{"as_of":"2026-08-15T09:12:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:e1bee4642ae0518f68681a4eee75a564e8e21e3185369a53530b96002ab2d0cd","coverage":[{"denominator":113,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":100,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-14T10:13:15.663173Z","state":"measured"},{"denominator":100,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":100,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-15T06:32:42.880941+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/1908.11762/citation-record","integrity":"/paper/1908.11762/integrity","json":"/paper/1908.11762/citation-record.json","paper":"/paper/1908.11762"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:13:15.218142Z","title":"Are the gate errors coherent or stochastic?","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.218142Z"},"links":{"citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:12f2e42a592b42c9586a1249f33c87e4ae47c97f42d264193e4202dda2b7b25c","observation_id":"8eb09f80-413f-4395-9c30-f56ce8d88555","resolution":{"observed_at":"2026-08-14T10:13:15.218142Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:13:15.223268Z","title":"coherent vs. stochastic","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.223268Z"},"links":{"citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:8d0f1094e92149f3b72d0f1d6c6c461b5947704e90bd4e5d367aff17e15a534e","observation_id":"9a8358cb-edff-4e07-9ad7-304081486594","resolution":{"observed_at":"2026-08-14T10:13:15.223268Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:13:15.194792Z","title":"The em- bedding is described by a feature map, φ, mapping each QCVV data setD to a feature vector f (i.e.,φ :D→ f∈ F)","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.194792Z"},"links":{"citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:bdf6719172c733e030ad2a65b2ddf90803c535fa6dcbb79d0c931ca50ac2fe5a","observation_id":"d5debbaa-af16-47f7-b6e6-57560d7cf8c1","resolution":{"observed_at":"2026-08-14T10:13:15.194792Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:13:15.199553Z","title":"For example, properties that are categorical would re- quire classification algorithms, whereas properties that are continuous would require regression algorithms","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.199553Z"},"links":{"citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:7632e063ca78dd8864c01756c36eff08a707d63a74f68095066789aa1302d9ae","observation_id":"a56c1cf4-112d-4e77-8d6f-3e20ce92ea4a","resolution":{"observed_at":"2026-08-14T10:13:15.199553Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:13:15.203687Z","title":"It measures the quality of fθ’s predictions","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.203687Z"},"links":{"citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:d8edd30b639f4c1618d6b96ebed59a26b4c5f20bd52a9ca8ebf66f12d973b3eb","observation_id":"adc2cc5d-7362-4220-9617-e13336c0ddf4","resolution":{"observed_at":"2026-08-14T10:13:15.203687Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:13:15.208349Z","title":"In simple cases the hyperparameters can be specified a priori","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.208349Z"},"links":{"citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:a017e9f5a4b1ed0f6aa327ae6c513f717ff1cb5ad407a5642ac0034eb7f23eb6","observation_id":"dc82953c-d32f-4ff0-a039-ca80fda11936","resolution":{"observed_at":"2026-08-14T10:13:15.208349Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:13:15.213198Z","title":"Estimate the coherence of noise","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.213198Z"},"links":{"citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:a63f563e256e0ea078ce45b97059c33934362876d65d960a6d424f474c5052ff","observation_id":"296ede83-e922-4bf3-bf99-097c816a365c","resolution":{"observed_at":"2026-08-14T10:13:15.213198Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:13:15.229016Z","title":"L =l GST feature vector","venue":null,"work_id":null,"year":2000},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.229016Z"},"links":{"citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:abfe01f3b49e47e14024e2863cccd7222ea0dc4ec4cf75cede02eab4ce6e8af6","observation_id":"874debbb-e1d9-4599-babe-3e1dc38c710d","resolution":{"observed_at":"2026-08-14T10:13:15.229016Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:13:15.233748Z","title":"Given a collection of feature vectors C = {(fj,yj)}N j=1, with yj ∈ {±1} indicating which class the feature vector fj∈F belongs to, learn a classifier c :F→{± 1}","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.233748Z"},"links":{"citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:4eef10e318dca71f745e295f75e864e548cef71b7b690b707787922d0c46862a","observation_id":"eb5eb9e7-d1f6-4c82-863a-6d0655d4487b","resolution":{"observed_at":"2026-08-14T10:13:15.233748Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:13:15.239973Z","title":"0/1 loss","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.239973Z"},"links":{"citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:d8431c3001b2f8bdf107d3e51255a653d58999022e14977f34bea43420f5a87f","observation_id":"97f8e03d-78e6-4324-848b-5435b3e7ac1a","resolution":{"observed_at":"2026-08-14T10:13:15.239973Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:13:15.244440Z","title":"For each algorithm, we performed hyperparameter tuning using brute-force grid search over the values listed in Table II; see Appendix C for details","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.244440Z"},"links":{"citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:f32ca0f38d54280c8313ed51abaee3485770b735a424abf49df23f58b50d851b","observation_id":"38bc39e5-494f-4fbb-984b-8f5ec3b64442","resolution":{"observed_at":"2026-08-14T10:13:15.244440Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:13:15.248232Z","title":"stochas- tic","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.248232Z"},"links":{"citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:3ae70d5b0ab521fc71d76dc325b8262f7fe652c69ac3ef5c4694a4675019afa3","observation_id":"c7b792c3-62a7-4cfe-b4ec-a9c76ffa20c5","resolution":{"observed_at":"2026-08-14T10:13:15.248232Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:13:15.253218Z","title":"linear GST","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.253218Z"},"links":{"citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:86502eb144e1d46d5c0ae1ac13300598dcf9834258f8ebbea3d22ef7993a081d","observation_id":"af13dce3-cfba-4386-8387-b959ba4c7da4","resolution":{"observed_at":"2026-08-14T10:13:15.253218Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:13:15.257269Z","title":"uninformative","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.257269Z"},"links":{"citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:fb3f4fa717086dc64ea625d5e4bbb3fa2b43ec6a4afbad794e9003fb5918a6c9","observation_id":"0f558a71-3334-44fc-a87a-ad432d7e277f","resolution":{"observed_at":"2026-08-14T10:13:15.257269Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:13:15.330711Z","title":"Hero test","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.330711Z"},"links":{"citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:db07d7451a019dced9b7a3019e42bc83ca580b2a575a32c7be1536cd67883213","observation_id":"dc526f0e-fda9-4496-874f-813f550444dc","resolution":{"observed_at":"2026-08-14T10:13:15.330711Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1801.00862","last_updated":"2018-07-31T21:46:33Z","snapshot_observed_at":"2026-08-14T19:58:26.631982Z","submitted_at":"2018-01-02T23:43:08Z","title":"Quantum Computing in the NISQ era and beyond","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1801.00862","snapshot_observed_at":"2026-08-14T10:13:15.268536Z","title":"Preskill, Quantum 