{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:2UL4SGFOOLPRDIJX5HVILPSOS2","short_pith_number":"pith:2UL4SGFO","schema_version":"1.0","canonical_sha256":"d517c918ae72df11a137e9ea85be4e9691214049a77e5ad2de5bfdce4ce8c860","source":{"kind":"arxiv","id":"2506.08331","version":1},"attestation_state":"computed","paper":{"title":"Correcting a noisy quantum computer using a quantum computer","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cond-mat.dis-nn","cond-mat.stat-mech"],"primary_cat":"quant-ph","authors_text":"Pan Zhang","submitted_at":"2025-06-10T01:35:21Z","abstract_excerpt":"Quantum computers require error correction to achieve universal quantum computing. However, current decoding of quantum error-correcting codes relies on classical computation, which is slower than quantum operations in superconducting qubits. This discrepancy makes the practical implementation of real-time quantum error correction challenging. In this work, we propose a decoding scheme that leverages the operations of the quantum circuit itself. Given a noisy quantum circuit $A$, we train a decoding quantum circuit $B$ using syndrome measurements to identify the logical operators needed to cor"},"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":"2506.08331","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"quant-ph","submitted_at":"2025-06-10T01:35:21Z","cross_cats_sorted":["cond-mat.dis-nn","cond-mat.stat-mech"],"title_canon_sha256":"4bc178a7055a12e6e4f0a7a3b38299743ed60fcc6a0316c15fd4a5b9a1539809","abstract_canon_sha256":"1d1b86e9177f976030a7094b0b6a3886cb2772b34ebaaf60dda52679e29a8f89"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:18:48.160580Z","signature_b64":"U6d8Nkm/Opq+H5X+IlLm1laULHsuiAhA2IIqCNHaDy9GZv0mbU7TcCNMSrw/yxU0B1Aucm6Gri4sB1ukxTuQAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d517c918ae72df11a137e9ea85be4e9691214049a77e5ad2de5bfdce4ce8c860","last_reissued_at":"2026-07-05T11:18:48.160202Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:18:48.160202Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Correcting a noisy quantum computer using a quantum computer","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cond-mat.dis-nn","cond-mat.stat-mech"],"primary_cat":"quant-ph","authors_text":"Pan Zhang","submitted_at":"2025-06-10T01:35:21Z","abstract_excerpt":"Quantum computers require error correction to achieve universal quantum computing. However, current decoding of quantum error-correcting codes relies on classical computation, which is slower than quantum operations in superconducting qubits. This discrepancy makes the practical implementation of real-time quantum error correction challenging. In this work, we propose a decoding scheme that leverages the operations of the quantum circuit itself. Given a noisy quantum circuit $A$, we train a decoding quantum circuit $B$ using syndrome measurements to identify the logical operators needed to cor"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.08331","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/2506.08331/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":"2506.08331","created_at":"2026-07-05T11:18:48.160259+00:00"},{"alias_kind":"arxiv_version","alias_value":"2506.08331v1","created_at":"2026-07-05T11:18:48.160259+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.08331","created_at":"2026-07-05T11:18:48.160259+00:00"},{"alias_kind":"pith_short_12","alias_value":"2UL4SGFOOLPR","created_at":"2026-07-05T11:18:48.160259+00:00"},{"alias_kind":"pith_short_16","alias_value":"2UL4SGFOOLPRDIJX","created_at":"2026-07-05T11:18:48.160259+00:00"},{"alias_kind":"pith_short_8","alias_value":"2UL4SGFO","created_at":"2026-07-05T11:18:48.160259+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":1,"sample":[{"citing_arxiv_id":"2508.02422","citing_title":"Superior resilience to poisoning and amenability to unlearning in quantum machine learning","ref_index":49,"is_internal_anchor":true}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/2UL4SGFOOLPRDIJX5HVILPSOS2","json":"https://pith.science/pith/2UL4SGFOOLPRDIJX5HVILPSOS2.json","graph_json":"https://pith.science/api/pith-number/2UL4SGFOOLPRDIJX5HVILPSOS2/graph.json","events_json":"https://pith.science/api/pith-number/2UL4SGFOOLPRDIJX5HVILPSOS2/events.json","paper":"https://pith.science/paper/2UL4SGFO"},"agent_actions":{"view_html":"https://pith.science/pith/2UL4SGFOOLPRDIJX5HVILPSOS2","download_json":"https://pith.science/pith/2UL4SGFOOLPRDIJX5HVILPSOS2.json","view_paper":"https://pith.science/paper/2UL4SGFO","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2506.08331&json=true","fetch_graph":"https://pith.science/api/pith-number/2UL4SGFOOLPRDIJX5HVILPSOS2/graph.json","fetch_events":"https://pith.science/api/pith-number/2UL4SGFOOLPRDIJX5HVILPSOS2/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/2UL4SGFOOLPRDIJX5HVILPSOS2/action/timestamp_anchor","attest_storage":"https://pith.science/pith/2UL4SGFOOLPRDIJX5HVILPSOS2/action/storage_attestation","attest_author":"https://pith.science/pith/2UL4SGFOOLPRDIJX5HVILPSOS2/action/author_attestation","sign_citation":"https://pith.science/pith/2UL4SGFOOLPRDIJX5HVILPSOS2/action/citation_signature","submit_replication":"https://pith.science/pith/2UL4SGFOOLPRDIJX5HVILPSOS2/action/replication_record"}},"created_at":"2026-07-05T11:18:48.160259+00:00","updated_at":"2026-07-05T11:18:48.160259+00:00"}