{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:XNHOB7CXKDZ6UOVYRCFWKR3JAJ","short_pith_number":"pith:XNHOB7CX","schema_version":"1.0","canonical_sha256":"bb4ee0fc5750f3ea3ab8888b654769026d1e73e88cbccf951cf2285444fc8b0a","source":{"kind":"arxiv","id":"2602.21253","version":2},"attestation_state":"computed","paper":{"title":"A Physics-Informed Neuro-Fuzzy Framework for Quantum Error Attribution","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.SE"],"primary_cat":"quant-ph","authors_text":"Marwa R. Hassan, Naima Kaabouch","submitted_at":"2026-02-22T16:19:51Z","abstract_excerpt":"As quantum processors scale beyond 100 qubits, distinguishing software bugs from stochastic hardware noise becomes a critical diagnostic challenge. We present a neuro-fuzzy framework that addresses this attribution problem by combining Adaptive Neuro-Fuzzy Inference Systems (ANFIS) with physics-grounded feature engineering. We introduce the Bhattacharyya Veto, a hard physical constraint grounded in the Data Processing Inequality that prevents the classifier from attributing topologically impossible output distributions to noise. Validated on IBM's 156-qubit Heron r2 processor (ibm_fez) across "},"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":"2602.21253","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"quant-ph","submitted_at":"2026-02-22T16:19:51Z","cross_cats_sorted":["cs.SE"],"title_canon_sha256":"37fc9be08714de0258cdecd51ab6af1a2cb008aa6399d06ad30ad43ab922f589","abstract_canon_sha256":"69b0740a653bb11d2b776eaf73223a67c7fb213c9a08239044382f72476e6584"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-26T01:02:32.450869Z","signature_b64":"r7KHNWEBFV4FPIENMXyxS3isjI5cpZwsXxe9b1Z1k6hw7ifsR6pkfShQrTXEOAPgTMA7mshzHk43d1pv7aF+DA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"bb4ee0fc5750f3ea3ab8888b654769026d1e73e88cbccf951cf2285444fc8b0a","last_reissued_at":"2026-05-26T01:02:32.450075Z","signature_status":"signed_v1","first_computed_at":"2026-05-26T01:02:32.450075Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"A Physics-Informed Neuro-Fuzzy Framework for Quantum Error Attribution","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.SE"],"primary_cat":"quant-ph","authors_text":"Marwa R. Hassan, Naima Kaabouch","submitted_at":"2026-02-22T16:19:51Z","abstract_excerpt":"As quantum processors scale beyond 100 qubits, distinguishing software bugs from stochastic hardware noise becomes a critical diagnostic challenge. We present a neuro-fuzzy framework that addresses this attribution problem by combining Adaptive Neuro-Fuzzy Inference Systems (ANFIS) with physics-grounded feature engineering. We introduce the Bhattacharyya Veto, a hard physical constraint grounded in the Data Processing Inequality that prevents the classifier from attributing topologically impossible output distributions to noise. Validated on IBM's 156-qubit Heron r2 processor (ibm_fez) across "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2602.21253","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2602.21253/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":"2602.21253","created_at":"2026-05-26T01:02:32.450194+00:00"},{"alias_kind":"arxiv_version","alias_value":"2602.21253v2","created_at":"2026-05-26T01:02:32.450194+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2602.21253","created_at":"2026-05-26T01:02:32.450194+00:00"},{"alias_kind":"pith_short_12","alias_value":"XNHOB7CXKDZ6","created_at":"2026-05-26T01:02:32.450194+00:00"},{"alias_kind":"pith_short_16","alias_value":"XNHOB7CXKDZ6UOVY","created_at":"2026-05-26T01:02:32.450194+00:00"},{"alias_kind":"pith_short_8","alias_value":"XNHOB7CX","created_at":"2026-05-26T01:02:32.450194+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/XNHOB7CXKDZ6UOVYRCFWKR3JAJ","json":"https://pith.science/pith/XNHOB7CXKDZ6UOVYRCFWKR3JAJ.json","graph_json":"https://pith.science/api/pith-number/XNHOB7CXKDZ6UOVYRCFWKR3JAJ/graph.json","events_json":"https://pith.science/api/pith-number/XNHOB7CXKDZ6UOVYRCFWKR3JAJ/events.json","paper":"https://pith.science/paper/XNHOB7CX"},"agent_actions":{"view_html":"https://pith.science/pith/XNHOB7CXKDZ6UOVYRCFWKR3JAJ","download_json":"https://pith.science/pith/XNHOB7CXKDZ6UOVYRCFWKR3JAJ.json","view_paper":"https://pith.science/paper/XNHOB7CX","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2602.21253&json=true","fetch_graph":"https://pith.science/api/pith-number/XNHOB7CXKDZ6UOVYRCFWKR3JAJ/graph.json","fetch_events":"https://pith.science/api/pith-number/XNHOB7CXKDZ6UOVYRCFWKR3JAJ/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/XNHOB7CXKDZ6UOVYRCFWKR3JAJ/action/timestamp_anchor","attest_storage":"https://pith.science/pith/XNHOB7CXKDZ6UOVYRCFWKR3JAJ/action/storage_attestation","attest_author":"https://pith.science/pith/XNHOB7CXKDZ6UOVYRCFWKR3JAJ/action/author_attestation","sign_citation":"https://pith.science/pith/XNHOB7CXKDZ6UOVYRCFWKR3JAJ/action/citation_signature","submit_replication":"https://pith.science/pith/XNHOB7CXKDZ6UOVYRCFWKR3JAJ/action/replication_record"}},"created_at":"2026-05-26T01:02:32.450194+00:00","updated_at":"2026-05-26T01:02:32.450194+00:00"}