2, 79 (2018), arXiv:1801.00862","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.268536Z"},"links":{"cited_paper":"/paper/1801.00862","citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:25659fabd1b9e35a66897ccf24e441b49dfe955ec5c5bfbde1461c996509bde4","observation_id":"d846b45b-197a-4590-81cf-484c917e2729","resolution":{"observed_at":"2026-08-14T10:13:15.268536Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:13:15.273010Z","title":"A Preview of Bristlecone, Google’s New Quan- tum Processor,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.273010Z"},"links":{"citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:f57f5955c8d04d09f15fcc3691da722faf6f19466a9d8ad8c10962748e732662","observation_id":"2855b13f-3063-4d37-98b1-c86a1a3cc03b","resolution":{"observed_at":"2026-08-14T10:13:15.273010Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:13:15.277577Z","title":"IBM Announces Advances to IBM Quantum Sys- tems & Ecosystem,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.277577Z"},"links":{"citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:d8ff10b68f099c9d63c6e50199f118caf789870c4a8342cfa856358474f8c9f8","observation_id":"111fb4de-b373-4c20-b79e-d913c0af6f0d","resolution":{"observed_at":"2026-08-14T10:13:15.277577Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1903.08181","last_updated":"2019-03-19T18:00:13Z","snapshot_observed_at":"2026-08-14T16:59:52.963865Z","submitted_at":"2019-03-19T18:00:13Z","title":"Benchmarking an 11-qubit quantum computer","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1903.08181","snapshot_observed_at":"2026-08-14T10:13:15.281874Z","title":"Wright, K","venue":null,"work_id":null,"year":1903},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.281874Z"},"links":{"cited_paper":"/paper/1903.08181","citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:65a5f03a1be1a5661fd6227cc140a05487be4dd4a0392adabf75698a704bcbda","observation_id":"cafa1954-1e7a-496e-951c-4dbc271b6b9e","resolution":{"observed_at":"2026-08-14T10:13:15.281874Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:13:15.286602Z","title":"Unsupervised Machine Learning on Rigetti 19Q with Forest 1.2,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.286602Z"},"links":{"citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:a61e39559814ce13e2341856ed461863f1ba986fcf477ad41352274305c0076f","observation_id":"5f0d878a-93ca-48a0-b057-ec67c61595bc","resolution":{"observed_at":"2026-08-14T10:13:15.286602Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1310.4492","last_updated":"2013-10-16T19:56:06Z","snapshot_observed_at":"2026-08-14T23:58:44.292972Z","submitted_at":"2013-10-16T19:56:06Z","title":"Robust, self-consistent, closed-form tomography of quantum logic gates on a trapped ion qubit","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1310.4492","snapshot_observed_at":"2026-08-14T10:13:15.291192Z","title":"Blume-Kohout, J","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.291192Z"},"links":{"cited_paper":"/paper/1310.4492","citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:058ed648691cdf7d3f5c34c929a981d973c7cae69362365e9cabb47dcf539d6a","observation_id":"779dc01a-9688-4698-8832-7fc9870e8ff2","resolution":{"observed_at":"2026-08-14T10:13:15.291192Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:13:15.295835Z","title":"Magesan, J","venue":null,"work_id":null,"year":2012},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.295835Z"},"links":{"citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:7ac107ab2534acd7b712a27c873a2ec4c0b99fd0ad3376f186b909a7c9349135","observation_id":"b8214921-ad4a-4938-aad1-a60272b7fe4c","resolution":{"observed_at":"2026-08-14T10:13:15.295835Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1009.3639","last_updated":"2010-09-19T13:59:08Z","snapshot_observed_at":"2026-08-15T05:08:25.693769Z","submitted_at":"2010-09-19T13:59:08Z","title":"Robust randomized benchmarking of quantum processes","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1009.3639","snapshot_observed_at":"2026-08-14T10:13:15.300034Z","title":"Magesan, J","venue":null,"work_id":null,"year":2011},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.300034Z"},"links":{"cited_paper":"/paper/1009.3639","citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:c0a1883c9d0b03a796625b2e93b693dbfe82d2be1877cc0e075d7a7832613e8b","observation_id":"d9fee7d5-0135-49af-b69f-b9807d564c4a","resolution":{"observed_at":"2026-08-14T10:13:15.300034Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1811.12926","last_updated":"2019-10-11T15:31:58Z","snapshot_observed_at":"2026-08-15T05:29:56.832153Z","submitted_at":"2018-11-30T18:25:51Z","title":"Validating quantum computers using randomized model circuits","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1811.12926","snapshot_observed_at":"2026-08-14T10:13:15.305092Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.305092Z"},"links":{"cited_paper":"/paper/1811.12926","citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:47139655d88e711196a8f3775444c2d5c1ac94dfa9444834756f8326d30d3530","observation_id":"b859b91b-ede3-4fd8-bd1c-933962275da1","resolution":{"observed_at":"2026-08-14T10:13:15.305092Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1904.05546","last_updated":"2020-11-16T17:17:07Z","snapshot_observed_at":"2026-08-14T16:48:14.050478Z","submitted_at":"2019-04-11T06:25:26Z","title":"A volumetric framework for quantum computer benchmarks","version":4},"cited_work":{"arxiv_id":"1904.05546","doi":null,"metadata_source":"pith","pith_arxiv_id":"1904.05546","snapshot_observed_at":"2026-08-14T10:13:16.271194Z","title":"A volumetric framework for quantum computer benchmarks","venue":"quant-ph","work_id":"afd34f3a-04d7-498b-9aa1-9e7bcd2a854d","year":2019},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.309419Z"},"links":{"cited_paper":"/paper/1904.05546","citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:d973efa0082948bfedbfedcad80766e89e1c269a3b59971fe4cb6fd944a57a52","observation_id":"26541d51-8404-464f-bc9b-c3d6a837e8c0","resolution":{"observed_at":"2026-08-14T10:13:16.276190Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:13:15.313885Z","title":null,"venue":null,"work_id":null,"year":1959},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.313885Z"},"links":{"citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:2a45a58edb15ed5f5960fac63ebcfb6892415ed6cfefa09cbb7dd731680a3307","observation_id":"b1df963f-7324-4b8e-bf6e-50389d2b06ab","resolution":{"observed_at":"2026-08-14T10:13:15.313885Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:13:15.317926Z","title":"Hastie, R","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.317926Z"},"links":{"citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:2a752349b60674f85e3bb45e4f130e24e829596132e6a61d0785795933fdbe66","observation_id":"4937fa07-a881-46e5-a2bd-01588afc2df0","resolution":{"observed_at":"2026-08-14T10:13:15.317926Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:13:15.322195Z","title":"Goodfellow, Y","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.322195Z"},"links":{"citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:08a1d1417dd6031f4da507586042c0f933c8bf690b7553b3cace4262bfa3197f","observation_id":"e86a517c-b8f4-4779-acc8-57c8975beb46","resolution":{"observed_at":"2026-08-14T10:13:15.322195Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:13:15.326533Z","title":"James, D","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.326533Z"},"links":{"citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:f4d1208f6d2a5ad5dc67c55f94af3d653ad4d1aade8ce32cf2b71a8a949467f2","observation_id":"abf24f38-1b62-4ce2-844f-39190afecc02","resolution":{"observed_at":"2026-08-14T10:13:15.326533Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1603.08675","last_updated":"2016-09-22T09:32:16Z","snapshot_observed_at":"2026-08-14T22:04:07.347684Z","submitted_at":"2016-03-29T08:25:22Z","title":"Quantum