{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:7EU5JFBFZA74WC5EFPVYUVBL25","short_pith_number":"pith:7EU5JFBF","canonical_record":{"source":{"id":"2205.09414","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"quant-ph","submitted_at":"2022-05-19T09:26:57Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"bfcf20c78c76d713b4f98ff8438abbd6999ef2e44bc105884ce884755a527e56","abstract_canon_sha256":"d5f8a15951452c5bf23b53cbf96db2f653785e9f7ce5b21993826ab10c6c478d"},"schema_version":"1.0"},"canonical_sha256":"f929d49425c83fcb0ba42beb8a542bd778270b2a93cbf8a5d3d34d99a34d5867","source":{"kind":"arxiv","id":"2205.09414","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2205.09414","created_at":"2026-07-05T04:24:44Z"},{"alias_kind":"arxiv_version","alias_value":"2205.09414v1","created_at":"2026-07-05T04:24:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2205.09414","created_at":"2026-07-05T04:24:44Z"},{"alias_kind":"pith_short_12","alias_value":"7EU5JFBFZA74","created_at":"2026-07-05T04:24:44Z"},{"alias_kind":"pith_short_16","alias_value":"7EU5JFBFZA74WC5E","created_at":"2026-07-05T04:24:44Z"},{"alias_kind":"pith_short_8","alias_value":"7EU5JFBF","created_at":"2026-07-05T04:24:44Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:7EU5JFBFZA74WC5EFPVYUVBL25","target":"record","payload":{"canonical_record":{"source":{"id":"2205.09414","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"quant-ph","submitted_at":"2022-05-19T09:26:57Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"bfcf20c78c76d713b4f98ff8438abbd6999ef2e44bc105884ce884755a527e56","abstract_canon_sha256":"d5f8a15951452c5bf23b53cbf96db2f653785e9f7ce5b21993826ab10c6c478d"},"schema_version":"1.0"},"canonical_sha256":"f929d49425c83fcb0ba42beb8a542bd778270b2a93cbf8a5d3d34d99a34d5867","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T04:24:44.447853Z","signature_b64":"hBXC1ubcg7zWONOOrZwSYl+RSNz/f8apjWBRG9czjFq5B095xVtv5IXFnaFIzq1sxdr7Ku2A1iWiSv86JFnNBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f929d49425c83fcb0ba42beb8a542bd778270b2a93cbf8a5d3d34d99a34d5867","last_reissued_at":"2026-07-05T04:24:44.447423Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T04:24:44.447423Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2205.09414","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T04:24:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"/IIOZcEpzSrGo3TNdCuIYE8M6wNTsRo8GYKFeX6LJlQLpN512gpP5Vxyjvb0+yx20g5rI3K9dKEmBSoBCYUXAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T06:23:55.820583Z"},"content_sha256":"56b6a545cba6db4633a53971dc6b4dd78af17fd8b888ae650acef708f50c3351","schema_version":"1.0","event_id":"sha256:56b6a545cba6db4633a53971dc6b4dd78af17fd8b888ae650acef708f50c3351"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:7EU5JFBFZA74WC5EFPVYUVBL25","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Machine learning applications for noisy intermediate-scale quantum computers","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"quant-ph","authors_text":"Brian Coyle","submitted_at":"2022-05-19T09:26:57Z","abstract_excerpt":"Quantum machine learning has proven to be a fruitful area in which to search for potential applications of quantum computers. This is particularly true for those available in the near term, so called noisy intermediate-scale quantum (NISQ) devices. In this Thesis, we develop and study three quantum machine learning applications suitable for NISQ computers, ordered in terms of increasing complexity of data presented to them. These algorithms are variational in nature and use parameterised quantum circuits (PQCs) as the underlying quantum machine learning model. The first application area is qua"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2205.09414","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2205.09414/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T04:24:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"smR0b5chDEJ8H4dD8/Un8Bqo2ihqhMl0p5NeMLynn4ENbYBm2B12EhN5HerJdEUCD858Lc34xpzhwZW03FAHCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T06:23:55.821179Z"},"content_sha256":"d76e09e5670cf59c23795a12c8706291e1a034e4016a1dea3ad2298a1af6c1e7","schema_version":"1.0","event_id":"sha256:d76e09e5670cf59c23795a12c8706291e1a034e4016a1dea3ad2298a1af6c1e7"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/7EU5JFBFZA74WC5EFPVYUVBL25/bundle.json","state_url":"https://pith.science/pith/7EU5