{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:NB5QRJHQ7AOLFKG54WF5W5EQS6","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"f7c19656a87200defa666c34241e847705cac12a67f7ee475e22a41a79201e41","cross_cats_sorted":["cs.IT","cs.LG","math.IT"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"quant-ph","submitted_at":"2022-04-28T17:56:44Z","title_canon_sha256":"baf42896e50180688005f31037a39140712099fa000b77fca2c968e39501f876"},"schema_version":"1.0","source":{"id":"2204.13691","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2204.13691","created_at":"2026-07-05T04:18:44Z"},{"alias_kind":"arxiv_version","alias_value":"2204.13691v1","created_at":"2026-07-05T04:18:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2204.13691","created_at":"2026-07-05T04:18:44Z"},{"alias_kind":"pith_short_12","alias_value":"NB5QRJHQ7AOL","created_at":"2026-07-05T04:18:44Z"},{"alias_kind":"pith_short_16","alias_value":"NB5QRJHQ7AOLFKG5","created_at":"2026-07-05T04:18:44Z"},{"alias_kind":"pith_short_8","alias_value":"NB5QRJHQ","created_at":"2026-07-05T04:18:44Z"}],"graph_snapshots":[{"event_id":"sha256:5a60e84b925c39dbb4c132771380ece7d9d8630d679e837e0fd7897f52efced0","target":"graph","created_at":"2026-07-05T04:18:44Z","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/2204.13691/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Understanding what can be learned from experiments is central to scientific progress. In this work, we use a learning-theoretic perspective to study the task of learning physical operations in a quantum machine when all operations (state preparation, dynamics, and measurement) are a priori unknown. We prove that, without any prior knowledge, if one can explore the full quantum state space by composing the operations, then every operation can be learned. When one cannot explore the full state space but all operations are approximately known and noise in Clifford gates is gate-independent, we fi","authors_text":"Hsin-Yuan Huang, John Preskill, Steven T. Flammia","cross_cats":["cs.IT","cs.LG","math.IT"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"quant-ph","submitted_at":"2022-04-28T17:56:44Z","title":"Foundations for learning from noisy quantum experiments"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2204.13691","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:dd551f4b1b0fef4e24fb30df57adffe708b4653a7b239b3d5a16578e785067d0","target":"record","created_at":"2026-07-05T04:18:44Z","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":"f7c19656a87200defa666c34241e847705cac12a67f7ee475e22a41a79201e41","cross_cats_sorted":["cs.IT","cs.LG","math.IT"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"quant-ph","submitted_at":"2022-04-28T17:56:44Z","title_canon_sha256":"baf42896e50180688005f31037a39140712099fa000b77fca2c968e39501f876"},"schema_version":"1.0","source":{"id":"2204.13691","kind":"arxiv","version":1}},"canonical_sha256":"687b08a4f0f81cb2a8dde58bdb749097a1525786e1c033fcdcfc288c3bf34025","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"687b08a4f0f81cb2a8dde58bdb749097a1525786e1c033fcdcfc288c3bf34025","first_computed_at":"2026-07-05T04:18:44.661505Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:18:44.661505Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"SWyY87JGdfJgSJJHIXw+hBVW4bT8eEzy1nmf0oN7j1mb8fgvK0ch08B4LfXK4GxiXi03Bx+SRKb7YY6am0NKBw==","signature_status":"signed_v1","signed_at":"2026-07-05T04:18:44.662131Z","signed_message":"canonical_sha256_bytes"},"source_id":"2204.13691","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:dd551f4b1b0fef4e24fb30df57adffe708b4653a7b239b3d5a16578e785067d0","sha256:5a60e84b925c39dbb4c132771380ece7d9d8630d679e837e0fd7897f52efced0"],"state_sha256":"45b6a65311de61ab3a6795cb4470583745891795203e97c94ab790815f897879"}