Recommendation Systems","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1603.08675","snapshot_observed_at":"2026-08-14T10:13:15.401484Z","title":"Kerenidis and A","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.401484Z"},"links":{"cited_paper":"/paper/1603.08675","citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:169a900bcd96fc03528d5c3e4c68e29f2b84154ce7b4b29c3e4c47fa59b2b6dd","observation_id":"f15d6549-3344-4586-8912-8895328e706c","resolution":{"observed_at":"2026-08-14T10:13:15.401484Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:13:15.335062Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.335062Z"},"links":{"citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:89b1de22227015dbb39a905fc94201a5b1135a8949c824582caa4e66b8982c15","observation_id":"50311ac5-e9c1-4740-9ba7-1a3228642d5f","resolution":{"observed_at":"2026-08-14T10:13:15.335062Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:13:15.339934Z","title":"Wasserman, All of Statistics: A Concise Course in Statistical Inference (Springer New York, 2004)","venue":null,"work_id":null,"year":2004},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.339934Z"},"links":{"citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:a4cebc02187ef79c0fad94f83d7146b278f67266bab5f04a160fe4febcf1022f","observation_id":"78942d42-0007-4185-80bc-ed6b22b42d4e","resolution":{"observed_at":"2026-08-14T10:13:15.339934Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:13:15.344749Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.344749Z"},"links":{"citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:6205921bcc6cc8c6a57e7e72b3ca316f5a4d61ad9e8235e7c687fd84daef3f82","observation_id":"c8f879d8-903f-43c0-af7a-1e54be0ef7cf","resolution":{"observed_at":"2026-08-14T10:13:15.344749Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:13:15.350369Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.350369Z"},"links":{"citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:527a445a5c5c8816b059ad0d0154cccf46d7ed5d53dbadc1085eb90f983fb47b","observation_id":"c72eb85e-24da-43b9-ba74-2b29c2665991","resolution":{"observed_at":"2026-08-14T10:13:15.350369Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:13:15.354541Z","title":null,"venue":null,"work_id":null,"year":1943},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.354541Z"},"links":{"citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:5571a7c2888224e6b24a153425e40c79148e2b383684f7278b1d7a2132fb3a10","observation_id":"3b7639d5-f550-4b7d-a353-41844100c03f","resolution":{"observed_at":"2026-08-14T10:13:15.354541Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:13:15.359397Z","title":"Farley and W","venue":null,"work_id":null,"year":1954},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.359397Z"},"links":{"citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:43be55731489f3bfadad49f8bbeaa8681ccdc6e239e69cbbd81659757d52c596","observation_id":"67066db5-79da-4996-b00a-92fafa992d0f","resolution":{"observed_at":"2026-08-14T10:13:15.359397Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:13:15.363444Z","title":null,"venue":null,"work_id":null,"year":2006},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.363444Z"},"links":{"citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:3ac96f224b6d71f0dc2fc6866ae007d74fc47e7255905bd5e0522c1a50e2c0d5","observation_id":"e6be2a33-0863-4cc5-856a-b951296aa82e","resolution":{"observed_at":"2026-08-14T10:13:15.363444Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1503.07865","last_updated":"2019-01-26T19:23:32Z","snapshot_observed_at":"2026-08-14T22:54:45.879537Z","submitted_at":"2015-03-26T20:00:24Z","title":"Estimating the Coherence of Noise","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1503.07865","snapshot_observed_at":"2026-08-14T10:13:15.367566Z","title":"Wallman, C","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.367566Z"},"links":{"cited_paper":"/paper/1503.07865","citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:515870bc859c217cba2d2cf7c70aa111145903c349353293b5808278a96a6207","observation_id":"a83758a3-96a2-40bc-b537-996f26aa9feb","resolution":{"observed_at":"2026-08-14T10:13:15.367566Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1603.03761","last_updated":"2016-12-07T21:34:12Z","snapshot_observed_at":"2026-08-14T22:06:24.861101Z","submitted_at":"2016-03-11T20:58:06Z","title":"Estimating the coherence of noise in quantum control of a solid-state qubit","version":3},"cited_work":{"arxiv_id":"1603.03761","doi":null,"metadata_source":"pith","pith_arxiv_id":"1603.03761","snapshot_observed_at":"2026-08-14T10:13:16.242148Z","title":"Estimating the coherence of noise in quantum control of a solid-state qubit","venue":"quant-ph","work_id":"0c6c6444-6e6b-4990-aa74-9aaa99453a53","year":2016},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.372030Z"},"links":{"cited_paper":"/paper/1603.03761","citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:cafa3d7d1514f03aebcaf58c0889ff7c8ebc8902fa56c23fd1fe10967d910f77","observation_id":"e4d1109d-a84a-4c77-8bf0-c0444dc6aecc","resolution":{"observed_at":"2026-08-14T10:13:16.246467Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1409.3097","last_updated":"2014-09-10T14:51:33Z","snapshot_observed_at":"2026-08-14T23:20:00.761564Z","submitted_at":"2014-09-10T14:51:33Z","title":"An introduction to quantum machine learning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1409.3097","snapshot_observed_at":"2026-08-14T10:13:15.376358Z","title":"Schuld, I","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.376358Z"},"links":{"cited_paper":"/paper/1409.3097","citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:b9ce09d85a102b1a8efb880e43e48a6fb174e61c0d0921fb16e855b7d5f52e1e","observation_id":"76ddb7e0-e007-4b21-9d44-78c5137fbea9","resolution":{"observed_at":"2026-08-14T10:13:15.376358Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1611.09347","last_updated":"2018-05-10T19:44:58Z","snapshot_observed_at":"2026-08-14T21:28:14.672465Z","submitted_at":"2016-11-28T20:59:46Z","title":"Quantum Machine Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1611.09347","snapshot_observed_at":"2026-08-14T10:13:15.380576Z","title":"Biamonte, P","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.380576Z"},"links":{"cited_paper":"/paper/1611.09347","citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:22fee4fc85e3cf171e826666f8e772931d6d9bf1d8d2a3b4fdfa671d2a714c82","observation_id":"4ce930c3-0c32-498b-a51d-bf5974d86ca4","resolution":{"observed_at":"2026-08-14T10:13:15.380576Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:13:15.385208Z","title":"Papers - Physics & Machine Learning,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.385208Z"},"links":{"citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:92af2c59d385b9dc425157c27570d534c7678ab7408bc37d182ec97206ca0c7e","observation_id":"78321069-b3e6-4671-915c-b3dcf9e1342f","resolution":{"observed_at":"2026-08-14T10:13:15.385208Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:13:15.389476Z","title":"Dunjko and H","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.389476Z"},"links":{"citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:732d8a6a8fc01808cdbda87018c9f6c4338051cd54625857699d005f7d266645","observation_id":"fcc5c7b0-5263-4c97-91e9-e7ad89a73952","resolution":{"observed_at":"2026-08-14T10:13:15.389476Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"0811.3171","last_updated":"2009-09-30T15:24:42Z","snapshot_observed_at":"2026-08-13T06:45:21.548753Z","submitted_at":"2008-11-19T20:36:41Z","title":"Quantum