3/MuhxtQPTYYh3Zs1P/ZDgC1MTT3FlRxXa7YVPg3NUp9aBD6Xh9tbVAJ0zLZqeSldybQlx4tNJW0K5Rdh/5qBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"41c05ddab230d943903eb7f1d34607c86e2c6e8c8b685079c03033e0da5fe9df","last_reissued_at":"2026-06-04T01:10:04.873848Z","signature_status":"signed_v1","first_computed_at":"2026-06-04T01:10:04.873848Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Fermionic non-Gaussianity via Bell sampling: monotones and efficient quantum algorithms","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"quant-ph","authors_text":"Poetri Sonya Tarabunga","submitted_at":"2026-06-03T16:29:05Z","abstract_excerpt":"Fermionic non-Gaussianity is an essential resource for unlocking the full computational power of fermionic quantum platforms. In this work we develop monotones and efficient quantum algorithms for fermionic non-Gaussianity, all built on the eigenvalue structure of the operator $\\Lambda = \\sum_{j=1}^{2n}\\gamma_j\\otimes\\gamma_j$ defined on two copies of an $n$-mode fermionic state, accessible via Bell sampling. In particular, we introduce the \\emph{bridge degree} of even pure states, a novel non-Gaussianity monotone defined as the largest eigenvalue sector of $\\Lambda$ populated by two copies of"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.05066","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/2606.05066/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":"2606.05066","created_at":"2026-06-04T01:10:04.873911+00:00"},{"alias_kind":"arxiv_version","alias_value":"2606.05066v1","created_at":"2026-06-04T01:10:04.873911+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.05066","created_at":"2026-06-04T01:10:04.873911+00:00"},{"alias_kind":"pith_short_12","alias_value":"IHAF3WVSGDMU","created_at":"2026-06-04T01:10:04.873911+00:00"},{"alias_kind":"pith_short_16","alias_value":"IHAF3WVSGDMUHEB6","created_at":"2026-06-04T01:10:04.873911+00:00"},{"alias_kind":"pith_short_8","alias_value":"IHAF3WVS","created_at":"2026-06-04T01:10:04.873911+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/IHAF3WVSGDMUHEB6W7Y5GRQHZB","json":"https://pith.science/pith/IHAF3WVSGDMUHEB6W7Y5GRQHZB.json","graph_json":"https://pith.science/api/pith-number/IHAF3WVSGDMUHEB6W7Y5GRQHZB/graph.json","events_json":"https://pith.science/api/pith-number/IHAF3WVSGDMUHEB6W7Y5GRQHZB/events.json","paper":"https://pith.science/paper/IHAF3WVS"},"agent_actions":{"view_html":"https://pith.science/pith/IHAF3WVSGDMUHEB6W7Y5GRQHZB","download_json":"https://pith.science/pith/IHAF3WVSGDMUHEB6W7Y5GRQHZB.json","view_paper":"https://pith.science/paper/IHAF3WVS","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2606.05066&json=true","fetch_graph":"https://pith.science/api/pith-number/IHAF3WVSGDMUHEB6W7Y5GRQHZB/graph.json","fetch_events":"https://pith.science/api/pith-number/IHAF3WVSGDMUHEB6W7Y5GRQHZB/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/IHAF3WVSGDMUHEB6W7Y5GRQHZB/action/timestamp_anchor","attest_storage":"https://pith.science/pith/IHAF3WVSGDMUHEB6W7Y5GRQHZB/action/storage_attestation","attest_author":"https://pith.science/pith/IHAF3WVSGDMUHEB6W7Y5GRQHZB/action/author_attestation","sign_citation":"https://pith.science/pith/IHAF3WVSGDMUHEB6W7Y5GRQHZB/action/citation_signature","submit_replication":"https://pith.science/pith/IHAF3WVSGDMUHEB6W7Y5GRQHZB/action/replication_record"}},"created_at":"2026-06-04T01:10:04.873911+00:00","updated_at":"2026-06-04T01:10:04.873911+00:00"}