JFBFZA74WC5EFPVYUVBL25/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/7EU5JFBFZA74WC5EFPVYUVBL25/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-07T06:23:55Z","links":{"resolver":"https://pith.science/pith/7EU5JFBFZA74WC5EFPVYUVBL25","bundle":"https://pith.science/pith/7EU5JFBFZA74WC5EFPVYUVBL25/bundle.json","state":"https://pith.science/pith/7EU5JFBFZA74WC5EFPVYUVBL25/state.json","well_known_bundle":"https://pith.science/.well-known/pith/7EU5JFBFZA74WC5EFPVYUVBL25/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:7EU5JFBFZA74WC5EFPVYUVBL25","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"d5f8a15951452c5bf23b53cbf96db2f653785e9f7ce5b21993826ab10c6c478d","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"quant-ph","submitted_at":"2022-05-19T09:26:57Z","title_canon_sha256":"bfcf20c78c76d713b4f98ff8438abbd6999ef2e44bc105884ce884755a527e56"},"schema_version":"1.0","source":{"id":"2205.09414","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2205.09414","created_at":"2026-07-05T04:24:44Z"},{"alias_kind":"arxiv_version","alias_value":"2205.09414v1","created_at":"2026-07-05T04:24:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2205.09414","created_at":"2026-07-05T04:24:44Z"},{"alias_kind":"pith_short_12","alias_value":"7EU5JFBFZA74","created_at":"2026-07-05T04:24:44Z"},{"alias_kind":"pith_short_16","alias_value":"7EU5JFBFZA74WC5E","created_at":"2026-07-05T04:24:44Z"},{"alias_kind":"pith_short_8","alias_value":"7EU5JFBF","created_at":"2026-07-05T04:24:44Z"}],"graph_snapshots":[{"event_id":"sha256:d76e09e5670cf59c23795a12c8706291e1a034e4016a1dea3ad2298a1af6c1e7","target":"graph","created_at":"2026-07-05T04:24:44Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2205.09414/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Quantum machine learning has proven to be a fruitful area in which to search for potential applications of quantum computers. This is particularly true for those available in the near term, so called noisy intermediate-scale quantum (NISQ) devices. In this Thesis, we develop and study three quantum machine learning applications suitable for NISQ computers, ordered in terms of increasing complexity of data presented to them. These algorithms are variational in nature and use parameterised quantum circuits (PQCs) as the underlying quantum machine learning model. The first application area is qua","authors_text":"Brian Coyle","cross_cats":["cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"quant-ph","submitted_at":"2022-05-19T09:26:57Z","title":"Machine learning applications for noisy intermediate-scale quantum computers"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2205.09414","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:56b6a545cba6db4633a53971dc6b4dd78af17fd8b888ae650acef708f50c3351","target":"record","created_at":"2026-07-05T04:24:44Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"d5f8a15951452c5bf23b53cbf96db2f653785e9f7ce5b21993826ab10c6c478d","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"quant-ph","submitted_at":"2022-05-19T09:26:57Z","title_canon_sha256":"bfcf20c78c76d713b4f98ff8438abbd6999ef2e44bc105884ce884755a527e56"},"schema_version":"1.0","source":{"id":"2205.09414","kind":"arxiv","version":1}},"canonical_sha256":"f929d49425c83fcb0ba42beb8a542bd778270b2a93cbf8a5d3d34d99a34d5867","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"f929d49425c83fcb0ba42beb8a542bd778270b2a93cbf8a5d3d34d99a34d5867","first_computed_at":"2026-07-05T04:24:44.447423Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:24:44.447423Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"hBXC1ubcg7zWONOOrZwSYl+RSNz/f8apjWBRG9czjFq5B095xVtv5IXFnaFIzq1sxdr7Ku2A1iWiSv86JFnNBg==","signature_status":"signed_v1","signed_at":"2026-07-05T04:24:44.447853Z","signed_message":"canonical_sha256_bytes"},"source_id":"2205.09414","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:56b6a545cba6db4633a53971dc6b4dd78af17fd8b888ae650acef708f50c3351","sha256:d76e09e5670cf59c23795a12c8706291e1a034e4016a1dea3ad2298a1af6c1e7"],"state_sha256":"a8e7c77dcc6150ab05fd06860b0cf407ffb9c4f916f59adaec17bef5f0c35db6"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ce58nw1bvp9cH7htaYh5dMFNsSdnC/xLeapIJ+tmECI9OpedgLdZE+E6BSt0sdVwNQhLM1GDh+TG9SqiSg7nAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-07T06:23:55.824869Z","bundle_sha256":"ec5338b9fcb45a2140ffdef8ecc456f5b8b47648c0ff2fd46a546b40d299e164"}}