algorithm for solving linear systems of equations","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"0811.3171","snapshot_observed_at":"2026-08-14T10:13:15.397000Z","title":null,"venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.397000Z"},"links":{"cited_paper":"/paper/0811.3171","citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:56c9943ecaaed4dcc58561ed2b9601bf7e240a5e34452ce1f0aed17267d611f4","observation_id":"5756eede-b2b8-4b6e-a063-1e33cf164fce","resolution":{"observed_at":"2026-08-14T10:13:15.397000Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:13:15.472799Z","title":"Torlai, G","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.472799Z"},"links":{"citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:0c9b2396a12ae5d3d5f98e3b94c98a3a3da6cc060bc7c4a5f7873bdec424b67b","observation_id":"3a6b13e4-9588-4bbb-a09e-47020740ba04","resolution":{"observed_at":"2026-08-14T10:13:15.472799Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:13:15.405435Z","title":"Tang, arXiv (2019), 10.1145/3313276.3316310, arXiv:arXiv:1807.04271v3","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.405435Z"},"links":{"citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:89a8932a1853fc660f52aea105acf9c734f90593690f87ea1d695fe6f31232f8","observation_id":"d26cbd65-0241-4fba-86fd-4499359c1d88","resolution":{"observed_at":"2026-08-14T10:13:15.405435Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1811.00414","last_updated":"2021-08-06T20:42:26Z","snapshot_observed_at":"2026-08-14T18:06:40.666468Z","submitted_at":"2018-10-31T03:23:52Z","title":"Quantum principal component analysis only achieves an exponential speedup because of its state preparation assumptions","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1811.00414","snapshot_observed_at":"2026-08-14T10:13:15.410091Z","title":"Tang, arXiv (2018), arXiv:1811.00414","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.410091Z"},"links":{"cited_paper":"/paper/1811.00414","citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:997faa5838793ab562add7a11e8bcccdb6a176b31a4124c9906c8b57a1253daa","observation_id":"3dc09641-c48a-4d00-861b-958bbff5fdd9","resolution":{"observed_at":"2026-08-14T10:13:15.410091Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1811.04909","last_updated":"2018-11-12T18:49:42Z","snapshot_observed_at":"2026-08-14T18:00:28.239124Z","submitted_at":"2018-11-12T18:49:42Z","title":"Quantum-inspired low-rank stochastic regression with logarithmic dependence on the dimension","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1811.04909","snapshot_observed_at":"2026-08-14T10:13:15.415562Z","title":"Gily´ en, S","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.415562Z"},"links":{"cited_paper":"/paper/1811.04909","citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:705d935ea1e59527dc315a033f59267e7dfc13c2c53e16569d40d0de2a309154","observation_id":"40f737bf-26dc-49a5-bc12-61e8b61ae47e","resolution":{"observed_at":"2026-08-14T10:13:15.415562Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1806.00419","last_updated":"2019-11-18T08:58:37Z","snapshot_observed_at":"2026-08-14T19:08:29.044747Z","submitted_at":"2018-06-01T16:16:41Z","title":"Automated discovery of characteristic features of phase transitions in many-body localization","version":3},"cited_work":{"arxiv_id":"1806.00419","doi":null,"metadata_source":"pith","pith_arxiv_id":"1806.00419","snapshot_observed_at":"2026-08-14T10:13:16.049191Z","title":"Automated discovery of characteristic features of phase transitions in many-body localization","venue":"quant-ph","work_id":"b22bed77-4556-4672-8da5-8430858b2c8e","year":2018},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.420406Z"},"links":{"cited_paper":"/paper/1806.00419","citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:f2a78ae824aea199997b6e423628f3412a1290f511e58d07c65f07dba396677d","observation_id":"a52de8d3-15fb-42be-8d81-034d09185996","resolution":{"observed_at":"2026-08-14T10:13:16.054057Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1610.02048","last_updated":"2016-10-06T20:04:06Z","snapshot_observed_at":"2026-08-14T21:36:21.006941Z","submitted_at":"2016-10-06T20:04:06Z","title":"Learning phase transitions by confusion","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1610.02048","snapshot_observed_at":"2026-08-14T10:13:15.425325Z","title":null,"venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.425325Z"},"links":{"cited_paper":"/paper/1610.02048","citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:89cacba450018f358e02d256fdc6793c71acc5fda62659ae81208f308f180744","observation_id":"9e77452f-85f8-4f80-9c57-02d219d2834d","resolution":{"observed_at":"2026-08-14T10:13:15.425325Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1605.01735","last_updated":"2016-05-05T20:00:04Z","snapshot_observed_at":"2026-08-14T21:58:38.997806Z","submitted_at":"2016-05-05T20:00:04Z","title":"Machine learning phases of matter","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1605.01735","snapshot_observed_at":"2026-08-14T10:13:15.430306Z","title":"Carrasquilla and R","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.430306Z"},"links":{"cited_paper":"/paper/1605.01735","citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:63629d1d11ae27b2e93a4e789e2ca7427993d32c098a869d2e59b155579d2cf3","observation_id":"4e52d6df-754f-4109-90d8-4c887ef23466","resolution":{"observed_at":"2026-08-14T10:13:15.430306Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1609.02552","last_updated":"2017-09-11T03:37:05Z","snapshot_observed_at":"2026-08-14T21:40:42.127881Z","submitted_at":"2016-09-08T19:54:34Z","title":"Machine Learning Phases of Strongly Correlated Fermions","version":3},"cited_work":{"arxiv_id":"1609.02552","doi":null,"metadata_source":"pith","pith_arxiv_id":"1609.02552","snapshot_observed_at":"2026-08-14T10:13:16.008232Z","title":"Machine Learning Phases of Strongly Correlated Fermions","venue":"cond-mat.str-el","work_id":"3b4d0c88-e239-4c1a-a61d-71701f80d7c7","year":2016},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.435142Z"},"links":{"cited_paper":"/paper/1609.02552","citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:8e8b71e985a03e5990e24134edac96798a67f0e8a74e80113990a8cf9fa51dd4","observation_id":"fdbb1c1a-8201-485e-86b4-d31c04eb4db8","resolution":{"observed_at":"2026-08-14T10:13:16.012702Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1703.02435","last_updated":"2017-03-12T23:44:34Z","snapshot_observed_at":"2026-08-14T21:13:05.114043Z","submitted_at":"2017-03-07T15:34:12Z","title":"Unsupervised learning of phase transitions: from principal component analysis to variational autoencoders","version":2},"cited_work":{"arxiv_id":"1703.02435","doi":null,"metadata_source":"pith","pith_arxiv_id":"1703.02435","snapshot_observed_at":"2026-08-14T10:13:15.990610Z","title":"Unsupervised learning of phase transitions: from principal component analysis to variational autoencoders","venue":"cond-mat.stat-mech","work_id":"d22d9449-0399-422e-b2fd-c03b6cc6ba9e","year":2017},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.440301Z"},"links":{"cited_paper":"/paper/1703.02435","citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:ad37279132df49483534ebffd05fa731cfcac9c20cbdac318e9e20ef9138c00e","observation_id":"4a97350a-e202-424c-a3e1-9a471017f926","resolution":{"observed_at":"2026-08-14T10:13:15.995377Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1708.09401","last_updated":"2018-01-19T23:13:36Z","snapshot_observed_at":"2026-08-14T20:37:38.229898Z","submitted_at":"2017-08-30T18:00:51Z","title":"Machine Learning Topological Invariants with Neural Networks","version":3},"cited_work":{"arxiv_id":"1708.09401","doi":null,"metadata_source":"pith","pith_arxiv_id":"1708.09401","snapshot_observed_at":"2026-08-14T10:13:15.973792Z","title":"Machine Learning Topological Invariants with Neural Networks","venue":"cond-mat.mes-hall","work_id":"58047904-8974-4a4d-b71b-93c12fb3d626","year":2017},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.444753Z"},"links":{"cited_paper":"/paper/1708.09401","citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:2d7d46fc6156beaaed6b99da5b0056738c8df7f80d07e815b9a8eae1fb68d79b","observation_id":"ee27362b-bad4-4af0-9815-baed41cad074","resolution":{"observed_at":"2026-08-14T10:13:15.978021Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1207.1655","last_updated":"2012-09-18T02:07:11Z","snapshot_observed_at":"2026-08-15T00:54:06.826348Z","submitted_at":"2012-07-06T15:17:55Z","title":"Robust Online Hamiltonian Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1207.1655","snapshot_observed_at":"2026-08-14T10:13:15.449580Z","title":null,"venue":null,"work_id":null,"year":2012},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.449580Z"},"links":{"cited_paper":"/paper/1207.1655","citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:cb13ab9fda99a5dc04630734a2e2f6ff3e21abe091a664db048c68410d79d356","observation_id":"aad6484e-e900-4cf8-b4dd-648272a748d3","resolution":{"observed_at":"2026-08-14T10:13:15.449580Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1807.01852","last_updated":"2019-03-07T02:36:44Z","snapshot_observed_at":"2026-08-14T18:55:31.854746Z","submitted_at":"2018-07-05T05:53:21Z","title":"Efficient online quantum state estimation using a matrix-exponentiated gradient method","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1807.01852","snapshot_observed_at":"2026-08-14T10:13:15.454242Z","title":"Youssry, C","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.454242Z"},"links":{"cited_paper":"/paper/1807.01852","citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:1f9b376b1172a70c63137d7307832a144995c98ce8303ec9f560e6866dc843e3","observation_id":"17f0aeb9-b2f3-4a24-a6d9-535f95580f08","resolution":{"observed_at":"2026-08-14T10:13:15.454242Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1712.01291","last_updated":"2017-12-04T19:00:03Z","snapshot_observed_at":"2026-08-14T20:07:03.817890Z","submitted_at":"2017-12-04T19:00:03Z","title":"Machine learning for predictive estimation of qubit dynamics subject to dephasing","version":1},"cited_work":{"arxiv_id":"1712.01291","doi":null,"metadata_source":"pith","pith_arxiv_id":"1712.01291","snapshot_observed_at":"2026-08-14T10:13:15.935302Z","title":"Machine learning for predictive estimation of qubit dynamics subject to dephasing","venue":"quant-ph","work_id":"b5403480-69e9-4067-b99a-14966296d3ac","year":2017},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.459280Z"},"links":{"cited_paper":"/paper/1712.01291","citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:1a46e5b63fdb8e53ff27b6b5560b0848a409aa3dbc275e74812ba47a282744d7","observation_id":"14b70dac-32ab-4081-8555-2194969fc573","resolution":{"observed_at":"2026-08-14T10:13:15.939644Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1411.4994","last_updated":"2014-11-24T20:34:49Z","snapshot_observed_at":"2026-08-14T23:11:08.814670Z","submitted_at":"2014-11-18T20:08:38Z","title":"Machine learning for discriminating quantum measurement trajectories and improving readout","version":2},"cited_work":{"arxiv_id":"1411.4994","doi":null,"metadata_source":"pith","pith_arxiv_id":"1411.4994","snapshot_observed_at":"2026-08-14T10:13:15.916744Z","title":"Machine learning for discriminating quantum measurement trajectories and improving readout","venue":"quant-ph","work_id":"55133b88-b5b9-4562-a7f1-ddb997db84f0","year":2014},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.463852Z"},"links":{"cited_paper":"/paper/1411.4994","citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:50498bac10ee573549b313eb7a316c2e78f2acc10962f6de6f9177ccb687657d","observation_id":"893687bc-76e0-4a0a-989f-33013a5b170a","resolution":{"observed_at":"2026-08-14T10:13:15.921747Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1807.10300","last_updated":"2020-01-23T10:31:04Z","snapshot_observed_at":"2026-08-14T18:47:19.608034Z","submitted_at":"2018-07-26T18:07:01Z","title":"Discovering physical concepts with neural networks","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1807.10300","snapshot_observed_at":"2026-08-14T10:13:15.468369Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.468369Z"},"links":{"cited_paper":"/paper/1807.10300","citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:ceed943257f645b36ebd297fe614493ade91b8d18badf4e714f56136e8c1fe50","observation_id":"a78d3fcc-0d8e-4b09-b465-cb20de6f4c50","resolution":{"observed_at":"2026-08-14T10:13:15.468369Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:13:15.542196Z","title":"Pedregosa, G","venue":null,"work_id":null,"year":2011},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.542196Z"},"links":{"citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:5f93df83d9e175e7020ab453d6082ea78c53de0e4fdb84ad194ada1e2a1bb896","observation_id":"7974c3a4-af8a-4ce9-8940-0c44c2dea202","resolution":{"observed_at":"2026-08-14T10:13:15.542196Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:13:16.997112Z","title":"The canonical QCVV task is to estimate a specific property, so supervised learning is more relevant","venue":null,"work_id":"0d9645bc-445e-4640-94b1-1a7267d75888","year":null},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.476386Z"},"links":{"citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:920201c73ff1b887b80cd52b205046c986e2ecbf31f2764f40f6915351275ff4","observation_id":"8f0442a2-a487-427c-8bc4-7228c2bfd40f","resolution":{"observed_at":"2026-08-14T10:13:17.002267Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:13:16.984180Z","title":null,"venue":null,"work_id":"1d35f105-0c69-459d-965f-163129475985","year":null},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.479970Z"},"links":{"citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:36801ebce8ed71fd8894b607c7986c09762682f95c623305ee09fe271a4eaf88","observation_id":"79abe12d-1601-4021-9a9f-1559c00baae6","resolution":{"observed_at":"2026-08-14T10:13:16.988418Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:13:16.970988Z","title":null,"venue":null,"work_id":"31f5e3fb-e3e3-4a61-8eb5-9b94a5199f28","year":1998},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.484477Z"},"links":{"citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:57dd94720075bc5b7ef716251f3d67191e7831047b69914d7e6f5096e7397297","observation_id":"cc9b21e2-2020-4983-8684-05bd41f9d92e","resolution":{"observed_at":"2026-08-14T10:13:16.975149Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:13:16.957128Z","title":null,"venue":null,"work_id":"033349fc-092c-4304-8496-bbad8e98fe46","year":2015},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.489516Z"},"links":{"citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:331362ca393f6cbc42cbbb96e4b9beaf7dbeeb5d7769060e22c996d9fdaf0cda","observation_id":"cac5c873-5dcc-42c3-bf49-fad42b99ab74","resolution":{"observed_at":"2026-08-14T10:13:16.961538Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:13:16.944117Z","title":"Bergstra, D","venue":null,"work_id":"03c82f79-751a-481b-907b-ed7cfdaa61df","year":2013},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":65,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.495538Z"},"links":{"citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:95fe4e8aa5509267c4ed5be9edc9252f4ad49b9c574b5b72f2ef0bbbe518cb9a","observation_id":"10c31703-dd8d-4bdb-9ec7-d8844c4edd2c","resolution":{"observed_at":"2026-08-14T10:13:16.948895Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1510.05653","last_updated":"2016-07-19T17:38:18Z","snapshot_observed_at":"2026-08-14T22:27:10.947068Z","submitted_at":"2015-10-19T20:17:47Z","title":"Comparing Experiments to the Fault-Tolerance Threshold","version":2},"cited_work":{"arxiv_id":"1510.05653","doi":null,"metadata_source":"pith","pith_arxiv_id":"1510.05653","snapshot_observed_at":"2026-08-14T10:13:15.886050Z","title":"Comparing Experiments to the Fault-Tolerance Threshold","venue":"quant-ph","work_id":"a68c20c1-2d7a-4b76-9ac6-290c33c690e2","year":2015},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":66,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.499795Z"},"links":{"cited_paper":"/paper/1510.05653","citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:bde2ce888ec66a422d559a57a5a2e376ea57a815f78c30e092dbeceed5e0dfef","observation_id":"a553f596-c8c5-46fe-834f-ad07cf70debb","resolution":{"observed_at":"2026-08-14T10:13:15.892142Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1704.03961","last_updated":"2017-04-13T00:55:59Z","snapshot_observed_at":"2026-08-14T21:06:56.890065Z","submitted_at":"2017-04-13T00:55:59Z","title":"Quantum error correction failure distributions: comparison of coherent and stochastic error models","version":1},"cited_work":{"arxiv_id":"1704.03961","doi":null,"metadata_source":"pith","pith_arxiv_id":"1704.03961","snapshot_observed_at":"2026-08-14T10:13:15.868189Z","title":"Quantum error correction failure distributions: comparison of coherent and stochastic error models","venue":"quant-ph","work_id":"5209779a-4d6e-41c5-8eb2-2e519c701eb8","year":2017},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":67,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.505239Z"},"links":{"cited_paper":"/paper/1704.03961","citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:b9d9feb2e13fb224f7afcc1d2489771827b4f95eacfc532632bdc72802d6d264","observation_id":"974c01b2-3a4c-41bd-be2d-21a952dad49d","resolution":{"observed_at":"2026-08-14T10:13:15.872878Z","resolver_source":"local_arxiv","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1607.06460","last_updated":"2017-08-01T13:43:10Z","snapshot_observed_at":"2026-08-14T21:47:20.940444Z","submitted_at":"2016-07-21T20:00:00Z","title":"Tensor-Network Simulations of the Surface Code under Realistic Noise","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1607.06460","snapshot_observed_at":"2026-08-14T10:13:15.509805Z","title":null,"venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":68,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.509805Z"},"links":{"cited_paper":"/paper/1607.06460","citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:1957a8ed6e324b919351f80907ccba93f7f25b61d22744d1904d7817a787f2e9","observation_id":"619739fa-fd68-4f14-8670-a20864749ab5","resolution":{"observed_at":"2026-08-14T10:13:15.509805Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1512.01098","last_updated":"2016-06-09T17:25:30Z","snapshot_observed_at":"2026-08-14T22:20:09.183430Z","submitted_at":"2015-12-03T14:52:16Z","title":"Noise tailoring for scalable quantum computation via randomized compiling","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1512.01098","snapshot_observed_at":"2026-08-14T10:13:15.516103Z","title":null,"venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":69,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.516103Z"},"links":{"cited_paper":"/paper/1512.01098","citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:94f6181f8581f52fa9e4547fa213102a0f5b676468546e63e5fa7264e9f484a6","observation_id":"765ae8f7-dfde-4b6b-8868-19110db708fa","resolution":{"observed_at":"2026-08-14T10:13:15.516103Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1605.03604","last_updated":"2016-05-11T20:09:46Z","snapshot_observed_at":"2026-08-14T21:57:46.277878Z","submitted_at":"2016-05-11T20:09:46Z","title":"Errors and pseudo-thresholds for incoherent and coherent noise","version":1},"cited_work":{"arxiv_id":"1605.03604","doi":null,"metadata_source":"pith","pith_arxiv_id":"1605.03604","snapshot_observed_at":"2026-08-14T10:13:15.825401Z","title":"Errors and pseudo-thresholds for incoherent and coherent noise","venue":"quant-ph","work_id":"b7c8cc26-7d0d-480f-9201-2ff67a6c6b05","year":2016},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":70,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.521307Z"},"links":{"cited_paper":"/paper/1605.03604","citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:67c0d02c4384abe663776e82d3dbd1415d2f196c02d2f73f24b50b13fe0ef031","observation_id":"56ffd470-92ec-4b1d-8f15-d8bcac24b7b5","resolution":{"observed_at":"2026-08-14T10:13:15.830042Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1504.06597","last_updated":"2015-04-24T18:56:54Z","snapshot_observed_at":"2026-08-14T22:51:06.986459Z","submitted_at":"2015-04-24T18:56:54Z","title":"Characterizing errors on qubit operations via iterative randomized benchmarking","version":1},"cited_work":{"arxiv_id":"1504.06597","doi":null,"metadata_source":"pith","pith_arxiv_id":"1504.06597","snapshot_observed_at":"2026-08-14T10:13:15.806518Z","title":"Characterizing errors on qubit operations via iterative randomized benchmarking","venue":"quant-ph","work_id":"a5da3812-6938-4f51-8a4d-cce0a4f2f914","year":2015},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":71,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.527157Z"},"links":{"cited_paper":"/paper/1504.06597","citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:09d5213cf82072510a6e9ec131769752a73ccd497ed0948ae77c47abd8e166ea","observation_id":"ff15c46d-cc43-45e2-84b3-6f71ee9d0f49","resolution":{"observed_at":"2026-08-14T10:13:15.812301Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1509.02921","last_updated":"2015-09-09T20:14:16Z","snapshot_observed_at":"2026-08-14T22:33:04.628799Z","submitted_at":"2015-09-09T20:14:16Z","title":"Introduction to Quantum Gate Set Tomography","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1509.02921","snapshot_observed_at":"2026-08-14T10:13:15.532268Z","title":"Greenbaum, arXiv:1509.02921","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":72,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.532268Z"},"links":{"cited_paper":"/paper/1509.02921","citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:8a880588e7e74ad004d2a523a575796c72b15515b55634c16632be6a60a60afc","observation_id":"0f9797b3-8c2d-42af-b30f-f8b3facc6fe7","resolution":{"observed_at":"2026-08-14T10:13:15.532268Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1605.07674","last_updated":"2017-01-29T23:05:43Z","snapshot_observed_at":"2026-08-14T21:55:53.300789Z","submitted_at":"2016-05-24T22:27:46Z","title":"Demonstration of qubit operations below a rigorous fault tolerance threshold with gate set tomography","version":2},"cited_work":{"arxiv_id":"1605.07674","doi":null,"metadata_source":"pith","pith_arxiv_id":"1605.07674","snapshot_observed_at":"2026-08-14T10:13:15.778441Z","title":"Demonstration of qubit operations below a rigorous fault tolerance threshold with gate set tomography","venue":"quant-ph","work_id":"8cc0d183-c4a6-43c0-b019-8b8a8c9628a8","year":2016},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":73,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.537060Z"},"links":{"cited_paper":"/paper/1605.07674","citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:dae2dce5890179eacd7b0febcc9c30abb4a8d94a60b831837ad9fb67e45ca956","observation_id":"972e4be1-0649-4be5-aebd-b0e072de88f8","resolution":{"observed_at":"2026-08-14T10:13:15.783051Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:13:16.748792Z","title":null,"venue":null,"work_id":"4fff62ea-5337-4562-bb1e-8e6378ad3199","year":1962},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":74,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.600924Z"},"links":{"citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:f02b85057f0b17360c5ecba1cbd6d781719077128f373ec6c99969701b1592c6","observation_id":"6e1fe2cf-fb33-463c-9917-ab877928919b","resolution":{"observed_at":"2026-08-14T10:13:16.759319Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:13:16.923667Z","title":"Rosenblatt, Psychological Review 65, 386 (1958)","venue":null,"work_id":"5240551f-a6b4-4a03-b84b-68589b225ea5","year":1958},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":75,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.546896Z"},"links":{"citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:1ef0edce032322c3e438706f5e6f708a050fd98574627aaab023492099f8d612","observation_id":"add63a7a-9235-403e-898a-2dcedf4aa0c0","resolution":{"observed_at":"2026-08-14T10:13:16.927723Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:13:16.911086Z","title":"Rosenblatt, The Perceptron - A Perceiving and Rec- ognizing Automaton , Tech","venue":null,"work_id":"9cdd8351-1284-453d-9a7d-daa1003049e7","year":1957},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":76,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.551085Z"},"links":{"citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:a6f3a279064cdd3399f8d2904b9c6a60c6f34de94e11fd6247269a91c8ee2be6","observation_id":"3c838135-60cf-4a7d-8a4c-dc7f834c92d6","resolution":{"observed_at":"2026-08-14T10:13:16.915385Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:13:16.896862Z","title":null,"venue":null,"work_id":"3d0110c2-c925-4d0d-92af-535d1223fb1e","year":1964},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":77,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.555296Z"},"links":{"citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:06271e7a305884ba7aab366aa6d2139317abf3e0d29bab25055faf6c33100385","observation_id":"be9432e7-99e8-488b-bc27-34c531b2fe66","resolution":{"observed_at":"2026-08-14T10:13:16.901574Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:13:16.884206Z","title":"Hofmann, B","venue":null,"work_id":"0c63c391-c6df-472e-bf75-91210244984b","year":2008},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":78,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.559053Z"},"links":{"citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:52733547c6466c53b688dafe6288c05bd51f7f10686a5f8c42e47c82a786b89f","observation_id":"5fcd0381-9467-4d5f-9fdb-31bdfb9d4c8d","resolution":{"observed_at":"2026-08-14T10:13:16.888593Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:13:16.870971Z","title":"Guyon, B","venue":null,"work_id":"4d38ae1c-e1e6-4098-bfea-c323e6a24da6","year":1993},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":79,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.563748Z"},"links":{"citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:fe80f50d1181c62371e9953b807bd0e1b885e19a680389be912418f4ad0cc1a0","observation_id":"62ef0c5e-d43e-45d8-a695-fc8a58f85029","resolution":{"observed_at":"2026-08-14T10:13:16.875076Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:13:16.856714Z","title":"pyGSTio/pyGSTi,","venue":null,"work_id":"169e57cb-f2d9-4e7b-a0f1-e6ec91070fe6","year":2017},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":80,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.567319Z"},"links":{"citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:6373bce7cae66fc970756ba077a16cff0b292964950a7aa554d583cab099a9cf","observation_id":"d9c5d0bc-7ad5-4442-b2d0-dd418140c003","resolution":{"observed_at":"2026-08-14T10:13:16.861506Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1307.1662","last_updated":"2014-06-27T17:31:33Z","snapshot_observed_at":"2026-08-15T00:11:38.024104Z","submitted_at":"2013-07-05T16:52:09Z","title":"Polyglot: Distributed Word Representations for Multilingual NLP","version":2},"cited_work":{"arxiv_id":"1307.1662","doi":null,"metadata_source":"pith","pith_arxiv_id":"1307.1662","snapshot_observed_at":"2026-08-14T10:13:15.758674Z","title":"Polyglot: Distributed Word Representations for Multilingual NLP","venue":"cs.CL","work_id":"26b0d7cd-3a08-41a0-9c89-d978fdf06b34","year":2013},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":81,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.571210Z"},"links":{"cited_paper":"/paper/1307.1662","citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:4e4b13ca17fc974c7462455ec18f85acd5134a08c3180497d3e00b7220498b6d","observation_id":"2f579bb0-54f8-4713-a428-a9ce78e5c9bd","resolution":{"observed_at":"2026-08-14T10:13:15.765056Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:13:16.842976Z","title":"Jolliffe, Principal Component Analysis , 2nd ed","venue":null,"work_id":"3746c4fb-851b-4e0a-9d6d-c42d1f337dcf","year":2002},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":82,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.575705Z"},"links":{"citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:238539647d374cc69c7aee5e001f130d65a0f046b24bf8b17edc1533ea60bcd3","observation_id":"6c74a336-6e97-400c-8786-71ed820a0065","resolution":{"observed_at":"2026-08-14T10:13:16.847911Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:13:16.828414Z","title":"Hotelling, Journal of Educational Psychology 24, 417 (1933)","venue":null,"work_id":"2013ebb0-8797-4767-9d81-846fcaf537e7","year":1933},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":83,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.579530Z"},"links":{"citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:77e644d8d41ba58cc1a21f6bce510d808b21617b056736a11bcb57f823382151","observation_id":"c9977cac-710d-4d3f-8e30-f321f49dc5db","resolution":{"observed_at":"2026-08-14T10:13:16.833014Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:13:16.812017Z","title":"Pearson, The London, Edinburgh, and Dublin Philo- sophical Magazine and Journal of Science 2, 559 (1901)","venue":null,"work_id":"804a59d9-0b8d-4ace-b512-60221f7a040d","year":1901},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":84,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.583211Z"},"links":{"citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:227fd4acd4f98d19de428e62d393759cf2c70b66b0bf3a213f9eb5052b1abe2c","observation_id":"14d09871-fd6c-41b0-946c-7d722d84736f","resolution":{"observed_at":"2026-08-14T10:13:16.818670Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:13:16.797352Z","title":"Borg and P","venue":null,"work_id":"cd4a0cd6-11bb-4a45-afed-856a13d082d8","year":2005},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":85,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.587217Z"},"links":{"citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:ea99fb5e543e1b22d1b541ebf3f7522f7c210460b806ccb312ff6f4e4430690c","observation_id":"2aaf1b6f-27d2-41bd-9de9-014fa789fc6e","resolution":{"observed_at":"2026-08-14T10:13:16.802281Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:13:16.782599Z","title":null,"venue":null,"work_id":"8d797aa6-6b17-469b-bab6-b5124542f52e","year":1958},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":86,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.592601Z"},"links":{"citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:378dbfc9500ddb41588f7735fa753977aac25b4164435f666d6d2ebe575bd144","observation_id":"3809e3ad-2bc5-4860-a676-18bd9b699db8","resolution":{"observed_at":"2026-08-14T10:13:16.787172Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:13:16.769147Z","title":null,"venue":null,"work_id":"63b84937-e987-4316-8bcb-0b30e7de9291","year":1964},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":87,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.596904Z"},"links":{"citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:44a11a4dd8527124a5ef82c5377d6424a08235aae0797f6e6e0cd469e8bf904f","observation_id":"90b7f70b-280b-49f8-95f2-04fd9b30c118","resolution":{"observed_at":"2026-08-14T10:13:16.773604Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:13:16.554824Z","title":"McKinney, in Proceedings of the 9th Python in Sci- ence Conference, edited by S","venue":null,"work_id":"637a878a-6207-4599-991e-238c818fe9cc","year":2010},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":88,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.663173Z"},"links":{"citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:c5bcdc6df15b2c60fa9994e590351d2a51d9d9889a83eaf41f300b1a40715082","observation_id":"e6502d0f-9bcd-4683-8c14-140ee0215b3d","resolution":{"observed_at":"2026-08-14T10:13:16.559647Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:13:16.725048Z","title":null,"venue":null,"work_id":"03c80e61-43d3-4100-9186-8b1b1cfa3b33","year":1962},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":89,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.604893Z"},"links":{"citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:3737c1ee722b05e9ee2712cf0c79fc2498dc0ac33f63deb9fd964be3b7c3a247","observation_id":"e086f330-9c4b-469e-bcef-29e3193689c0","resolution":{"observed_at":"2026-08-14T10:13:16.736611Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:13:16.692394Z","title":null,"venue":null,"work_id":"403e102d-69f3-4f99-8252-33e0f54c7a97","year":null},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":90,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.608937Z"},"links":{"citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:81d4c73f7b06fe33d38db2d5fcc5503455bdc2c000767ff81f772561362f2796","observation_id":"5115db76-e697-41c2-891b-f5069a1d925e","resolution":{"observed_at":"2026-08-14T10:13:16.705620Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:13:15.612592Z","title":"Jamio lkowski, Reports on Mathematical Physics 3, 275 (1972)","venue":null,"work_id":null,"year":1972},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":91,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.612592Z"},"links":{"citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:9a99310b47f7e718614b1379b260d7715f765114d00e1eef60a8501d694ad63e","observation_id":"7435b678-508e-456b-9e1c-7f178976cd1f","resolution":{"observed_at":"2026-08-14T10:13:15.612592Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:13:16.671181Z","title":null,"venue":null,"work_id":"c3441330-e348-4d11-817c-6438ed8733c7","year":null},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":92,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.616757Z"},"links":{"citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:096c4582e20b170548e4a9409abd37ee679c02e0b012e300b113ad2f8f17f793","observation_id":"86df1b92-a366-42d0-9e11-9dd745b793c6","resolution":{"observed_at":"2026-08-14T10:13:16.675386Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:13:16.658180Z","title":null,"venue":null,"work_id":"5cc87e20-7f48-4055-8f62-2c69b109fbc4","year":null},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":93,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.622186Z"},"links":{"citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:8389898a09a0e805a8e0be074bf79bad84ea90f127223df0e65d4248335b1b0c","observation_id":"fee8f27d-a890-41b0-b562-61f125629287","resolution":{"observed_at":"2026-08-14T10:13:16.662590Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:13:16.645137Z","title":"F¨ osel, P","venue":null,"work_id":"4ab49074-c7bb-42b7-81c9-9f5be41b2469","year":2018},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":94,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.627161Z"},"links":{"citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:f1d19382452609964b1dc1cb3baccba3f0abfe4174c840d6860be4c64405f9bf","observation_id":"825dfa29-f1fb-4f91-a732-77c53d84e47a","resolution":{"observed_at":"2026-08-14T10:13:16.649925Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:13:16.631129Z","title":"Gatti, Design of Experiments for Reinforcement Learning, 1st ed","venue":null,"work_id":"1a37032e-de77-4e2f-9af3-1202374dd7a3","year":null},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":95,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.632290Z"},"links":{"citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:0fad0a6f054622d041ea8fca5df962f6f1a02c912c42a9d973f61ab20e36ea9f","observation_id":"055fc5f5-787f-428b-b5ad-423569ce2fa8","resolution":{"observed_at":"2026-08-14T10:13:16.635431Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:13:16.616253Z","title":null,"venue":null,"work_id":"7b459139-5430-4701-abdf-9d617ca20ded","year":2013},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":96,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.636726Z"},"links":{"citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:16735c58cc86c9761176a01ac9f0ebe41ed421c3b6cb5f9eecee2417dc34bc40","observation_id":"f519737d-54d5-4a42-b67f-30664e1eee02","resolution":{"observed_at":"2026-08-14T10:13:16.620724Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:13:15.640775Z","title":"Diamond and S","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":97,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.640775Z"},"links":{"citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:05e4f973883b1c47a412950f76e2fe3f80ee9f504d12db1db0ef1dc64b961c1b","observation_id":"e63e0c7e-375b-445a-9bfe-768c33fff27a","resolution":{"observed_at":"2026-08-14T10:13:15.640775Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:13:16.589562Z","title":"Agrawal, R","venue":null,"work_id":"765635e7-a3b8-499c-b34e-2cf8c6f3226b","year":2018},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":98,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.645649Z"},"links":{"citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:96da7cbb1cccbe86e35f4fe1501d400f4d51fb3b863cde506b7269aabbcbaf82","observation_id":"2dfebc08-ea28-4d6d-aae6-a0224b48855b","resolution":{"observed_at":"2026-08-14T10:13:16.594662Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:13:16.576549Z","title":"P´ erez and B","venue":null,"work_id":"82050f7d-3f98-4935-8ae2-905d558aeec9","year":2007},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":99,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.650691Z"},"links":{"citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:ed01ebf96c65b926f435331085dd038387d94f4e414ddc356af3e2a2cbc8f391","observation_id":"fd84e85b-57cd-4911-9522-c0bbd8ee9e47","resolution":{"observed_at":"2026-08-14T10:13:16.580789Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T10:13:15.654703Z","title":null,"venue":null,"work_id":null,"year":2007},"citing_paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning","version":1},"reference_index":100,"source":"pdf_text","source_observed_at":"2026-08-14T10:13:15.654703Z"},"links":{"citing_paper":"/paper/1908.11762"},"observation_digest":"sha256:02246a369f476f120b2a53c05e7aa0e5dc073a5925f707cb7d2086520ebed1fa","observation_id":"a11b8371-ed61-4b60-9201-a82522847c9e","resolution":{"observed_at":"2026-08-14T10:13:15.654703Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"1908.11762","last_updated":"2019-08-30T14:37:05Z","latest_version":1,"primary_category":"quant-ph","snapshot_observed_at":"2026-08-15T02:08:15.792248Z","submitted_at":"2019-08-30T14:37:05Z","title":"Classifying single-qubit noise using machine learning"},"reference_resolution":{"displayed":100,"state_counts":{"malformed_identifier":1,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":70,"verified_exact":13,"verified_fuzzy":16},"total_outbound_references":113},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"thesis":"As of 15 August 2026, this Paper Citation Record lists 100 of 113 outbound references and 0 inbound Pith citation observations for arXiv:1908.11762."}